Theory Of Constraints Handbook.pdf
Julia Heaslet
The theory of constraints (TOC) is a management paradigm that views any manageable system as being limited in achieving more of its goals by a very small number of constraints. There is always at least one constraint, and TOC uses a focusing process to identify the constraint and restructure the rest of the organization around it. TOC adopts the common idiom "a chain is no stronger than its weakest link". That means that organizations and processes are vulnerable because the weakest person or part can always damage or break them, or at least adversely affect the outcome.
The theory of constraints is an overall management philosophy, introduced by Eliyahu M. Goldratt in his 1984 book titled The Goal, that is geared to help organizations continually achieve their goals.[1] Goldratt adapted the concept to project management with his book Critical Chain, published in 1997.
An earlier propagator of a similar concept was Wolfgang Mewes[2] in Germany with publications on power-oriented management theory (Machtorientierte Fhrungstheorie, 1963) and following with his Energo-Kybernetic System (EKS, 1971), later renamed Engpasskonzentrierte Strategie (Bottleneck-focused Strategy) as a more advanced theory of bottlenecks. The publications of Wolfgang Mewes are marketed through the FAZ Verlag, publishing house of the German newspaper Frankfurter Allgemeine Zeitung. However, the paradigm Theory of constraints was first used by Goldratt.
The underlying premise of the theory of constraints is that organizations can be measured and controlled by variations on three measures: throughput, operational expense, and inventory. Inventory is all the money that the system has invested in purchasing things which it intends to sell. Operational expense is all the money the system spends in order to turn inventory into throughput. Throughput is the rate at which the system generates money through sales.[3]
Before the goal itself can be reached, necessary conditions must first be met. These typically include safety, quality, legal obligations, etc. For most businesses, the goal itself is to make profit. However, for many organizations and non-profit businesses, making money is a necessary condition for pursuing the goal. Whether it is the goal or a necessary condition, understanding how to make sound financial decisions based on throughput, inventory, and operating expense is a critical requirement.[3]
The five focusing steps aim to ensure ongoing improvement efforts are centered on the organization's constraint(s). In the TOC literature, this is referred to as the process of ongoing improvement (POOGI).
A constraint is anything that prevents the system from achieving its goal. There are many ways that constraints can show up, but a core principle within TOC is that there are not tens or hundreds of constraints. There is at least one, but at most only a few in any given system. Constraints can be internal or external to the system. An internal constraint is in evidence when the market demands more from the system than it can deliver. If this is the case, then the focus of the organization should be on discovering that constraint and following the five focusing steps to open it up (and potentially remove it). An external constraint exists when the system can produce more than the market will bear. If this is the case, then the organization should focus on mechanisms to create more demand for its products or services.
The concept of the constraint in Theory of Constraints is analogous to but differs from the constraint that shows up in mathematical optimization. In TOC, the constraint is used as a focusing mechanism for management of the system. In optimization, the constraint is written into the mathematical expressions to limit the scope of the solution (X can be no greater than 5).
If a constraint's throughput capacity is elevated to the point where it is no longer the system's limiting factor, this is said to "break" the constraint. The limiting factor is now some other part of the system, or may be external to the system (an external constraint). This is not to be confused with a breakdown.
Buffers are used throughout the theory of constraints. They often result as part of the exploit and subordinate steps of the five focusing steps. Buffers are placed before the governing constraint, thus ensuring that the constraint is never starved. Buffers are also placed behind the constraint to prevent downstream failure from blocking the constraint's output. Buffers used in this way protect the constraint from variations in the rest of the system and should allow for normal variation of processing time and the occasional upset (Murphy) before and behind the constraint.
Buffers can be a bank of physical objects before a work center, waiting to be processed by that work center. Buffers ultimately buy you time, as in the time before work reaches the constraint and are often verbalized as time buffers. There should always be enough (but not excessive) work in the time queue before the constraint and adequate offloading space behind the constraint.
Buffer management, therefore, represents a crucial attribute of the theory of constraints. There are many ways to apply buffers, but the most often used is a visual system of designating the buffer in three colors: green (okay), yellow (caution) and red (action required). Creating this kind of visibility enables the system as a whole to align and thus subordinate to the need of the constraint in a holistic manner. This can also be done daily in a central operations room that is accessible to everybody.
There are four primary types of plants in the TOC lexicon. Draw the flow of material from the bottom of a page to the top, and you get the four types. They specify the general flow of materials through a system, and also provide some hints about where to look for typical problems. This type of analysis is known as VATI analysis[6] as it uses the bottom-up shapes of the letters V, A, T, and I to describe the types of plants. The four types can be combined in many ways in larger facilities, e.g. "an A plant feeding a V plant".
From the above list, one can deduce that for non-material systems one could draw the flow of work or the flow of processes, instead of physical flows, and arrive at similar basic V, A, T, or I structures. A project, for example, is an A-shaped sequence of work, culminating in a delivered product (i.e., the intended outcome of the project).
The focusing steps, this process of ongoing improvement, have been applied to manufacturing, project management, supply chain/distribution generated specific solutions. Other tools (mainly the "thinking process") also led to TOC applications in the fields of marketing and sales, and finance. The solution as applied to each of these areas are listed below.
Within manufacturing operations and operations management, the solution seeks to pull materials through the system, rather than push them into the system. The primary methodology used is drum-buffer-rope (DBR)[7] and a variation called simplified drum-buffer-rope (S-DBR).[8]
Drum-buffer-rope is a manufacturing execution methodology based on the fact the output of a system can only be the same as the output at the constraint of the system. Any attempt to produce more than what the constraint can process just leads to excess inventory piling up.[9] The method is named for its three components. The drum is the rate at which the physical constraint of the plant can work: the work center or machine or operation that limits the ability of the entire system to produce more. The rest of the plant follows the beat of the drum. Schedule at the drum decides what the system should produce, in what sequence to produce and how much to produce.[10] They make sure the drum has work and that anything the drum has processed does not get wasted.
The buffer protects the drum, so that it always has work flowing to it. Buffers in DBR provide the additional lead time beyond the required set up and process times, for materials in the product flow. Since these buffers have time as their unit of measure, rather than quantity of material, this makes the priority system operate strictly based on the time an order is expected to be at the drum. Each work order will have a remaining buffer status that can be calculated. Based on this buffer status, work orders can be color coded into Red, Yellow and Green. The red orders have the highest priority and must be worked on first, since they have penetrated most into their buffers followed by yellow and green. As time evolves, this buffer status might change and the color assigned to the particular work order change with it.[11][12]
Traditional DBR usually calls for buffers at several points in the system: the constraint, synchronization points and at shipping. S-DBR has a buffer at shipping and manages the flow of work across the drum through a load planning mechanism.[13]
The rope is the work release mechanism for the plant. Orders are released to the shop floor at one "buffer time" before they are due to be processed by the constraint. In other words, if the buffer is 5 days, the order is released 5 days before it is due at the constraint. Putting work into the system earlier than this buffer time is likely to generate too-high work-in-process and slow down the entire system.[14]
Automated production lines achieve high throughput rates and output quantities by deploying automation solutions that are highly task-specific. Depending on their design and construction, these machines operate at different speeds and capacities and therefore have varying efficiency levels.
A prominent example is the use of automated production lines in the beverage industry. Filling systems usually have several machines executing parts of the complete bottling process, from filling primary containers to secondary packaging and palletisation.[15]
b1e95dc632