Contents List of Illustrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix List of Abbreviations and Acronyms. . . . . . . . . . . . . . . . . . . . . . . . . . xiii Chapter 1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Chapter 2
The Unpaced Production Line . . . . . . . . . . . . . . . . . . . 13
Chapter 3
Unbalanced Lines Studied . . . . . . . . . . . . . . . . . . . . . . 31
Chapter 4
Considerations in Unbalancing Your Line . . . . . . . . . . 87
Notes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
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Illustrations Tables 3.1.
Improvements in the Best Configuration’s IT and ABL Compared to the Balanced Line . . . . . . . . . . . . . . . . . . . . . 46
3.2.
Percentage Change in Idle Time Over the “Balanced” Equal Buffer Distribution . . . . . . . . . . . . . . . . . 54
3.3.
Percentage Savings in the Best Configuration’s ABL Over the Balanced Equal Buffer Capacity Line . . . . . . . . . . 55
3.4.
Percentage Savings in the Best Configuration’s ABL Over the Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
3.5.
Percentage Change/Reduction in the Best Configuration’s IT Over the Control . . . . . . . . . . . . . . 78
Figures
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1.1.
Drum, buffer, and rope. . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.
An unpaced production line. . . . . . . . . . . . . . . . . . . . . . . . 14
2.2.
Example of a sequence of tasks in a production line. . . . . . 16
2.3.
Illustration of a production line in which task times are unbalanced. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.4.
A three-station assembly line, station 2 slowing down. . . . . 24
2.5.
A five-station assembly line, station 2 slowing down. . . . . . 24
2.6.
Illustration of uneven allocation of buffer space in an unbalanced line. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
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x
ILLUSTRATIONS
3.1.
One possible configuration of mean operation time imbalance—slight and high increases for 10- and 5-station lines, respectively. . . . . . . . . . . . . . . . . . . . . . . . . 35
3.2.
Illustration of the patterns of unbalanced mean operating times. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.3.
Best and worst configurations in terms of idle time.. . . . . . 38
3.4.
Best and worst average buffer level results. . . . . . . . . . . . . . 40
3.5.
Illustration of a five-station line with descending levels of variability.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.6.
Variability configurations: S = Steady (CV = 0.08), M = Medium (CV = 0.27), V = Variable (CV = 0.5). . . . . . 44
3.7.
Bowl patterns—five and eight stations. . . . . . . . . . . . . . . . 45
3.8.
Best configurations (bowl shaped) for lines of five and eight stations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.9.
A five-station line with buffers evenly distributed between workstations. . . . . . . . . . . . . . . . . . . . 48
3.10.
Three sample simulation configurations for N = 5 and total buffer capacity of eight units (not to scale). . . . . . 51
3.11.
Best configurations in terms of reduction of idle time: Fve- and Eight-station lines with average buffer sizes of two and six (not to scale). . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.12.
Best configurations in terms of reduction of average buffer levels: Five- and eight-station lines with average buffer capacities of two and six (not to scale). . . . . . . . . . . 56
3.13.
Illustration of combining different configurations of mean operation times and variabilities: High variability (V), medium variability (M), and low variability (S). . . . . . 59
3.14.
Illustration of a pattern of mean operation times and variability combined. . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.15.
Best pattern for idle time performance. . . . . . . . . . . . . . . . 61
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xi
3.16.
Best ABL pattern. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.17.
Two examples of five-station lines with buffer space and mean operating times allocated unevenly (not to scale). . . . . 65
3.18.
Some of the buffer configurations considered (not to scale).. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.19.
Configurations of the buffer capacity along the line with the overall pattern. . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
3.20.
Illustration of some of the five-station lines simulated (not to scale). . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.21.
Variability configurations: S = steady, M = medium, V = variable. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3.22.
Configurations of the buffer capacity along the line with the overall pattern. . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.23.
Best idle time results: Visualization of combined buffer capacity allocation and pattern of variability. . . . . . . 76
3.24.
Best average buffer level results: Visualization of combined buffer capacity allocation and pattern of variability. . . . . . . . . .77
3.25.
Best throughput (TR) and idle time (IT) pattern for a five-station line (MT: mean operating time, CV: coefficient of variation, BC: buffer capacity allocation). . . . 82
3.26.
Best average buffer level configuration for a line length of five stations (MT: mean operating time, CV: coefficient of variation, BC: buffer capacity allocation). . . . . . . . . . . . 83
Boxes
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1.1.
Lean Manufacturing: The Case of Toyota . . . . . . . . . . . . . . 5
1.2.
Theory of Constraints (TOC) in Action . . . . . . . . . . . . . . . 8
1.3.
Bucket Brigade Triumphs . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.4.
Chapter 1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
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ILLUSTRATIONS
2.1.
Illustrations of Worker Variability . . . . . . . . . . . . . . . . . . . 21
2.2.
Chapter 2 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.1.
How to Interpret the Results . . . . . . . . . . . . . . . . . . . . . . . 32
3.2.
Average Buffer Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.3.
Chapter 3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
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Abbreviations and Acronyms ABL B COMSOAL CONWIP CV DI DBR IT JIT MT TOC TPS TR WIP
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average buffer level buffer Computer Method of Sequencing Operations for Assembly Lines constant work in process coefficient of variation degree of imbalance drum-buffer-rope principle idle time just in time mean time theory of constraints Toyota Production System throughput work in process
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CHAPTER 1
Introduction Rise of the Assembly Line When we think of an assembly line, our imaginations probably take us straight to the modern factory floor with images of machines, robots, and people engaged in assembling complex products that roll off the production line in a never-ending process. The basic concept of the assembly line, however, with individual workers specializing in just one or two specific tasks and creating a whole final product from the total efforts of the team of specialists, is not that new. A rather impressive example of mass production can be found in the Terracotta army commissioned by the Chinese Emperor Qin Shi Huangdi (215 BC), where different artisan workshops created particular body parts that were later assembled to produce 8,000 life-size clay soldiers and horses. So the concept of mass production extends far back into the history of human civilization. The development of modern mass production, however, is generally thought to have its roots in the assembly lines at the Ford Motor Company (1908–1915), where specialized workers were placed at workstations along a moving production line, each repeating the same limited number of tasks throughout the workday and each carefully positioned to get the car assembled from its various parts as rapidly and as efficiently as possible. The results of this mode of production are well known; prices of cars tumbled, huge numbers of cars could now be produced at affordable prices, and the assembly line method of production established itself worldwide in all sectors of industry. Companies that did not adopt these practices found themselves unable to compete in a very short time. Once the basic concept took off, a lot of attention was given to how to organize these assembly lines to get the best performance out of them. There have been unceasing efforts ever since to find the particular ways in
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which efficiency can be improved for the various types and configurations of assembly lines.
Searching for the Ideal Solution Paced, unpaced, balanced, unbalanced, just in time, push, pull: so much has been written about different ways of improving production line efficiency that managers can be forgiven if they struggle to navigate their way through all the models and theories and identify which approach is best for their own operation. We decided that it’s time to bring the most important ideas together in one place, examine the pros and cons of each one, and help managers decide how best to tackle their particular case. A primary concern for line managers has always been how to get the most out of their production system, given the limited amount of resources at their disposal. This is particularly so in the present context of global operations, dwindling resources, and economic uncertainty. First, if we take a look at how globalization is impacting production, we can see that the increasingly global nature of business has led over the last few years to a big debate surrounding the issue of relocation. Moving the entire production operation to a lower wage economy like China or India has obvious attractions, but the emergence of even lower cost countries such as Vietnam and the Philippines, combined with bad publicity about working conditions, shoddy quality, possible lawsuits, and unhappy stakeholders, has led many companies to decide to concentrate on making their Western-based operations as competitive and efficient as possible instead.1 One of the growing concerns of governments, society, and business in the last decade has been the rising pace of environmental degradation, in particular global warming and dwindling natural resources. The growing levels of carbon emissions are leading to frightening predictions concerning irreversible climate change and subsequent impacts on flora and fauna of the planet, which are our natural resources. One of the causes of climate change is human activity, and as this book is being written, governments are meeting to seriously discuss the ways and means to legislate for the diminution of countrywide production of man-made greenhouse gases, a significant proportion of which come from human energy use. Production facilities will certainly have to comply with upcoming legislation on
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3
carbon emissions, so finding efficient methods of production with less waste and less use of energy is going to be of utmost importance. The increase in production and consumption of goods worldwide over the last century has also meant that we have slowly been using up many of the planet’s natural resources such as oil (and its derivative products such as plastics) and minerals without paying enough attention whether these resources can be renewed or recycled. The result of this is that many of the raw materials needed for production of goods that we take for granted today are set to run out in the coming decades, and so alternatives will have to be found. In the meantime, it is important that we try to husband the resources we have and make sure that our production processes are as efficient as possible by reducing waste and energy use as much as we can. The present worldwide economic downturn has also emphasized the need to run the most efficient operations possible. Manufacturers everywhere are doing their best to cut overhead costs and enhance performance in order to remain profitable. All this naturally brings us to the question of what managers can do to stay in business in this tough operating environment. Obviously, one very interesting possibility for them would be to use their current resources more effectively, thereby cutting costs and improving performance while maintaining quality. For this to happen, the elimination of waste is an essential priority. Waste can be identified in many parts of the production process. Even a tiny percentage of improvement in productivity can generate large reductions in the cost of production. So it is not surprising that some of our best brains have been searching for new insights into line efficiency. What has emerged is that there are no “silver bullets” or “one-size-fits-all” solutions. A model that works well in some industries may be far less effective in others. This is not to say, however, that managers cannot find and adopt a particular solution based on general principles that will yield results. There are a number of generally applicable conclusions to be drawn that can help to guide decision making across a wide spread of operations. The first step in choosing the particular way to design an efficient assembly line is to identify what type of line it is, what specific characteristics it has, and what constraints exist due to the particular context, physical or otherwise.
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Production Line Characteristics There are many ways to describe the type and characteristics of a production line. In the following sections we are going to outline the main types. It is important to identify accurately the salient features of the line, because subsequent design issues rest firmly entrenched in the particular way the line is designed and the operating system that is in place.
Less Pace, More Speed First, every production line can be described as either paced or unpaced. The definition of a paced line is one that moves work pieces mechanically from one station to the next at a uniform speed. By adjusting the pace at which the line moves, the production manager can determine the precise rate of output. On the other hand, unpaced lines are defined as those in which the work is moved along the line by hand, by using some form of mechanical handling (e.g., a forklift truck, roller, or a conveyor), or sometimes by a combination of both. Operators can work at their own rhythm. Instinctively, one would tend to think that a paced line would be the more efficient, but research has, in fact, demonstrated that unpaced lines produce higher levels of productivity.
Push or Pull? Another way of classifying lines is by whether they are operated on a push or a pull system. Push lines mean that an operating station always processes a piece of work if there are a number of pieces in front of it to work on. Any particular station will continue to process regardless of what is happening further down the line. The consequence of this is that if the station upstream keeps producing while the station further along has stopped momentarily or is working more slowly, the number of unfinished pieces build up. This means that there is a need for a large amount of storage (or “buffer”) space to keep the production line fully active. As a consequence, extra space for storage has to be made available in addition to the increased cost associated with the inventory held in the buffers.
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5
The opposite is true of a pull line: here the production of a new unit only begins when stations further down the line request it. As pull lines have less need for storage of unfinished pieces or work in process (WIP), less additional cost is involved. One would think, then, that a pull strategy would always be the best way to go, and it was on this basis that the Japanese kanban (pronounced kahn-bahn) system was developed in the 1950s and spread widely and successfully throughout the world in the following decades.
Just in Time or Just Too Lean? The Japanese system based on the pull line that they call kanban is also referred to as just in time (JIT). Under this principle, production is planned according to customer demand, and supplies are delivered as and when they are needed. The positive consequences of this kind of system are that WIP and the floor space needed for buffers are reduced to a minimum. Often referred to as lean production, the aim is to cut wastage throughout the production process, usually by using smaller lot sizes. It clearly works in many cases.
Box 1.1. Lean Manufacturing: The Case of Toyota In the 1940s, managers at Toyota had been able to observe the production methods of Ford and were also interested in the operations of U.S. supermarkets, in particular the system in which customers could get what they wanted at the time and in the quantities they needed. It was not until 1953, however, that these observations were built upon and translated into what was essentially a pilot plant for testing the just-in-time mode of operation. The results of their trials were successful, and soon all their production facilities were operating using JIT methods. The fine-tuning of this system over 50 years led to more and more efficient and productive processes. Today the Toyota Production System (TPS) is one of the most successful lean manufacturing systems in the world. Many sources have discussed the philosophy and organization behind lean production—and it has turned out not to be that easy to mimic. Some of the tools used and the objectives, such as Toyota’s aim
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of reduction of three types of waste—muda (non-value-adding work), muri (overburden), and mura (unevenness)—seem fairly clear, but the level of attention to detail in the rigorous elimination of waste is not always that easy to achieve. In addition, the organizational context and in particular the training of employees at all levels in the lean production philosophy, their commitment, and the necessity of a fair rewards system are often overlooked. Although kanban offers many advantages, there are some drawbacks to it, which mean that it is not the universal panacea initially imagined for assembly line production. Some disadvantages of JIT are that the system depends on fairly stable prices and quality of supplies, as changes in these can be more advantageous for companies that keep inventory, allowing them some time to deal with price rises or defective supplies. Another problem directly concerned with the operation of the line is the strong likelihood of insufficient WIP at certain times, which leads to expensive out-of-stock situations. In a lean operation, any quality problems are also more exposed. Operators sometimes do not have access to a stock of WIP to use for any rework that is required, so the line comes to a halt. Finally, a particular disadvantage for performance indicators is that the JIT model does tend to involve a lot more time when workers are standing idle, waiting for the next piece to process. As much as 18% of their time on the shift can be spent doing nothing. This is seen as far too costly by most managers, although some claim that the increased idle time is offset by higher quality and lower WIP costs. So we see that lines can be identified as paced or unpaced, push or pull, and in the next section we’ll see that there is also an issue of balance.2
Losing Your Balance Can Be Good for You A balanced production line is one in which each step of a process takes almost exactly the same average amount of time as the step preceding it and following it. Every workstation completes its tasks in the same average time as each of the other workstations. For many years, the consensus has been that this is the ideal state of affairs. The amount of time, money, and patience expended by managers every year in an attempt to bring their line into balance shows how powerful this school of thinking has become.
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7
In contrast, unbalanced lines are those in which the workstations along the same assembly line may vary in the average time taken to complete their tasks. Unlike the balanced line, one station can be working faster or more slowly on average than its predecessors or successors. Again, one might believe that this kind of operation would not yield the levels of performance obtained from balanced lines, yet research indicates that an unbalanced line can in truth be the more efficient solution. When workers who work at different speeds, in other words who have different mean service times, are repositioned along the line in certain configurations, we can witness significant increases in output, reductions in idle time, and lower WIP stock requirements. For example, a bowl configuration, in which the slowest workers are placed at the start and the end of the line, with the faster workers in the middle, can produce impressive results.3 Production lines can therefore be classified according to whether they are paced or unpaced, work under a push or a pull system, and can be balanced or unbalanced. In the next section, we look at other ways of defining how these lines operate and the dilemmas faced by line designers when they consider how best to get the system running smoothly.
The Story of the Drum, the Rope, and the Bottleneck Although companies have been spending a lot of time and resources on balancing their lines, the fact is that most lines are naturally unbalanced: the actual work done at different stations needs a longer or shorter time to complete and there are the practical considerations of where enough space is available to locate the buffers. One of the theories developed to cope with this natural imbalance is the theory of constraints (TOC). This maintains that if you can identify the slowest station in the line (the constraint or bottleneck station) and assign extra resources to it, that station will never be starved of product to process and the whole line will run more smoothly. Ensuring that the bottleneck station functions efficiently has a knock-on effect on performance throughout the whole line, and allocating resources here is much more important than to other, less strategic workstations. In fact, they found that deliberately inserting a bottleneck station could achieve a higher output performance than a balanced line. The way TOC lines work is based on what is known as the drumbuffer-rope principle (DBR), as is shown in Figure 1.1.
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Workstations Input
1
2
3
4
Signal/Communications (Rope)
5
6
Inventory Time (Buffer)
7
8
Output
Bottleneck (Drum)
Figure 1.1. Drum, buffer, and rope.
The “drum” is the name given to the bottleneck station that dictates the pace of the entire line. The storage buffers are positioned near the bottleneck to ensure a sufficient supply of WIP. The “rope” is, in fact, a signaling device that the bottleneck station sends to all the other stations, telling them to work in harmony with the pace of the bottleneck. This signal can be anything from a card (kanban means “card” in Japanese) to a flag, and it can be an electronic or a verbal message. The results are enhanced on-time delivery and a more predictable flow of finished products.
Box 1.2. Theory of Constraints (TOC) in Action AIA, a French company that undertakes the maintenance of aircraft carriers for the French armed forces, noticed that they were not able to keep up with orders, and the number of planes waiting for maintenance was piling up. Their objective was to reduce time to delivery with no supplementary recruitment of workforce. They undertook a study of their operations and identified the bottlenecks in their processes, taking inspiration from the U.S. Air Force’s maintenance of its C5s. Every day they drew up a list of tasks for their ongoing aircraft maintenance projects. Once everything was entered into the Concerto software, they had the buffer time consumed and a calculation of the impact on the delivery date for each aircraft. In function of the constraints for each carrier and including global constraints, they were able to allocate resources to those aircraft at the top of the list. Using this method they had optimum allocation of their resources with strong emphasis on pooling. They were also able to freeze maintenance on a plane if resources were lacking for a particular task. Using TOC, this company was able to allocate its workforce more effectively, meaning less time spent in the offices and
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INTRODUCTION
9
more time on task completion. The number of planes in maintenance fell from five to six in 2007 to around three in 2008, meaning an average of two more aircrafts are back in operation.4 Some researchers have found that DBR lines outperform JIT lines. The biggest challenge in operating a DBR line is the need to ensure that there is sufficient product in the buffers to keep the bottleneck supplied all the time. The scheduling of DBR lines is also more difficult, as the whole line’s performance depends on the efficiency of the bottleneck station.5
Is CONWIP the Answer? Another TOC model is known as constant work in process, or CONWIP. Its success is founded on maintaining inventory at a constant level. When a completed product emerges from the end of the line, this immediately triggers the release of the next work piece at the front station. Again, CONWIP lines have been found to outperform JIT lines. There are several exceptions to this rule: if the lines are highly variable (stochastic) with long setup times, this can affect performance. Regular machine failures in the system can also mean that CONWIP design may not be the way to go. Other characteristics, such as high levels of scrap and so on, can also reduce efficiency of CONWIP. In these cases, JIT lines are more efficient than TOC lines, so choosing JIT probably will be the wiser option.6
Bring on the Bucket Brigade! One of the latest developments in the assembly line story is the bucket brigade line. This is a self-balancing line, in which the number of operators is fewer than the number of workstations. The operating speed (i.e., service time) of each worker is determined, and they are then placed in order from the slowest to the fastest. Each worker accompanies his or her work piece along the line until the point at which it is handed on to the next worker. The workers then return upstream to their first station so that they are ready either to take over another piece from their predecessor or, if they are first in line, to start work on a new piece. This is called
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“resetting the line.” Workers are not specialized in one task and can go to where the work is. One of the main advantages of this kind of line is its flexibility. The production rate can be adjusted by simply changing the number of workers, after which the line will spontaneously readjust itself to respond to perturbations that interrupt the running of the line. There is no WIP, so costs are reduced.
Box 1.3. Bucket Brigade Triumphs Several companies have adopted the bucket brigade system after trying other types of production and have had successful results. Two researchers, Bratcu and Dolgui,7 have collected and reported several instances of this phenomenon. For example, Subway sandwiches used this technique to improve its sandwich assembly time, and Mitsubishi Consumer Electronics America, suppliers of televisions and cellular phones, managed to improve its performance in record time, eliminating unfinished pieces and bottleneck risks from their lines. Another example is Tug Manufacturing, which produces tractors. The turnover in this company was very high (around 70%), leading to difficulties in achieving a steady production rate. They dealt with this problem by using the bucket brigade approach—with teams of four workers on a closed curve passing by the points of construction of four tractors, each of which required 10 steps for its completion. Each worker was then in charge of the completion of one of the steps. In this way, productivity increased and the time taken to train new workers decreased.
The bucket brigade system is at its most effective in the garment industry, in order-picking operations, or indeed in any line that involves relatively simple repetitive tasks and is particularly useful for seasonal production, in which recruitment of unskilled labor at peak periods is necessary. Because the training required is so short—as little as 45 minutes in some cases, even with unskilled workers—it is quick and easy to set up, and output improvements of as much as 30% can be achieved. Once the system is running, bucket brigade workers need little supervision and WIP is effectively zero.8
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Conclusion We have seen in this chapter that the concept of the assembly line began in the distant past but started to develop in the early 20th century to become a complex and widespread system that has been studied and implemented worldwide across all sectors of industry. The different methods of defining and operating production lines are constantly being researched and implemented, with advantages and drawbacks being found for all of them. There is certainly no shortage of production line efficiency frameworks available. All of them are adaptable to a broad range of industrial environments. The choice is yours. Clearly, every company has to strike the right balance between cost and quality for their line to be truly competitive, but at least you now have a comprehensive toolbox to work with.
Box 1.4. Chapter 1 Summary In this chapter we have seen an overview of general production line issues: • A brief history of the assembly line from 215 BC until the present day • The definition of an unpaced versus a paced production line • A discussion of push and pull systems • The pros and cons of just-in-time or lean production • The growing awareness that balanced lines do not necessarily outperform unbalanced lines • The theory of constraints and CONWIP • The bucket brigade self-balancing line9
We shall now move on to the focus of this book, which is unpaced production lines, and discuss their characteristics and the major issues of line balancing. The objective is that at the end of chapter 2, you will have a solid understanding of the issues involved in designing and configuring an assembly line and can then take a critical look at the lines studied by researchers and decide which types of design might suit your operations best.
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