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Beyond the Theory of Constraints: How to Eliminate Variation and Maximize Capacity

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The matchsticks and dice exercise in Goldratt's and Cox's The Goal illustrates the effect of variation--not in product characteristics, but in processing and material transfer times--on a balanced factory that is operating at 100 percent capacity. The Goal asks, "Why do you think it is that nobody after all this time and effort has ever succeeded in running a balanced plant?" More than half a century before The Goal was written, Henry Ford claimed to have run a balanced factory at close to 100 percent capacity: "The idea is that a man must not be hurried in his work— he must have every second necessary but not a single unnecessary second." We conclude from the Kingman Equation (for cycle time in queue as a function of utilization and variation) and detailed examination of Henry Ford's methods that Ford achieved the seemingly impossible by suppressing variation in processing and material transfer times. Beyond the Theory of Constraints explores the methods that Ford, as well as modern lean practitioners, have used to achieve this.

Preface (c) 2007 Producivity Press

Eliyahu Goldratt's and Jeff's Cox's The Goal (1992, 86) asks, "Why do you think it is that nobody after all this time and effort has ever succeeded in running a balanced plant?" Henry Ford (1922, 82) claims to have done so: "The idea is that a man must not be hurried in his work— he must have every second necessary but not a single unnecessary second." Ford's apparent success in doing what The Goal shows to be impossible prompted this book's development.

When manufacturing engineers think of variation, critical-to-quality product characteristics are the first things that come to mind. The concept of variation in product characteristics is in fact central to the quality sciences. This is not, however, the variation that prevents operation of a balanced factory at close to 100 percent capacity. Variation in processing times and material transfer times either wastes capacity or requires large inventories as insurance against its effects. It is therefore necessary to state the following proposition at the outset:
(1)   Variation in product characteristics causes rework and scrap.
o     This is the familiar random or common-cause variation whose effects are shown by measurement histograms. The process standard deviation is the basis of the control limits for statistical process control charts.

(2)   Variation in processing and material transfer times is the root cause of longer cycle times, higher inventories, and inability to run a balanced factory at close to 100 percent capacity.
The matchsticks-and-dice simulation in The Goal illustrates the latter variation's effects. The simulation also shows Ford's proposition to be an obvious formula for a deranged nightmare in which inventory overruns the factory while cycle time in queue becomes infinite. As utilization approaches one hundred percent, cycle time in queue (and hence inventory) will indeed approach infinity— unless variation in processing times and material transfer times approaches zero. Ford's production system was designed explicitly to suppress this kind of variation, and his success demands close investigation of the methods he used. Furthermore, Toyota's heijunka (level scheduling, production smoothing) concept reflects both the need and the ability to suppress the "random" variation suggested by The Goal's matchsticks-and-dice factory simulation.

JIT is also helpless unless downstream production steps practice level scheduling (heijunka in Toyota-speak) to smooth out the perturbations in day-to-day order flow unrelated to actual customer demand. Otherwise, bottlenecks will quickly emerge upstream and buffers ("safety stocks") will be introduced everywhere to prevent them (Womack and Jones, 1996, 58).

It is the author's conclusion that The Goal's matchsticks-and-dice exercise is an excellent device for teaching the effects of variation on throughput and inventory. It may also, however, teach the unintended lesson that the factory is at the mercy of this variation. A die roll suggests unavoidable random variation (also known as common cause variation) but the workstation is nonetheless capable of processing six units. This book's purpose is to teach the reader how to identify and remove the variation, and thereby roll a six every time.

The book is organized as follows:
(1)   Chapter 1 is an overview of the Theory of Constraints, and it also covers the engineering and managerial economic aspects of TOC.
(2)    Chapter 2 covers pull production control methods such as kanban and synchronous flow manufacturing's drum-buffer-rope (DBR) system.
(3)    Chapter 3 illustrates the effect of variation in processing and material transfer times, and shows why this variation prevents achievement of 100 percent utilization.
(4)       Chapter 4 describes methods for reducing variation in processing and material transfer times. Some of the material overlaps with the theme of Chapter 5 because techniques that suppress variation often improve productivity, and vice versa.
(5)        Chapter 5 discusses methods for increasing productivity and reducing cycle time. These are useful for elevating the constraint (increasing its capacity) and they may also reduce variation.


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