Systems Constraint Theory (TOS). Theory of Constraints: Intrinsic Simplicity and Control of Constraints Drum Rope

In the theory of constraints ( TOC) many people are confused by two different aspects. The first of these is production improvement tools, including the Drum-Buffer-Rope constraint management method ( drum-buffer-rope). The second aspect that is becoming increasingly known and widely used is mental processes, which, according to CBT, are powerful tools, but they take some time and effort to understand and apply.

The theory of constraints, also known as constraint management, was developed by Dr. Eliyahu Goldratt. His views were presented to a wide range of readers in the best-selling book "The Purpose." In this book, the author introduced and explained the Drum-Buffer-Rope technology and the Five Focused Steps method. Thought processes were also identified in the book, but they were not discussed in detail. While some companies have used the concepts in this book to make significant improvements to their processes, others have failed to do so. And the reason for this is not the situation at all CBT and not the people who read The Purpose. The book is written in the genre of a novel, it introduces the reader to the concepts, but is not a textbook or implementation guide CBT.

Our goal is to give you a quick overview of the different tools so you can then make an informed decision about which one to use. There are special materials and organizations that can be contacted for a more detailed study if these methods are adopted.

By revising CBT An often overlooked fact is that many of the tools presented in the book must be used in the process of applying five focused steps that are used to identify and eliminate bottlenecks, or restrictions. During the elimination phase, various tools may be needed to improve the process.

6.1. Why "Target"?

The title of the book, “The Purpose,” has a special meaning. CBT is a management philosophy developed for application to a manufacturing organization. It begins with the preparation of a production schedule and an attempt to optimize the planning of the production plant. The question is asked: what is the purpose of this organization? The answer is making a profit now and in the future. It's important to understand this because, at the end of the day, most companies' primary desire is to make a profit. Non-profit organizations have a similar goal, the only difference is where the money received then goes and what it is spent on. Any type of activity of the organization must in one way or another contribute to achieving its goals. The concept of efficient productivity and the calculations based on it (all of which will be discussed in detail below) are based on this goal - making a profit.

6.2. "Drum - buffer - rope"

Although the Drum-Buffer-Rope constraint management method is used after identifying constraints in the Five Focused Steps stage, we will start with it because it is more familiar to many. As noted, this book is aimed primarily at small businesses in the manufacturing sector, so it is assumed that most readers have a manufacturing background. The Drum-Buffer-Rope method will be discussed specifically in the context of production, but it can be applied to any process. Keep this in mind as you begin to identify and eliminate limitations. They can also occur outside of your production process.

So what exactly is meant by limitation? A constraint is something that prevents a system from operating at a higher level. In a manufacturing context, a constraint, or bottleneck, is anything that prevents a company from producing as much output as it needs. Notice we didn't say "produce as much product as possible." You may not need to produce as much as possible to achieve your goals (this is related to the concept of efficient productivity, which will be discussed below). A constraint resource is a piece of equipment, area, tool, employee, or even established plant policy that prevents greater productivity.

The manufacturing process involves several stages in which various raw materials and components are processed and assembled into the finished product. Each stage of this process is characterized by its production capabilities, or production capacity. Companies often look at each step individually, rather than looking at the entire process as a whole. Many improvement proposals focus on improving the efficiency of only one or a few steps of the production process. In essence, most methods for assessing the performance of an organization and its managers are based on assessing the effectiveness, or productivity, of individual stages of the process. In the theory of constraints, this way of thinking is considered fundamentally wrong.

Figure 6.1 shows the sequence of production steps discussed in Chapter 4, indicating the capacity of each section. The drilling area is a constraint (bottleneck) because it limits the performance of the entire system. For a clearer understanding of the situation, let's consider it in more detail. Of course, it is easier to identify the limitation

using a simplified example, where operations are arranged in a certain sequence. In a traditional manufacturing environment, activities do not always follow each other strictly, which leads to some difficulties.

The theory of constraints states that the entire system must be considered and that optimizing one step in a process will not necessarily achieve the goal. This situation is difficult for many to accept, but if you look back and think about it, you will find it makes sense. Let's take an example from the chapter on Lean Manufacturing (Chapter 4) - a simple three-step process of drilling, soldering and assembling a model XL 10. In this case, the capacity of each stage is: for the drilling process - 12 products per hour (five minutes per product), the soldering process - 20 products per hour (three minutes per product), the assembly process - also 20 products per hour.

The maximum output of this three-stage process is 12 products per hour, which is equal to the productivity of the first stage - the drilling process. Even if it were possible to double the productivity of the soldering process by installing additional equipment, it is not worth even thinking about. Increasing the productivity of the soldering process will have absolutely no impact on the overall performance of the system. To increase overall productivity, it is necessary to increase the power of the drilling process, since this is the part of the system that has the lowest production capacity.

If you have not yet understood why the maximum system throughput is only 12 products per hour, while the productivity of the soldering and assembly areas is 20 products per hour, let's take a closer look at this example. First, let's assume that a product moves from stage to stage one item at a time: once processing of one item is completed, it moves to the next stage rather than waiting for a whole batch of items to be formed and the entire group to move. So, we begin to send one product at a time into production. We will send 20 pieces in total.

How long will it take to process 20 products in the first section - drilling? The area operates at a capacity of 12 pieces per hour, so processing 20 pieces will take about 1 hour 40 minutes (20 / 12 = 1.67 hours, or 1 hour 40 minutes). Since the products move through the stages of the system one at a time, immediately after the drilling operation the product enters the soldering area. Products leave the drilling area at a rate of 12 pieces per hour. At the next stage - soldering - 20 products per hour can be processed, that is, 20 pieces per hour can leave the soldering area, but only 12 arrive here. Consequently, the soldering installation will be idle for some time. The assembly and soldering sections can also produce 20 products per hour, but 12 products leave the soldering section per hour (since that is the amount supplied to this link).

As a result, all 20 products will be processed at a rate of 12 pieces per hour. You may still think that if the last link in the chain produces 20 pieces per hour, then the system's productivity is the same. Let's analyze the process again. Products leave the drilling section at a rate of 12 products per hour, and therefore enter the soldering section at the same speed. The assembly area can process 20 pieces per hour, but only 12 pieces per hour arrive. Accordingly, the same 12 products leave this stage every hour. The assembly area could process 20 items per hour if they came into the area in that quantity, but this does not happen.

As you can see, investing resources into increasing the production capacity of soldering or assembly processes is futile. It is necessary to concentrate efforts on the drilling process - the area of ​​​​lowest power. Figure 6.2 shows a system with an increased capacity of the assembly process. It is easy to see that the limitation remains in the same area, so that efforts to increase the power of the assembly process are wasted.

If you still believe that you can achieve a system throughput of 20 products per hour, then consider the situation from the other side. Let's create a stock and see what happens. Let's say we have formed a stock of products and put it into production at the stages of soldering and assembly, so that these areas operate at nominal productivity (Fig. 6.3).

So what happens if you have some stock? (We don't ask ourselves how we formed it.) Let's look at all the stages separately. The assembly area can process 40 products per hour, with 80 products ready for processing. Thus, 40 pieces will come off the production line every hour. Considering only the assembly process, we see that it would be possible to work at maximum productivity for two hours.

Now let's look at the soldering process. The soldering area can process 20 products per hour, with 80 products ready for processing. This means that this area can operate at maximum productivity for four hours. At maximum process productivity, every hour 20 products leave the soldering area and enter the assembly area. In two hours, 40 units will accumulate, awaiting arrival at the assembly site. The initial 80 items will take two hours to process in the assembly area, so by the time they are completed, another 40 items will be waiting in the assembly area. This means that the assembly will work at maximum productivity for three hours.

With a stock in place, the assembly section can operate at maximum productivity for three hours, and the soldering section for four hours. After three hours, the assembly area will no longer be able to operate at maximum productivity, the entire supply will be used up, and we will be left with the amount that comes from the soldering area, which is 20 products per hour. After three hours of operation, the soldering area is still running at maximum capacity, and the assembly area is still running at 20 units per hour, even though it can process 40. What happens after four hours of operation? The soldering section will run out of products, and its work will again be limited to the quantity that comes from the drilling section (12 products per hour). So, after four hours of work, we return to a productivity of 12 products per hour, which is the limit for the limiting resource.

For a while, we deluded ourselves into thinking we could get better performance out of the system. Miraculously, we built up some reserves, allowing two sites to operate at higher yields. However, how could these reserves arise? To create them, you need to slow down or stop the operation of the equipment for a while. If the equipment is idle, then the products are not produced. Since there is no output for some time, and then work continues at increased productivity for several hours, the average productivity will still be the same 12 or less products per hour. If the limiting resource is running continuously and the other resources are running without long interruptions, the system produces 12 units per hour. If the limiting resource is idle or operating at reduced capacity, the performance of the entire system is reduced.

Now let’s change the capacity of the processes and put the limiting resource at the end instead of the beginning (Fig. 6.4). For example, if we change the power of the drilling and soldering processes, they will be the same - 40 products per hour. This means that the processing of products will take one and a half minutes at the drilling and soldering stages and five minutes at the assembly stage (initially there were five minutes for drilling and three minutes for soldering and assembly).

Now, once products are sent to production, it will be possible to process 40 products per hour in the drilling and soldering areas, however, when they reach the assembly stage, the capacity will decrease. What will happen? Semi-finished products will begin to accumulate in the assembly area. In a traditional enterprise, it is believed that every machine, area or department must operate at maximum productivity. Downtime is bad! You paid a lot of money for the equipment, you pay the workers, and therefore it is necessary that the equipment is constantly working. In addition, many methods for assessing the performance of an enterprise and bonus systems are based on the efficiency of using computer time. If you are a drilling supervisor and you are being evaluated on how efficiently you use your machine time, wouldn't you be working at peak productivity? Of course you will! What will happen in the next sections of the production line, what will happen to the system as a whole? Let's get a look.

If products are sent into production so that the first two sections operate at maximum productivity, then, as already noted, semi-finished products will begin to accumulate in the assembly section. Moreover, different types of products will be processed, so that stocks of various semi-finished products will accumulate. This fact will present us with a problem: how to determine which type of accumulated semi-finished products to process first? You can guess that priorities will constantly change, you will start producing one product, then switch to another when the consumer needs it. However, let's leave this problem aside for now.

All this is wonderful, but what does the drum, buffer and rope have to do with it? Let's figure it out. You're probably thinking: The first thing to do is increase the performance of the limiting resource. In theory, this should increase the performance of the entire system, but this assumption needs to be tested. There are several important issues to consider. Firstly, is the productivity really 12 pieces per hour? Even if a system has the potential to provide such performance, this does not mean that it actually provides it. Planned or unscheduled downtime caused by equipment breakdowns, repairs, labor shortages, tool changes, or simply lack of work results in actual product output not meeting plans or expectations. It is necessary to investigate the reasons for what happened and see what can be done to eliminate them and increase productivity. Secondly, you need to ask yourself whether productivity really needs to be increased. Do you sell everything you produce, or are the products just adding to your inventory? Of course, there may be good reasons for holding a reserve, but these should be carefully considered.

As already noted, the overall performance of the system depends on the limiting resource. The limiting resource (or bottleneck) is the drum, which determines the tempo. Remember Ben Hur and the man on the galley who beat out the rhythm for the rowers on a huge drum.

In the "Drum - Buffer - Rope" method, the drum sets the rhythm of work for the entire system. The drum is a limitation, a bottleneck in the system, since it is the least productive stage. As can be seen in the example (Fig. 6.4), the assembly area determines the pace for the entire production process. We will use this “drum” and use it to control ourselves to avoid overloading the system or creating unwanted inventory (did you notice that this is unwanted inventory?).

Since the drum sets the tempo for the system as a whole, it is necessary that all links in the chain obey this tempo. The drum will determine the flow of materials into production. If you feed materials at a rate that can be processed in the drilling and soldering areas, you will end up with a large volume of semi-finished products in the assembly area, which cannot process them quickly enough. As you move to more complex systems, getting materials into production at drum (resource limiting) pace becomes even more important.

So, it’s clear what a drum is. Now let's look at the buffer. These are buffer stocks, which is the amount of stock you keep in front of the reel. If the drum, or limiting resource, is idle for some reason, the performance of the entire system is reduced. The purpose of the buffer is to help provide the drum section with materials for work and to prevent downtime. In our example, the buffer will be created before the assembly section. We don’t want this site to be idle, and therefore we keep a certain supply of semi-finished products in front of it in order to always be able to provide the site with work. The buffer quantity does not just need to be created - it needs to be planned and controlled. You should not accumulate too much inventory, as this leads to other problems, but you should not allow it to reach zero levels either. The quantity of inventory must be maintained at the required level by producing more or less quantity in previous stages. If we want to increase the buffer size, we will increase the processing speed or the amount that is processed in the system until we reach the required level. If we need to reduce the buffer, we will slow down the production speed or reduce the number of processed products.

And finally, we have rope. The rope connects the drum, that is, the tempo-setting operation, with the supply of materials to production. It is not advisable to feed volumes into the system at a rate greater than the drum rate (unless you need to create a buffer reserve). A rope is a signal that restricts the flow of materials into a system. When planning the receipt of materials into the system, the state of the limiting resource (drum) and buffer (buffers) should be monitored. It may not be easy to accept, but there may be times when no materials or items are allowed into the system for processing at all. Some machines or areas of the plant will be idle. The idea that everyone and everything needs to be constantly employed is so ingrained in many manufacturing plants (and other organizations) that it is sometimes very difficult to combat this stereotype. The statement is especially true in cases where managers are assessed and rewarded based on the efficiency and productivity of individual sections or divisions. However, do not forget that we are interested in the operation of the system as a whole, and not of any section or department. Let's see what the system is now (Fig. 6.5).

Do not forget that the operation of the system as a whole is being considered. The performance of the entire system is equal to the performance of the limiting resource. Increasing productivity, quality of work, efficiency in any other part of the process is a waste of time and money. Equipment downtime and personnel idleness are sometimes necessary. This does not mean that people can sit and do nothing. While the main production work on the site is suspended, there will always be many useful things to do. Workers may be involved in equipment maintenance or cleaning, undergo training or training, or help in other areas. Without a doubt, many ideas can be proposed to keep workers productively occupied. For example, staff may work to increase the capacity and efficiency of a limiting resource. Wouldn't that be the most useful?

In the described case, the production process is quite simple, since it includes only three stages. Of course, most manufacturing processes are not so simple. If you operate a traditional manufacturing setup, production is likely divided into areas with different types of equipment in each area. Several groups and types of products are produced, and there are various assembly units and semi-finished products. You have a fairly complex production schedule, conflicting and changing priorities, and perhaps even a dedicated team of freight forwarders.

In such an environment, it is sometimes difficult to identify the limiting resource. However, there are probably some guesses as to where the bottleneck of the process is. If you are not sure of the correctness of the conclusions, then the first thing you should pay attention to is the area where stocks of materials accumulate.

Regardless of the complexity of your production structure, the concepts we've discussed work the same. There may be a need for multiple buffers, but there will only be one bottleneck in the system (at least one most important limiting resource), and it will set the pace for the entire system. The restriction, or drum, will determine the flow of materials entering the system using a rope - a kind of signal. Consider Figure 6.6, which shows a more complex system that still uses the Drum-Buffer-Rope mechanism.

The flow of materials into the system is controlled by a limiting resource—grinding. Not all products are processed at the grinding stage, so materials for these products are supplied as needed. In any case, caution should be exercised. An ordinary (non-limiting) resource can supply materials to a limiting one. However, it is obvious that it is not worth overloading such an ordinary resource, so as not to jeopardize the supply of the limiting one. Let's look at this below.

6.2.1. Buffers and their management

By buffer we mean buffer stocks because we create them in front of limiting resources to prevent downtime at bottlenecks due to lack of work. It might be more accurate to call these buffers time buffers. The same problems we face when managing production capacity also arise when managing buffers. You work across a range of products and need to have standard power or buffer analysis and management techniques in place to help you measure and manage power or buffer size. Very often time is used as a standard.

Let's demonstrate this using an example of processing XL 10. This model requires three minutes for drilling and soldering and five minutes for assembly for one product. Another type of product, say RG 7, will require for one product four minutes for drilling, five minutes for soldering and eight minutes for assembly. If we operate in pieces, then a buffer of 100 pieces actually means different sizes of buffers for these two items; 100 pcs XL 10 transforms into 8.3 hours of assembly site work, and 100 pieces RG 7- at 13.3 hours. If the buffer serves to protect the limiting resource from being idle due to lack of work, then it is important to know exactly the amount of work in the buffer, and not just the number of items. This is why the time buffer is so convenient to use.

Another important question: how big should the buffers be? To give an answer, let's look again at why they are needed. This is protection for the bottleneck. We don't want the limiting resource to remain idle, since it determines the performance of the entire system. How is the buffer created? Resources that supply the limiting resource also fill the buffer. The limiting resource should process items at a constant speed (ideally, of course), as we concentrate our efforts on keeping it running at all times (except for downtime when necessary). Fluctuations in the performance of the supply operation affect the buffer size.

If supply operations experience problems that cause disruptions, the buffer will not be replenished and will begin to decrease. If you want to increase its size, all you have to do is improve the performance of supply operations. This is unlikely to be a problem since these operations have higher capacity than the limiting resource. The size of the buffer should be determined by how large the fluctuations in the performance of supply operations are, what kinds of problems cause supply disruptions and a reduction in the buffer.

The buffer size should be at least as long (remember that's a time buffer?) enough to restore service after a certain number of interruptions in supply operations. As shown in Chapters 5 and 7 on Six Sigma and Quality Control, deviations tend to follow a pattern. This means that the duration and frequency of production disruptions will follow a pattern that can be used to determine the size of buffers.

If performance fluctuations are small enough that you can recover from outages without using a buffer, you can avoid using a buffer altogether. As variations in the duration or frequency of outages increase, the buffer size must also be increased. In addition, as with any type of abnormality, rare, anomalous events may occur. Something serious, such as a complete failure of a piece of equipment that will take two weeks to replace, is likely (hopefully) a rare event. It is impossible to insure yourself against any eventuality, so you need to choose a level of protection that is convenient for you. Take all of this into account when determining your buffer size. Of course, the easiest way is to start with an approximate or even arbitrary size.

There is nothing wrong with making a reasonable forecast and starting to implement it. Spend at least some effort on this. The starting point is not as important as the next steps. Once the buffer size is determined and the buffer is created, it must be monitored and managed. You need to compare the actual buffer size with the planned one you suggested. The actual buffer size will fluctuate as the performance of the operations supplying the buffer fluctuates. The productivity of these operations varies for two reasons: due to uncontrollable disruptions (normal variances) and as a result of planning the production schedule and activities to ensure that the buffer size matches plans (planned variances). Buffer management comes down to monitoring its state and control. It is advisable to monitor the size of buffers both as a measure of operational efficiency and as a control mechanism. If the buffer size does not change, then you are not using it up and it is not protecting you from anything. It just takes up space, requires monitoring, but isn't really that necessary. In reality, this is not entirely true - the buffer does something in this case, but not what is required. In short, monitor the size of your buffers, manage them, and change them when appropriate.

We looked at one of the most famous aspects CBT(the “Drum - Buffer - Rope” method), however, this theory contains several more important stages that may have to be completed before moving on to the method we have described. Let's consider another aspect CBT, which will help us reach the stage of using the Drum-Buffer-Rope method - five focused steps.

6.3. Five Focused Steps

Usually the impetus for change is a serious problem or crisis. Some companies have the foresight to put systems in place to monitor processes and make changes before a problem arises, but in most cases it is a serious problem that forces us to look for ways to improve. More often than not, this is a response rather than a planned action. Something unwanted happens, someone signals it, and employees try to do something. This “something” will most often just be a half-baked quick fix that doesn’t actually solve the problem.

Ideally, systems and processes should be reviewed and analyzed regularly to make changes and improvements before problems arise. But even if you don't and are faced with a problem that needs solving, five focused steps are a great start.

Five focused steps are used to determine where and how to invest time and energy to make process improvements. You should find out what exactly needs to be changed, to what and how, considering this in the context of achieving the goal of your enterprise. The five focused steps involve the following actions.

• Identify system limitations.
• Decide how to exploit the system's limitations.
• Bring all other elements of the system into accordance with the previous steps.
• Remove system limitations.

If the restriction was removed in the previous step, return to step 1 again, but do not allow inertia to become the cause of the restriction.

6.3.1. Step 1: Identify System Limitations

This step seems clear enough, but it is not so simple. Manufacturing processes are rarely uncomplicated and problems are not always understood. Problems usually begin with consumer complaints (for example, the order was not shipped on time or was not fully completed, the consumer received defective products, the promised deadlines did not meet customer requirements, the production cycle was too long, etc.).

Instead of real attempts to solve the main problem, attention is often focused only on issues of shipment timing. Production schedules, if they exist, become meaningless. The order of order fulfillment is redistributed in the workshops in such a way as to satisfy those who demand their way loudest. Work on partially completed orders is suspended and postponed in favor of new last-minute orders to be completed on site right now. Buyers are called, cajoled, and bribed with the promise that materials ordered will be shipped today, and those not yet ordered will be ready tomorrow. You yourself know how this happens.

All of the above are signs that the system is out of control, and you've probably seen how this happens. There must be a more attractive option. Instead of running back and forth trying to put out the fire, some changes must be made to processes and systems, otherwise such a rush is guaranteed to be constant. The rhythm may slow down for a while, but sooner or later another consumer will make a claim - and you will start working in fire brigade mode again. Therefore, changes need to be made. But you can’t act at random; it’s important to know what specifically requires changes. Before you do anything, you should find out what exactly needs to be replaced. Finally, you need to determine how to make changes. This is often the hardest part. You know what needs to be done, but how to do it? Let's look at this a little later.

The best place to start is by looking for an operation that is stockpiling inventory. Stockpiling of inventory is a good indicator of a bottleneck, but this fact should be verified. Constraints are mainly of three types: in enterprise policy, in resources and in materials. The most common are restrictions in the company's policy. It would seem that they are the easiest and cheapest to overcome, but this is not always the case. Constraints in established practice include lot sizes, shipping rules, etc. For example, products are manufactured in specific batches. Do you know why the batch sizes are the way they are? Probably not. Most likely, the answer will be “Because that’s how we do it” or “We’ve always done it that way.” Why was priority given to these sizes? Why are the products produced in this order? It is often difficult to find answers to these questions, and such limitations in established practice can affect the performance of the entire system. It is necessary to find out what is the reason for the restriction.

Resource constraints do not arise as often as you might think. Problems are usually related to the way the system is supplied with work, and not to any specific link within the system itself. Resources are the equipment, tools, personnel, and everything needed to produce your product. Resource constraints can be easily overcome, at least in theory. A limitation within a limitation can only be the decision to attract more resources, as well as to identify and assess the needs for additional resources.

Limitations in materials are not widespread, but they do occur. Make sure that the limitation is actually related to the material and not to established practice. Are the materials out of stock, insufficient, or simply not anticipated, planned for, or ordered in time? This is the difference between a material constraint and a practice constraint: whether materials are actually missing or whether it is a planning error.

6.3.2. Step 2: Decide How to Use System Limits

Now you need to decide what to do to overcome the limitations. This is in some way a stage of reworking the process diagram. You need to determine what your improvements will be. The second step is specifically for situations where new procedures or rules need to be developed. The need to attract new resources or modify existing ones is also clarified at this stage. Throughout this phase, the main goal and concept of throughput must be kept in mind.

The way a constraint is overcome is partly determined by the type of constraint itself. Whatever it is, the improvement or new version of the process will be similar to it. Since it is likely that the limitation is due to established practice, the solution to the problem is to change a process or introduce a new one. First of all, you should analyze the existing process and draw up a flowchart of operations. It is difficult to change something if you have a vague idea of ​​the situation at the moment. Many people believe that they know the current processes well, but until the diagram is depicted on paper, the state of the process is unknown.

Once the current state of affairs is clearly reflected, you can begin to look for ways to improve the process. This is an area where many of the other tools you are familiar with can come in handy. Perhaps the constraint appears to be a resource constraint because you are unable to process enough materials to fill customer orders and meet their production cycles. However, it may be that the limitation is due to established practice, the system of working according to the traditional production scheme. Instead of continuing to operate in this manner and trying to solve the problem with an additional shift or more pieces of equipment, try moving to cell production and using lean manufacturing methodology.

The problem may be related to requisition prioritization or planning because the information systems do not meet your needs. A limitation in this case may be the lack of information or poor processing of it. This limitation can be overcome with the help of an improved information system - by introducing an enterprise resource planning system ( ERP). Six Sigma can be used to identify system limitations and develop improved processes. If a constraint arises due to lack of inventory or poor inventory control, it can be overcome by using a cycle counting system.

6.3.3. Step 3: bring all other elements of the system into line with the previous steps

What does it mean to bring all other elements of the system into line with the previous steps? Since the constraint determines the efficiency of the entire system, it is necessary to focus efforts on it. There is no need to worry about upgrading other parts of the system as it will not affect the overall efficiency of the system. But you must ensure that all remaining parts are running in sync with the limiting resource so that it is never idle.

Subordination means that all other parts of the system supply the constraint, that is, resources that do not limit performance supply the constraining resource. You must manage these facilities so that the limiting resource is sufficiently loaded. You don't want to provide too much work (that's exactly what we're trying to avoid), but you also don't want the limiting resource to be idle. The supply of materials to the system, the production schedule and the ordering of orders in other parts of the system must be synchronized with or subject to the constraint. All efforts are focused on achieving maximum efficiency and productivity of the limiting resource. This is submission.

6.3.4. Step 4: Remove system restrictions

Removing a system constraint means turning a limiting resource into a non-limiting one. Once you've done everything you can to maximize system throughput—focusing on improving the limiting—you can invest in increasing the limiting power. Let's return to our example. If the build process has been a limiting resource and everything has been done to improve its performance, then another plant or build area may need to be added to increase system performance.

Let's say a lean manufacturing system is implemented, work cells are organized and a pull system is introduced to overcome the constraint and you still need to improve productivity. In this case, you should consider installing additional equipment, creating new cells, hiring additional workers or introducing additional shifts to increase capacity. However, you should not do this until you have tried all other options to resolve the restriction.

6.3.5. Step 5: back to step 1?

If the constraint was removed in the previous step, return to step 1 and do not allow inertia to limit the system. Ultimately, after making all the improvements, removing the limitation and increasing the throughput, you need to go back to step 1 and start over. The warning about inertia leading to limitation means that you shouldn't just keep doing what you've been doing. It is necessary to ensure that the constraint is defined correctly and to identify any new constraint that may have unexpectedly arisen during the work.

After completing the first four steps, identifying the constraint, making adjustments to the process, and eliminating the limiting resource, a new constraint will appear. It should appear. Even if you have made great improvements and increased the throughput and power to the highest level in the system, there will still be a limitation in the process. Remember that your goal is to make money, now and in the future. You want to continue to increase your income. In this case, sales volumes below maximum capacity will become a new constraint that will have to be overcome in order to utilize the increased production capacity.

6.3.6. Changes

This study brings up the important point that things need to change. Organizations don't change easily. Change management is an overlooked area in many organizations. For improvement to become a reality, change must be introduced and managed effectively. So how do we make change?

People are believed to be resistant to change. This is not true: people like to change. They change constantly. Problems arise when attempts are made to force employees to change. Nobody likes this, people do everything they can to resist the pressure. The question arises of how to get employees to want change and achieve the changes you want to make.

One way to attract people is to “bribe” them into making the changes you want. This method has its advantages, but it is very passive. “Okay, we agree that changes need to be made. What's next?" - this approach usually does not lead to the necessary transformations. Other methods are used: requests, persuasion, even bribery, but they are not very effective. So what can you do to convince people to change?

Let's ask ourselves: why do people change things? What makes them want change? People change when they see a benefit for themselves: “What will this give me?” The benefits can be both material (money, easier work, shorter working hours) and intangible (increased status, job satisfaction, a sense of control over the situation). It is likely that staff will change the process when making the same money, working fewer hours or doing easier work. Some employees are ready for change, provided they receive a new, more respectable-sounding title. If people can feel satisfied with their work, feel that their efforts were well spent, they themselves will want change. If the change is their idea (or they think it is), then employees are eager to begin the change process. And if they also control the process (because it is their idea and they suggest what needs to be done and how), then they will fight for these changes. Conversely, people will be upset and disappointed if things remain the same.

This is the trick: making people feel a sense of personal ownership, control over the change process; push them to come up with the idea to change something; convince them to believe that the process needs to be modified because its current state is unacceptable. Dr. Goldratt recommends the Socratic method (the art of obtaining truth by identifying contradictions in an opponent's judgment) and the use of thought processes to bring about the necessary changes. We will discuss these methods in Section 6.5, but for now we will consider in detail another aspect of the theory of constraints, which we touched on a little earlier.

6.4. Effective performance and reporting based on it

Sometimes it can be difficult to determine whether you are making a profit or not. Accounting and costing rules do not facilitate the simplicity and clarity of such valuations, at least for the layman. Being profitable on paper doesn't mean you're actually making money. A positive balance is a more accurate indicator of profitability, especially for a small business.

The theory of constraints offers an even more precise way of assessing profitability (i.e., goal achievement). The concept of efficient productivity and accounting reports based on it acts as an alternative to traditional cost-based calculation methods. Many confirm that effective performance-based reporting is more powerful in determining whether you are getting closer to your goals. Despite this, this type of calculation has not yet become widespread. Until performance reporting is recognized by accounting standards bodies and government regulators, and is included in university accounting curricula, it will not be easy to gain acceptance as a method. Of course, this doesn't mean you can't or shouldn't use it. Any business can use valuation techniques that help determine whether it is making money. The problem will only be the need to express the results of reporting on effective productivity on the basis of costing and financial accounting.

What is effective performance? Whether you have been trained in traditional costing or are simply familiar with it, the concept of efficient productivity will require some rethinking. If you don’t understand accounting, then you need to at least familiarize yourself with its basics (although you wouldn’t wish this on your worst enemy). Effective productivity is the rate at which a business makes money. This is not just the yield of suitable products. Remember: to have effective productivity, you need to sell products (in other words, sales are necessary). If you simply produce items that replenish inventory, you get productivity, but it is not efficient (Figure 6.7).

It sounds simple enough (in fact, it is). The difficulty lies in relating this method to the complexities and rules of traditional

accounting and changing mindsets. Read the definition again: the rate at which money is made. If there are no sales, you are not making money, therefore there is no effective productivity. Effective productivity is not about total sales revenue, but about money earned. This is the money received from sales, minus the money spent on producing and selling products. The difference between efficient productivity and net profit is that in conventional accounting, net profit is based on the cost of production, which includes the allocation of overhead and wage costs, while in efficient productivity accounting these costs are treated differently.

According to CBT, together with effective productivity, two more quantities are used: operating costs and inventory costs. IN CBT The concept of reserves is different from the traditional one. In accordance with CBT, inventories are the funds spent on purchasing everything necessary to produce products that will be sold. Inventories include all business assets, such as capital and auxiliary equipment, buildings, and all materials and components, but do not include wages and overhead costs. Operating expenses are defined as the funds spent to convert inventory into efficient productivity. Operating expenses are salaries and overhead, sales commissions and other related expenses.

IN CBT net profit is calculated as follows:

Net profit = effective productivity - production costs,

and return on investment:

Return on investment = net profit / investment,

Return on investment = (effective productivity - production costs) / investment.

These calculations are somewhat different from the traditional method, but they are very useful tools for assessing the performance of your company, the function of which is to provide businesses with the opportunity to better evaluate financial performance. Financial calculations and costing remain relevant, but they do not provide enough information to help achieve the goal.

Calculation methods in CBT evaluate the system as a whole (effective productivity is all the money the company earns, it does not evaluate any individual part of the production process). Traditional evaluation methods are used primarily to evaluate the effectiveness of individual parts rather than the system as a whole. As noted in the section on the Drum-Buffer-Rope method, what matters is the efficiency of the entire system. Determining the performance of individual parts of the system as a preliminary step before making changes is pointless unless you are working to eliminate the limitation.

6.5. Thought processes

Five focused steps are needed to get your efforts on the right track. "Drum-buffer-rope" is a method of planning the work of an enterprise and managing production and inventory. Thinking processes are needed to identify underlying problems, develop improved processes, and overcome obstacles that arise. You need to know what to change, what to replace with, and how to implement those changes. Thought processes are methodologies designed to apply logic to ensure that given steps are worked through efficiently and thoroughly. The purpose of thinking processes is to put logical thoughts and arguments on paper so that they can be evaluated, discussed, and revised as needed. Thinking processes use logical diagrams that resemble flowcharts.

6.5.1. "Dispersing the Fog"

Although the Socratic method is very effective in identifying root causes, it is often not sufficient to find a solution to the identified problem.

The root cause is most often a conflict between two opposing forces. The Clearing the Fog process, also known as a conflict resolution diagram, is designed to resolve an existing conflict. Followers CBT believe that compromises will not necessarily resolve the conflict; moreover, resolving the conflict in this way is undesirable. They believe that it is possible to find a solution in which both sides benefit.

It is necessary to clearly define the problem: describing it on paper makes it easier to visualize and understand. The “clearing the fog” method is a way to identify and visualize a problem so that the goal, necessary conditions, prerequisites and the conflict itself can be easily identified and reflected on paper. It is assumed that a clear definition of the problem helps to find the right solution. Figure 6.8 shows the most common form of conflict resolution diagram.

What do we mean by “dispersing the fog”? At first glance, “dispel the fog” means to overcome or eliminate a conflict, to make it disappear. This is true to some extent: we want to make the fog of conflict evaporate, but not quite in the way you think.

Typically, such a situation (Fig. 6.8) immediately suggests a compromise option (in our case there should be some kind of average inventory level and an assortment of products manufactured both to order and to stock). However, compromise is not what we need. Even if it is possible, it is not always the best solution.

The “clearing the fog” technique encourages reframing of an issue or disagreement. The problem is identified, described - why rethink it? Perhaps the problem identified is not true. There may be a need to reconsider the situation and question our assumptions.

This is where the difficulty lies. It seems to us that the problem is clearly defined and the conflict has been identified, but the basis is based on assumptions that we have not yet identified. In the example, we determined that the problem was related to the time it took to ship products and the need to reduce it. The first question that will arise is “why?” Why is it necessary to reduce the time for shipping products? Possible answers: The customer needs faster cycle times or competitors can provide them. This may be true, but let's look at some as-yet-unspecified assumptions.

It is possible that the time interval between the receipt of an order from the consumer / its placement and the receipt of the ordered products is too long. It is also assumed, based on the identified problem, that in order to reduce cycle time it is necessary to either store the stock in the warehouse or wait until the consumer orders the product. If we store inventory, then we only need to select and ship the products. If we wait until the consumer places an order, we can produce only what is ordered and not waste time on producing other types of products. To be able to supply products from the warehouse, it is necessary to increase the volume of inventory, and vice versa, if we work to order, we reduce the volume. Of course, it is impossible to increase and decrease the amount of inventory at the same time, so there are signs of an internal conflict between the two statements.

But let's look at our assumptions. Let's start with the first and most significant: production cycle times should be reduced to meet customer demands. Maybe this is true, maybe not. Most likely, the problem is not in the duration of the cycle, but in something else. Perhaps the cycle time fluctuates too much, and the consumer needs more stability. It is likely that it is simply not possible to ensure the order is completed within the promised time frame. It may be that the indicated time is completely inconsistent with the actual time required to produce, package and ship the product. We may be trying to solve the wrong problem!

Clearing the fog isn't just about identifying the problem and putting it on paper, it involves uncovering all those default assumptions, analyzing them, and finding the true source of the problem. If we destroy at least one of the foundations of our problem expressed in the diagram, then it will be solved and the conflict will disappear. The problem that needs to be worked on will remain, but this time it will most likely be the real cause of the conflict: a systemic problem, not a local one. Now we will look at the problem systematically, as we re-evaluate it and analyze the underlying assumptions, and ask questions without losing sight of the overall goal.

The goal is to generate profits by increasing efficient productivity. Considering the initially identified problem from the point of view of achieving the goal, we concentrated our efforts on improving the entire system and increasing effective productivity rather than simply “fixing” some part of the system, in our case, the time of shipment of goods to the consumer. This is the strength and advantage of the “fog dispersal” method. It will take practice, but you should try and evaluate this method.

6.5.2. Current Reality Tree

Another method CBT is a current reality tree, which is a type of logical diagram that reflects the current state - how work is going at the moment. The purpose of the current reality tree is to identify the root cause of any factor that prevents the achievement of a goal. Just like a conflict resolution diagram, the current reality tree helps resolve conflict situations by clearly identifying and documenting the current state of the production process. At the very least, the idea of ​​it is identified and documented. One way or another, it is best to start with the actions mentioned. The current reality tree resembles a process map, but it is a logical map. You must have a clear idea of ​​where you are before you decide where to go.

When constructing a current reality tree, one usually begins by observing undesirable effects ( undesirable effects,UDE). Next, causes and effects are compared in reverse order until the root cause of all those UDE, with which we started. Let's go back to the example and start with UDE, which lies in the fact that consumers are not satisfied with the delivery time. Figure 6.9 shows a simple current reality tree based on this undesirable effect. In this example, we start by stating an undesirable effect: “Consumers are not satisfied with the delivery time.” The delay occurs for two main reasons: firstly, the shipping time is too long, and secondly, consumers change their orders at the last minute. In fact, these are undesirable effects, so we need to look for the reasons that gave rise to them, and we will do this until we identify one or more root causes. In this case, we traced the chain to the end and found that the time to start, stop and changeover was too long, there was no system of penalties for changing orders at the last minute, and the sales department was rewarded only for sales volume. This provides an excellent opportunity to find solutions to eliminate the identified causes.

6.5.3. Future Reality Tree

Similar to the current reality tree, the future reality tree is used to develop and analyze predicted states of the system in the future, as well as the cause-and-effect relationships that will lead to them. The starting point is the initial design of the future reality tree. The original arguments and thoughts are presented on paper in a logical format, which allows the data to be reviewed and discussed. Arguments expressed in terms of cause and effect must be carefully justified and analyzed.

Again, this is the starting point. As the situation is analyzed, and especially when the time comes to make changes, it may be necessary to modify the plan. This is normal, you should not expect the original project to remain unchanged. As you work, you will improve the plan. Figure 6.10 shows an example of a future reality tree.

Possible negative consequences can be included in the future reality tree, or UDE(Fig. 6.11). When developing a new process or product, you should try to anticipate potential problems or possible negative impacts. This will not only bring more reality to the calculations, but will also help develop solutions, mitigation tactics, or elimination of problems if they arise.

These logical diagrams - "clearing the fog", the current reality tree and the future reality tree - are based on cause-and-effect relationships. Working with them will take some practice, but they are very useful for analyzing and overcoming problems and finding solutions. Process and value maps are also very informative and can be used in conjunction with logic diagrams. So use all the elements of the accumulated tools, if they are applicable to your tasks and will lead to the desired result.

Note

A method of teaching by asking questions rather than lecturing. The learner finds answers to questions himself, instead of receiving ready-made ones. When applied to root cause analysis, this means that the cause is identified by answering a series of questions.

"Ben Hur" ( Ben Hur) is a 1959 US classic film set in biblical times. The main character - Ben Hur - was exiled to the galleys. — Note translator

Lisin N.G., Odinokov S.I.

Everyone knows that in a standard solution 1C:ERP A revolutionary production planning technique has been implemented. But how does it compare with classical methods? MRP, APS, TOS (BBV)?

Is it true that 1C:ERP uses TOC theory of constraints methods (“ Drum-buffer-rope")?

Let's try to answer this question without overloading the reader with tons of calculations, formulas and other theoretical research, as is customary in textbooks.

We will consider only inter-shop planning (the so-called “global dispatcher” level); In-shop planning and management of launch-release batches (route sheets) are not covered in this article.

Before we begin discussing this issue, let us briefly recall the essence, advantages and possible area of ​​​​use of methods for calculating end-to-end intershop production schedules MRP/CRP, APS, BBB (TOS, DBR).

MRP/CRP/RCCP (Material Requirements Planning, Capacity Requirements Planning, Rough-Cut Capacity Planning)

The schedule of inter-shop transfers of products is calculated from the planned release date of the product according to the order back in time (right -> left). In this case, the program is based on the structure of the product tree (the final product tree is expanded back in time by simple expansion) and the total time for performing all operations on semi-finished products (components) in the workshops.

For each time interval (day, shift), the program records what production capacity is needed to fulfill each order (this is the CRP technique). The need is fixed “after the fact”, regardless of availability during the planning process - in other words, whether there is available equipment operating time in a shift (day, week), taking into account repairs and occupancy on other orders.

It can be done so that the operating time requirements of only those capacities that are recognized by logisticians as potential bottlenecks will be recorded. This will avoid overloading the system with information (technique RCCP).

Also in the system CRP/RCCP contains information about the available operating time fund production capacity in each interval, namely:

• working hours types of work centers (WRC, groups of similar equipment) taking into account stops for repairs,
• and opening hours labor resources(workers) by shop, taking into account vacations and sick leave.

After all orders are planned according to interdepartmental movements, the logistician looks at the report - a comparison of the demand for capacity operating time required by the plan (interval) and the available capacity operating time fund.

Shortages of operating time of facilities and labor resources are identified at intervals:

Power shortage per interval = Total demand for power operating time for all orders for the interval – Available capacity operating time fund for the interval

• Positive value – deficit
• Negative value – surplus(excess power).

If there is a shortage in at least one interval, then it is conditionally considered that the entire set of orders is unfulfillable. In this case, appropriate manipulations are made with the release dates of orders (shifting into the future to unload production) and their further rescheduling in order to balance the load and eliminate shortages.

Thus, the MRP/CRP/RCCP methodology allows you to see capacity shortages “after the fact” after the planning procedure, but does not suggest distributing orders along the time axis in order to eliminate these shortages. This sorting of orders by date is done manually by logisticians based on their experience and order priorities. Next, all orders are rescheduled and again checked for shortages.

There may be several such iterations; they are carried out until the production schedule becomes at least approximately balanced in capacity (i.e., all shortages are eliminated).

The task of calculating the possible date of completion of a new order is solved extremely approximately - the schedule and required capacity of the new order are superimposed on the already calculated interval capacity load for existing orders. Then logisticians check what new capacity utilization has occurred, and whether it has gone beyond the available capacity fund:

• If No, the date of the order is considered executable,
• If Yes, the logistician selects a release date for the new order so that the total production schedule is feasible; if the order is important, then another order can be manually moved forward in time, thereby making room for a new order.

This scheme does not cause any special problems if, based on accepted customer orders, production capacity is no more than 70% . In other words, “the main thing is to sell, but we can always produce.” Planning inaccuracies are smoothed out by the remaining 30% available operating time of capacities.

The tasks of optimizing loading, minimizing work in progress and changeovers are solved by local shop dispatchers “on the spot” according to their instincts and experience - for this they have room for maneuver, since the production schedule is “leaky” and it does not load 100% of the capacity in the planning horizon.

This is a normal situation in enterprises where the limitation on sales volume for any period is the market, and not production, which entails a constant underutilization of production.

It’s another matter if the limitation on sales for the period is production, or production capacity approximately corresponds to the average volume of customer orders for the period. It must be said right away that this situation may indicate an imbalance between the enterprise and the market, as well as the presence of serious problems with accurate production planning with the most dense loading possible, which allows fulfilling as many orders as possible per period.

If demand is seasonal, planning may not be optimal: during the low demand season, production is underutilized, and during the high demand season, there is a rush.

Since in such situations planning is carried out with the maximum possible production load, such planning is risky, since there is always a possibility of not completing the order on time due to, for example, equipment breakdown or defects. It is difficult to optimize production, enlarge batches and minimize changeovers; nervousness and emergency production are possible. The interests of production workers (to optimize production and work rhythmically) begin to contradict the interests of businessmen (to sell as much as possible and quickly fulfill urgent orders, including for new types of products).

For completeness, we note that upon closer examination of the issue, the CRP methodology falls into two subsections:

• RCCP (Rough-Cut Capacity Planning). Preliminary planning of production capacity. A procedure for quickly checking shortfalls in several key capacities (potential bottlenecks). The point of highlighting this procedure is only in its high speed, since not all powers are checked, but a very limited list of them.

• FCRP (Finite Capacity Resource Planning). Final planning of production capacity. Procedure for checking shortages of all production capacities.

APS (Advanced Planning and Scheduling)

In a situation where production is a potential constraint on product sales, the (rather relative) solution is the APS method.

The main difference between APS and MRP/CRP is the following: when calculating the schedule of inter-shop transfers of semi-finished products, the program goes down to technological operations and plans operations for specific pieces of equipment, capturing their operating time. Advanced APS systems also capture staff time and other production constraints (tooling time, etc.).

The very first and priority order captures the capacity operating time from the available capacity operating time pool. The next order takes over what is left of the first and so on until all orders are planned.

When a new order arrives, it can be placed at the end of the queue - it will capture the capacity on the time axis that remains from all existing orders. Or you can “squeeze” it into the middle of the queue - it will again capture the capacity on the time axis that remains from all the existing orders standing in the queue in front of it, but will not take into account the capacity of the orders standing in the queue after it. In this case, of course, rescheduling of all orders queued later is required.

To capture the operating time of the capacity, the program analyzes the time axis and looks for the free operating time of the capacity remaining after scheduled repairs and other, higher-priority orders. At the same time, the program tries to comply with the criteria for optimizing production - it minimizes changeover time, the size of work in progress, maximizes batches of transferred products, reduces production costs, etc.

We can say that the APS system builds an end-to-end (across all workshops) operational schedule of equipment to fulfill an order at the global dispatcher level, removing this task from workshop dispatchers.

Planning can be done:

• From right to left(operations are assigned to the time axis as late as possible, where there is free capacity time). Disadvantages: disruption of the department's operations schedule inevitably leads to a delay in the order completion date. As a result, there is a need for rescheduling and, as a consequence, a shift in release dates for orders, or overtime/emergency work. Nervous schedule, oversaturation with deadlines, high “tension” of production batches.
• From left to right(operations are assigned to the time axis as early as possible, where there is free capacity time, but not earlier than the production start date noted in the order). Disadvantages: the need for materials occurs earlier than is actually needed to complete the order. In general, this is a more optimal mode, especially when production is underutilized and the product has an unlimited shelf life. It’s better to start fulfilling your order in advance to ensure it’s on time.

As the diagram shows, when planning “as early as possible,” there is a margin of time to complete the order equal to the difference between the release date desired by the customer and the release date calculated by the enterprise.

If you need to count minimum date order execution, then this problem is most effectively solved in the “left-to-right” mode. The order is inserted into the order queue (capacity capture queue) and captures the capacity that remains from the orders in the queue in front of it. Since production steps are distributed across available time slots from left to right, the program determines:

• estimated date for the order to go into production(start date of the very first stage in the product structure) – the date on which there is free capacity to perform the very first operation;
• estimated release date for the order– the date that resulted from the sequential seizure of capacity by order operations from left to right, starting with the first operation.

Simply put, when a new order arrives, the program tries to place it on the time axis as far to the left as possible - where there is free space for the equipment to work (taking into account already planned higher priority orders) for the very first operation of the order. There will be a place in any case - this will be the launch date of the order. Then a time point (free capacity) is sought for the next operation, and so on. Eventually, the program “goes out” to the last operation and also schedules it for the available equipment time - this will be the release date for the order.

It would seem, what more could you want? This system seems ideal. The schedule loads production at maximum capacity, production operates rhythmically according to the schedule (without rush jobs or downtime), sales for the period are achieved at the maximum possible volume, customers are satisfied - as a result of accurate planning, orders are completed on time, possible order completion times are immediately determined.

However, not all so simple. In theory - beautiful. But in practice there may be problems:

• As a result of the distribution of order operations over the operating time of the equipment, the following picture can be observed (for example): the first order with the release on the 10th of the item X 10 pcs. was distributed over three days with the launch on the 7th, and the second order with the release on the 20th of the same nomenclature and quantity should be launched tomorrow - it was spread out over twenty days. To a shop manager, such a schedule may seem strange. Why launch on the 2nd if it is due on the 20th, and the production cycle lasts three days? Such a schedule may result from optimization of changeovers, as well as for other reasons not entirely clear to the dispatcher.
  • There is an uneven, complexly intersecting distribution of order operations of different priorities over time, which is not always obvious to dispatchers, which means there is a danger of dispatchers moving away from this schedule. Many will probably demand that the global dispatcher simply give a schedule for the delivery of products according to orders, “and what operations to launch when - we will figure this out ourselves.” Still, at the level of a global dispatcher (inter-shop schedule) it is difficult to take into account all the intra-shop nuances.
• Failure to complete any planned operation on time, defects, delays in the delivery of material, employee illness, and the like leads to the cascading impossibility of all subsequent operations planned as tightly as possible in time (precisely tightly, otherwise why APS?). In such situations, it is necessary to immediately reschedule the schedule, since it has become irrelevant - the entire schedule, for all workshops and orders.
  • Rescheduling can be performed at different intervals, for example, at the end of each shift or day. As a result, the schedule may be rearranged beyond recognition. And restructuring the schedule is not only a change in the requirements for immediate changeovers and the need for equipment (which “hits” workshops and auxiliary production), but also a change in the estimated release dates for orders (which “hits” customers with whom they have to negotiate for more late dates). All this creates nervousness and high tension both in the production itself and in the sales department.
• APS requires accurate regulatory data, including multiple production parameters. Technologists may not have data on these parameters - often they are not formalized and are in the heads of shop foremen (local dispatchers). If the nuances are not taken into account, the schedule will be unfulfilled. Digitization and structuring of such regulatory data (operational route maps) with all the parameters necessary for calculating production schedules, as well as maintaining the relevance of this information for an average machine-building, instrument-making enterprise is a task of incredible organizational complexity!
• APS is an absolutely determinative system that formalizes all the work of the workshop “from above” with maximum detail (down to operations) from the level of the global dispatcher (GDS). Local dispatchers execute the schedule of operations issued from above. It is the schedule of operations, not the schedule of delivery of products. This operation schedule does not take into account production parameters that are unknown to the scheduler, but which directly affect the calculation executable schedule. Examples (of course, this is only a small part):
• 
  • Turner Ivanov is not in the mood today and he does not need to be trusted with a critical part, and turner Kozlov should not be allowed near the old machine - he has an increased taper and he will screw up the workpiece.
  • On one of our projects, the APS system, as it turned out, is not able to connect machines into a production line as one flow control center (this is a technology requirement), removing these machines from the available capacity pool. It is also impossible to describe this set of DCs as one DC - for other products they are planned separately...
  • Problem with mating parts: you cannot drill the cover until the body is drilled, although the cover and body are in different branches of the product tree and are connected only at assembly.
  • Difficulties arise with transfers through cooperation to the outside or to other workshops when there is a lack of capacity.
  • The furnace can operate not only in synchronous, but also in asynchronous mode. It is brought to a given temperature, and then the workpieces are inserted and removed not synchronously (in one loading batch), but at different times, according to the duration of the heat treatment of each workpiece.
  • An experienced local dispatcher resolves such situations without problems, whereas the program is not capable of this. This requires artificial intelligence. That's why systems that give the dispatcher a tentative schedule for delivery of products and leave room for creativity when planning operations within the workshop are more stable and less stressful. The APS system largely deprives the workshop dispatcher of the ability to maneuver and be independent in taking into account nuances.
• APS systems are based on highly complex mathematics - in particular, genetic algorithms. The simplest APS systems use heuristic greedy algorithms. In any case, it is impossible to reproduce (calculate) the planning results manually, just as it is impossible to explain to an experienced logistician why the program planned it this way, although there is another, more optimal plan. Indeed, there are no guarantees that the program will find the most optimal one among thousands of plan options.
• And finally, let’s calculate how many scheduled operations the APS system should plan for a month in advance.
  • For example, 1000 orders for finished products per month, for each - 1000 operations across all workshops. We get a million operations that need to be calculated, optimized and recorded in the database, most likely every day, which means that the planning procedure in a three-shift operating mode takes half an hour to an hour.

So, the main disadvantages of APS systems are:

• Inability to take into account all production parameters to accurately calculate the schedule. If for MRP an inaccurate schedule is normal, then for APS it is disastrous, since it implies the impracticability of the schedule and its constant rescheduling. And this is nervousness and irregular production.
• Organizational complexity in creating and digitizing a regulatory system (specifications, route maps). Bringing what is in the enterprise to the format required by APS, continuously maintaining the relevance of this data.
• High demands on speed and data storage volumes.

If these shortcomings do not manifest themselves in a particular production, then the APS system is an absolute recommendation for use.

There has been a lot of talk lately about how difficult it is to develop a universal APS system for all industries. Highly specialized APS systems, “tailored” for specific industries and taking into account all the features of specific industries, work most successfully.

MES (M anufacturing Execution System)

To complete the picture, let us also mention MES systems. Drawing a clear line between an APS and an MES system is not always easy. A lot of research has been devoted to this topic.

For example, an APS system can be conditionally considered an MES system if the entire enterprise consists of one workshop, and re-planning of the workshop is possible based on the results of each operation in order to obtain an accurate modified operation plan after each operation.
.

The characteristic features of MES systems can be considered:

• Planning operations at the local dispatcher level only within the workshop. The workshop's delivery schedule is used as the initial data.
• Rescheduling the schedule automatically (for example, every 15 minutes) based on the results of the operations of the previous version of the schedule. In any case, rescheduling is performed with a frequency equal to the average duration of operations. As a result, the dispatcher (and workers at work centers) see a continuously updated schedule of operations for work centers, taking into account what the DCs are currently doing.
• Accurate calculation of equipment operating schedules over a short-term horizon (several shifts), taking into account all production parameters. That is, a realistically executable schedule is obtained that does not require adjustment by the dispatcher due to unaccounted for nuances. With a large number of operations, the dispatcher simply will not be able to view and adjust all planned operations every 15 minutes.
• Direct communication with equipment – ​​transmission of signals from equipment to the MES system about the current operating modes of the equipment, the actual start and completion of operations. This is important, since the requirements for the efficiency and accuracy of entering actual data are very high.

MES systems are most effective when they are highly specialized (this allows specific production parameters to be taken into account in the system), built into specific production equipment and supplied with it.

CBT, BBV/DBR (Theory of Constraints of Systems, “Drum-Buffer-Rope”, “Drum, Buffer, Rope”)

This technique is truly revolutionary and was not immediately recognized by luminaries. Created by world famous researcher, founder of Theory of Constraints, Eliyahu Goldratt.

This ingenious technique challenges traditional methods and is designed not only to eliminate the shortcomings of APS and MRP, but also to combine their advantages.

What is the “drum-buffer-rope” technique?

The BBB is based on the following obvious premises:

1. Production is most often not completely balanced. The production capacity for each type of product is limited by only one type of production resource (capacity). For example, some unique expensive machine. The exception is in-line and continuous production, in which each flow center is completely balanced with other flow centers. But this is not a case of TOC, or even a case where detailed production planning is required.
2. There is no point in planning every production area in detail. It is enough to accurately plan a site with a narrow production resource - “ drum" This will be the main production cycle. The drum operating schedule is strictly observed. It must be loaded continuously with a minimum of changeovers. This means that production is at maximum capacity.
   • Obviously, stopping the drum means stopping the activity of the entire enterprise. Calculating the order completion date is very simple: to do this, you need to assign order processing to one DC - the drum - taking into account its operating time. An order processing schedule for one work center can be created in Excel.
3. All other sections will automatically adjust to the main beat of the drum, since their throughput is higher than required to ensure the beat of the drum. Therefore, there is no need for a site work schedule. It is enough to launch the source materials into the initial sections some time before entering the drum and require the sections to immediately process and send the products further to the corresponding recipient sections that perform the following operations.
   • The principle of launching materials into production before the products are released onto the drum is “ rope" The rope “pulls” materials from the warehouse in accordance with the beat of the drum, and only in the amount needed for the drum. In no case should you supply more material than the drum requires - otherwise, the sites will begin to increase batches in order to optimize production, and their throughput will become less than that of the drum. In other words, the drum will no longer be a bottleneck.
4. The schedule should be such that there is always a non-empty queue of products in front of the drum. This will ensure that it loads continuously. In order for the queue to be non-empty, the source materials must be put into production much earlier than the processing time to the drum requires. For example, the time of such advance in the launch of materials can be 3 times longer than the processing time to the drum. This advance time is called temporary " buffer».
5. There is no point in monitoring the timely delivery of all products by workshops. It is enough to control which products left the “green zone” - that is, did not arrive in line at the drum in a timely manner according to the production cycle. Such products/orders require dispatcher control and intervention.
   • The traffic light principle is used. If the order is in the “green zone”, we do not pay attention to it. If the order is in the “yellow zone” - that is, 1/3 of the buffer has already passed, but no more than 2/3 of the buffer, and the order has not reached the drum - we begin to figure out why the delay occurred. If the order is in the “red zone” - that is, more than 2/3 of the buffer has passed, but the order has not reached the drum - we urgently intervene, otherwise the drum’s operating schedule will be disrupted. Of course, due to other orders in the queue, the drum most likely will not stop, which indicates the great stability of the system.

Between the drum and the output of finished products there may be outputs of intermediate semi-finished products - in this case, the “final buffer” must be taken into account when planning. In other words, some fixed time passes from processing on the drum to the release of the finished product, which is taken into account (added) during planning. For example, if the product for an order must be released on the 10th, and the final buffer is 3 days, then the drum operation to process the order is scheduled for the 7th.

Unfortunately, BBV is also not an absolutely universal technique.

BBB works great if the production has a clearly defined narrow work center for each type of product, which does not migrate when the range of products produced changes. If the bottleneck is difficult to “catch” or it migrates, then there will be problems with the BBB.

So, we looked at 3 main planning methods. Each of them has its pros and cons. Each has its own limitations. Is it possible to find a universal method, a kind of “golden mean”, which has the advantages of all other methods, but is devoid of their disadvantages?

Is this problem solvable? Isn't it akin to the attempts of medieval alchemists to turn lead into gold or invent a perpetual motion machine?

Searching for the “philosopher’s stone” in 1C:ERP...

Production planning algorithm 1C:ERP

We will not describe all the nuances. We will describe only the main points that make up the essence of the algorithm for intershop production planning in 1C:ERP.

For each production unit, the time axis is divided into equal intervals. For example, days or weeks are the most popular options. Moreover, for each division the interval is configured individually.

The production order specifies Desired launch and release date:

• Earlier desired launch date(props “start date no earlier than”) the program is prohibited from scheduling execution of the schedule according to the order.
• Product release must be scheduled no later than desired release date. Essentially, this is the date desired by the client.

Each division describes the types of work centers (WRC) available in the division, as well as the available total planned operating time of the WRC, taking into account repairs.

The time management center consists of individual time centers, but when planning, the total time fund of the time management center is taken into account.

The specification for the production stage indicates:

• in which department the stage is being performed,
• the working hours of which WRCs of this unit need to be captured when fulfilling the stage specification.

The stage specification should only indicate the potential bottlenecks of the unit. In this case, the schedule of inter-shop transfers by order will be built according to the capture of the operating time of these VRCs, without taking into account those VRCs that are not bottlenecks.

The left-to-right or right-to-left planning methodology is determined in a separate production order. Based on this parameter, it is already possible to classify 1C: ERP as an APS class system, because The MRP algorithm involves calculating the production schedule only from right to left

The program performs sequential order planning according to the order queue. The order queue is determined by the priority of the order; within orders with one priority, the queue is determined in accordance with the date the document was entered. The order queue is calculated within one department - the dispatcher.

In accordance with the Release Placement parameter, the system searches for a planning interval to place production stages to the left of the demand date back in time or to the right of the Start no earlier than date forward in time, which will be the reference point.

Scheduling is then carried out to the right or left according to the release placement until the order is fully placed in production. In this case, the stages capture the operating time of the VRC specified in its specification, and makes this captured time unavailable for all subsequent lower-priority orders.

5. DRUM-BUFFER-ROPE (DBR) METHOD

The “Drum-Buffer-Rope” method (DBR-Drum-Buffer-Rope) is one of the original versions of the “push-out” logistics system developed in the TOC (Theory of Constraints). It is very similar to the limited FIFO queue system, except that it does not limit the inventory in individual FIFO queues.

Rice. 9.

Instead, an overall limit is set on the inventory located between the single production scheduling point and the resource that limits the productivity of the entire system, the ROP (in the example shown in Figure 9, the ROP is area 3). Each time the ROP completes one unit of work, the planning point can release another unit of work into production. This is called a “rope” in this logistics scheme. “Rope” is a mechanism for controlling the restriction against overload of the ROP. Essentially, it is a materials issue schedule that prevents work from entering the system at a rate faster than it can be processed in the ROP. The rope concept is used to prevent work in process from occurring at most points in the system (except critical points protected by planning buffers).

Since EPR dictates the rhythm of the entire production system, its work schedule is called “Drum”. In the DBR method, special attention is paid to the resource that limits productivity, since it is this resource that determines the maximum possible output of the entire production system as a whole, since the system cannot produce more than its lowest capacity resource. The inventory limit and the time resource of the equipment (the time of its effective use) are distributed so that the ROP can always start new work on time. This method is called “Buffer” in this method. The “buffer” and “rope” create conditions that prevent the ROP from being underloaded or overloaded.

Note that in the “pull” logistics system DBR, the buffers created before the ROP have temporal rather than material in nature.

A time buffer is a reserve of time provided to protect the scheduled “start of processing” time, taking into account the variability in the arrival at the ROP of a particular job. For example, if the EPR schedule requires that a particular job in Area 3 begin on Tuesday, then material for that job must be issued early enough so that all pre-EPR processing steps (Areas 1 and 2) are completed on Monday (i.e., in one full working day before the required deadline). Buffer time serves to “protect” the most valuable resource from downtime, since the loss of time of this resource is equivalent to a permanent loss in the final result of the entire system. The receipt of materials and production tasks can be carried out on the basis of filling the “Supermarket” cells. The transfer of parts to subsequent stages of processing after they have passed through the ROP is no longer a limited FIFO, because the productivity of the corresponding processes is obviously higher.

Rice. 10. An example of organizing buffers in the DBR method
depending on the position of the ROP

It should be noted that only critical points in the production chain are protected by buffers (see Figure 10). These critical points are:

• the resource itself with limited productivity (section 3),
• any subsequent process step where the part processed by the limiting resource is assembled with other parts;
• shipment of finished products containing parts processed with a limiting resource.

Because the DBR method focuses on the most critical points of the production chain and eliminates it elsewhere, production cycle times can be reduced, sometimes by 50 percent or more, without compromising reliability in meeting customer shipment deadlines.

Rice. eleven. Example of supervisory control
passing orders through the ROP using the DBR method

The DBR algorithm is a generalization of the well-known OPT method, which many experts call the electronic embodiment of the Japanese “Kanban” method, although in fact, between the logistics schemes for replenishing the “Supermarket” cells and the “Drum-Buffer-Rope” method, as we have already seen, there is a significant difference.

The disadvantage of the “Drum-Buffer-Rope” (DBR) method is the requirement for the existence of a ROP localized at a given planning horizon (at the interval of calculating the schedule for the work being performed), which is only possible in the conditions of serial and large-scale production. However, for small-scale and individual production, it is generally not possible to localize EPR over a sufficiently long period of time, which significantly limits the applicability of the considered logistics scheme for this case.

6. LIMIT OF WORK IN PRODUCTION (WIP)

A pull logistics system with a work in process (WIP) limit is similar to the DBR method. The difference is that temporary buffers are not created here, but a certain fixed limit of material inventories is set, which is distributed to all processes of the system, and does not end only at the ROP. The diagram is shown in Figure 12.

Rice. 12.

This approach to building a “pull” management system is much simpler than the logistics schemes discussed above, is easier to implement, and in a number of cases is more effective. As in the “pull” logistics systems discussed above, there is a single planning point here - this is section 1 in Figure 12.

A logistics system with a WIP limit has some advantages compared to the DBR method and the FIFO limited queue system:

• malfunctions, fluctuations in the rhythm of production and other problems of processes with a margin of productivity will not lead to a shutdown of production due to lack of work for the EPR, and will not reduce the overall throughput of the system;
• only one process must obey scheduling rules;
• there is no need to fix (localize) the position of the ROP;
• It is easy to locate the current EPR site. In addition, such a system gives fewer “false signals” compared to limited FIFO queues.

The considered system works well for rhythmic production with a stable range of products, streamlined and unchangeable technological processes, which corresponds to mass, large-scale and serial production. In single-piece and small-scale production, where new orders with original manufacturing technology are constantly being put into production, where product release times are dictated by the consumer and can, generally speaking, change directly during the manufacturing process of products, then many organizational problems arise at the level of production management. Relying only on the FIFO rule in the transfer of semi-finished products from site to site, the logistics system with a work in progress limit in such cases loses its effectiveness.

An important feature of the “push” logistics systems 1-4 discussed above is the ability to calculate the production time (processing cycle) of products using the well-known Little formula:

Release time = WIP/Rhythm,

where WIP is the volume of work in progress, Rhythm is the number of products produced per unit of time.

However, for small-scale and individual production, the concept of production rhythm becomes very vague, since this type of production cannot be called rhythmic. Moreover, statistics show that, on average, the entire machine system in such industries remains half underutilized, which occurs due to constant overloads of one equipment and simultaneous downtime of another in anticipation of work related to products lying in line at previous stages of processing. Moreover, downtime and overloading of machines constantly migrate from site to site, which does not allow them to be localized and to apply any of the above logistics pull schemes. Another feature of small-scale and individual production is the need to fulfill orders in the form of a whole set of parts and assembly units by a fixed deadline. This greatly complicates the task of production management, because The parts included in this set (order) can be technologically subjected to different processing processes, and each of the areas can represent an ROP for some orders without causing problems when processing other orders. Thus, in the industries under consideration, the effect of the so-called “virtual bottleneck” arises: the entire machine system on average remains underloaded, and its throughput is low. For such cases, the most effective “pull” logistics system is the Calculated Priority Method.

7. COMPUTABLE PRIORITIES METHOD

The method of calculated priorities is a kind of generalization of the two “push” logistics systems discussed above: the “Supermarket” replenishment system and the FIFO system with limited queues. The difference is that in this system, not all empty cells in the “Supermarket” are replenished without fail, and production tasks, once in a limited queue, are moved from site to site not according to the FIFO rules (i.e. mandatory discipline is not observed “ in the order received"), and according to other calculated priorities. The rules for calculating these priorities are assigned at a single production planning point - in the example shown in Figure 13, this is the second production site, immediately following the first “Supermarket”. Each subsequent production site has its own executive production system (MES - Manufacturing Execution System), the task of which is to ensure timely processing of incoming tasks taking into account their current priority, optimize internal material flow and timely show emerging problems associated with this process ,. A significant deviation in the processing of a particular job in one of the sites can affect the calculated value of its priority.

Rice. 13.

The “pull” procedure is carried out due to the fact that each subsequent section can begin to perform only those tasks that have the highest possible priority, which is expressed in the priority filling at the “Supermarket” level not of all available cells, but only those that correspond to priority tasks. Subsequent section 2, although it is the only planning point that determines the work of all other production units, is itself forced to carry out only these highest priority tasks. Numerical values ​​of task priorities are obtained by calculating the values ​​of the criterion common to all in each section. The type of this criterion is set by the main planning link (section 2), and each production section independently calculates its values ​​for its tasks, either queued for processing, or located in the filled cells of the “Supermarket” at the previous stage.

For the first time, this method of replenishing “Supermarket” cells began to be used at Japanese enterprises of the Toyota company and was called “Production Leveling Procedures” or “Heijunka”. Nowadays, the process of filling the “Heijunka Box” is one of the key elements of the “pull” planning system used in the TPS (Toyota Production System), when the priorities of incoming tasks are assigned or calculated outside the production areas executing them against the backdrop of the existing “pull” replenishment system of the “Supermarket”. (Kanban). An example of assigning one of the directive priorities to an executing order (emergency, urgent, planned, moving, etc.) is shown in Figure 14.

Rice. 14. Example of assigning a directive
priority to fulfilled orders

Another option for transferring tasks from one site to another in this “pull” logistics system is the so-called “calculated rule” of priorities.

Rice. 15. Sequence of executed orders
in the calculated priority method

The queue of production tasks transferred from section 2 to section 3 (Figure 13) is limited (limited), but unlike the case shown in Figure 4, the tasks themselves can change places in this queue, i.e. change the sequence of their arrival depending on their current (calculated) priority. In fact, this means that the performer himself cannot choose which task to start working on, but if the priority of tasks changes, he may have to, having not completed the current task (turning it into the current WIP), switch to completing the highest priority one. Of course, in such a situation, with a significant number of tasks and a large number of machines on the production site, it is necessary to use MES, i.e. carry out local optimization of material flows passing through the site (optimize the execution of tasks already being processed). As a result, for the equipment of each site that is not the only planning point, a local operational production schedule is drawn up, which is subject to correction every time the priority of the tasks being executed changes. To solve internal optimization problems, we use our own criteria, called “Equipment Loading Criteria”. Jobs awaiting processing between sites not connected by the “Supermarket” are ordered according to “Queue Selection Rules” (Figure 15), which, in turn, can also change over time.

If the Rules for calculating priorities for tasks are assigned “externally” in relation to each production site (Process), then the Site Equipment Loading Criteria determine the nature of the internal material flows. These criteria are associated with the use of optimization MES procedures on the site, intended exclusively for “internal” use. They are selected directly by the site manager in real time, Figure 15.

Rules for selection from the queue are assigned based on the priority values ​​of the tasks being executed, as well as taking into account the actual speed of their execution at a specific production site (section 3, Figure 15).

The site manager can, taking into account the current state of production, independently change the priorities of individual technological operations and, using the MES system, adjust the internal production schedule. An example of a dialog for changing the current priority of an operation is shown in Fig. 16.

Rice. 16.

To calculate the priority value of a specific job being performed or awaiting processing at a specific site, a preliminary grouping of jobs (parts included in a specific order) is carried out according to a number of criteria:

1. Number of the assembly drawing of the product (order);
2. Part designation according to the drawing;
3. Order number;
4. The complexity of processing the part on site equipment;
5. The duration of passage of parts of a given order through the machine system of the site (the difference between the start time of processing of the first part and the end of processing of the last part of this order).
6. The total complexity of operations performed on parts included in this order.
7. Equipment changeover time;
8. A sign that the processed parts are provided with technological equipment.
9. Percentage of part readiness (number of completed technological operations);
10. The number of parts from a given order that have already been processed at this site;
11. The total number of parts included in the order.

Based on the given characteristics and calculating a number of specific indicators such as tension (the ratio of indicator 6 to indicator 5), comparing the values ​​of 7 and 4, analyzing the ratios of indicators 9, 10 and 11, the local MES system calculates the current priority for all parts found in one group.

Note that parts from the same order, but located in different areas, may have different calculated priority values.

The logistics scheme of the Calculated Priority Method is used mainly in multi-item production of small-scale and single types. Featuring a "pull" scheduling system and using local MES to ensure high-speed orders flow through individual production areas, this logistics design uses decentralized computing resources to maintain process efficiency in the face of changing job priorities.

Rice. 17. Example of a detailed production schedule
for workplace in MES

A distinctive feature of this method is that the MES system allows you to draw up detailed schedules of work performed within the production area. Despite some complexity in implementation, the method of calculated priorities has significant advantages:

• current deviations that arise during production are compensated by local MES based on the changing priorities of the tasks being performed, which significantly increases the throughput of the entire system as a whole.
• there is no need to fix (localize) the position of the ROP and limit the work in progress;
• it is possible to quickly monitor serious failures (for example, equipment breakdown) at each site and recalculate the optimal sequence of processing parts included in various orders.
• The presence of local production schedules in certain areas allows for operational functional and cost analysis of production.

In conclusion, we note that the types of “pull” logistics systems discussed in this article have common characteristic features, these are:

1. Preservation in the entire system as a whole of a limited volume of stable reserves (current reserves) with regulation of their volume at each stage of production, regardless of current factors.
2. An order processing plan drawn up for one site (a single planning point) determines (automatically “pulls out”) the work plans of other production departments of the enterprise.
3. Promotion of orders (production tasks) occurs both from the next section in the technological chain to the previous one using the material resources consumed in the production process (“Supermarket”), and from the previous section to the next one according to FIFO rules or calculated priorities.

LITERATURE

1. Jonson J., Wood D., Murphy P. Contemporary Logistics. Prentice Hall, 2001.
2. Gavrilov D.A. Production management based on the MRP II standard. - St. Petersburg: Peter, 2003. - 352 p.
3. Womack D, Jones D. Lean manufacturing. How to get rid of losses and achieve prosperity for your company. — M.: Alpina Business Books, 2008, 474 p.
4. Hallett D. (translation by Kazarin V.) Pull Scheduling Systems Overview. Pull Scheduling, New York, 2009. pp.1-25.
5. Goldratt E. Purpose. Goal-2. - M.: Balance Business Books, 2005, p. 776.
6. Dettmer, H.W. Breaking the Constraints to World-Class Performance. Milwaukee, WI: ASQ Quality Press, 1998.
7. Goldratt, E.. Critical Chain. Great Barrington, MA: The North River Press, 1997.
8. Frolov E.B., Zagidullin R.R. . // General Director, No. 4, 2008, p. 84-91.
9. Frolov E.B., Zagidullin R.R. . // General Director, No. 5, 2008, p. 88-91.
10. Zagidullin R., Frolov E. Control of manufacturing production by means of MES systems. // Russian Engineering Research, 2008, Vol. 28, No. 2, pp. 166-168. Allerton Press, Inc., 2008.
11. Frolov E.B., Zagidullin R.R. Operational scheduling and dispatching in MES systems. // Machine park, No. 11, 2008, p. 22-27.
12. Frolov E.B., . // General Director, No. 8, 2008, p. 76-79.
13. Mazurin A. FOBOS: Effective production management at the workshop level. // CAD and graphics, No. 3, March 2001, p. 73-78. — Computer Press.

Evgeniy Borisovich Frolov, Doctor of Technical Sciences, Professor, Moscow State Technological University "STANKIN", Department of Information Technologies and Computing Systems.

One of the most difficult tasks in production is planning the production process and providing operational management based on it. There are several different approaches. In this article, we will focus on the essence and advantages of the approach developed by the “Drum-Buffer-Rope” constraint theory.

The essence of the method is to simplify the problem as much as possible: planning production tasks for only one resource, which is a limitation, and ensuring synchronous operation of all other areas. It is clear that the output of the entire plant depends on the volume of output of this limiting resource, so there is no need to ensure optimal loading of all other centers and plan their work.

The term “drum” in the LBC refers to the production schedule of the internal resource of limited capacity (ROM), which determines the productivity of the enterprise as a whole. Thus, the limitation sets the pace or rhythm of the work of the entire company, protecting against overproduction and overload in the unrestricted. This allows for flexibility and a high degree of system responsiveness.

The “buffer” in BBK is a protective mechanism that allows you to make maximum use of the capacity of the limiting resource (eliminate possible downtime) and fulfill customer orders on time. However, these are not objects, but time. The buffer is designed to ensure that work in progress arrives a certain time before the scheduled start of processing. At the same time, a mechanism is provided to control the consumption of the buffer and the progress of the workpiece, part, assembly or product along the production chain.

“Rope” is a means of communication that allows you to ensure the synchronization of the release of materials and the speed of the restriction. This mechanism allows you to avoid excess materials in the production system, speed up production, reduce inventory and lead time. In fact, this is a plan for the release of materials from the warehouse, which is adjusted depending on the operating modes of the restriction.

This planning mechanism allows you to:

• Monitor and manage the execution of orders on time.
• Reduce production cycle time.
• Reduce the amount of work in progress in the system.

Another advantage of this method is its flexibility: BBK can be used both in order production and in warehouse production.

Unlike other systems, BBK aims to generate income rather than reduce inventory. At the same time, the use of this method allows you to see bottlenecks in production and take focused measures to solve problems that arise. Moreover, the effect of such measures will be immediate and tangible. So, applying the changeover method (SMED) from lean manufacturing to a limited capacity resource (SCR) will instantly increase the output of the entire enterprise. Thus, the approaches of the Theory of Constraints do not contradict, but complement existing techniques, significantly enhancing the effect of their application.

According to the theory of constraints proposed by E. Goldratt, in each production a relatively small list of work centers can be identified, which are bottlenecks, the productivity of which limits the productivity of the entire production as a whole. To achieve maximum production productivity, these bottlenecks must be expanded as much as possible and used as efficiently as possible.

Method "Drum-buffer-rope" Theories of limitation of TOS systems by E. Goldratt in: General description

Specific steps to optimize production while taking into account production bottlenecks are combined into a technique known as “Drum-Buffer-Rope” or DBR (Drum-Buffer-Rope). Basic steps for using the technique:

• work centers that are bottlenecks. The technique calls these bottlenecks drums;
• ensure the most efficient loading of drums. To do this, you should accurately plan their work, draw up a schedule for the operation of these drums, eliminating downtime;
• subordinate the work on other work centers to the work of the drum. Production time at work centers located in front of the drum during the production process, the technique is called buffer. Work in the buffers must begin in advance, a specified time before the scheduled start time of the drum. The duration of the buffer must be chosen in such a way that work in it must be completed before the operating time of the drum. Thus, the buffer must protect the drum from downtime.

To support the “drum-buffer-rope” (hereinafter referred to as BBV) methodology, the production management functionality offers the following operating procedure:

• All production is divided into stages. The selection of stages is not a consequence of the BBB technique, but it may be necessary for other purposes, for example, the selection of parts of production carried out in different territories;
• stands out at each stage key work center of this stage is his drum. The drum is given precise information about its performance. For all work performed before and after it, a generalized execution time is specified, during which they are guaranteed to be completed - buffer;
• Production schedule planning is carried out on the basis of information from production stages. Thus, for production planning, detailed information about the productivity of all work centers is not required: it is enough to know the productivity of key work centers and the operating time in buffers; During production, the status of work in buffers in front of key work centers is monitored.

Tips for using the Drum-Buffer-Rope technique

• One of the most effective approaches to finding bottlenecks is to look at which work centers have workpieces piling up waiting to be processed.
• It may be advisable to place quality control in front of the “drum”. In this case, the bottleneck will only process workpieces that are known to be of high quality, and its inefficient operation will be eliminated.
• It is necessary to constantly monitor production and control changes in the composition of its bottlenecks. New bottlenecks can be identified by optimizing the loading of previously identified bottlenecks.
• All possible measures must be taken to ensure that the “drum” does not stand idle and works efficiently.
• If possible, the productivity of the “drum” should be increased, because this increases the performance of the entire system.

Literature on the methodology of TOC Theory of system limitations.