

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 variationnot in product characteristics,
but in processing and material transfer timeson 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, criticaltoquality 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 commoncause 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 matchsticksanddice 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 matchsticksanddice
factory simulation.
JIT is also helpless unless downstream
production steps practice level scheduling (heijunka in Toyotaspeak) to
smooth out the perturbations in daytoday 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 matchsticksanddice 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 drumbufferrope (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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