Theory of Constraints Operations Management
by Skip Reedy
The management concepts of the Theory of Constraints were originally applied to manufacturing. In manufacturing, constraints are usually physical. In project management, the constraint of a single project is the Critical Chain.
Your system has a constraint. That sounds bad, but it’s good. It is the part of your system you can improve to get significant and nearly immediate results.
The Theory of Constraints focuses attention on the most loaded resource, the system constraint. Increasing the effective capacity of the constraint increases the output through the system. The constraint is also an indicator of the health of the system. If it’s running well, the system is running well. If the constraint is struggling or stopped, so is the system. It’s easier to manage a complex system with only one resource to watch closely.
A common manufacturing approach has been to pay attention to everything. Then we try to increase the efficiency of all of the individual system parts expecting to improve the whole. The primary intent seems to be to keep resources busy. Unfortunately, keeping busy is better at making inventory than money.
Other common approaches are based on the idea that improving anything will improve the system, and that pushing work into the system increases output.
Think of a garden hose with a kink in it. (Figure 1) Helping the kink will improve the output of that system. Helping any other part will not. [Well maybe pushing at 500PSI would momentarily help.]
Figure 1: Constricted Garden Hose
In the 1980’s, the Theory of Constraints (TOC) was developed by Dr. Eliyahu M. Goldratt to describe a common characteristic of systems, and he created a methodology using that characteristic to improve performance. Every system has something that limits it, usually just one thing. Identifying and helping this system constraint will improve the output significantly. Improving any other part of the system will not increase throughput. [Throughput is Sales less Totally Variable Expenses.]
Five-Step Process of On-Going Improvement
TOC has a Five Step Process that is repeatable. Each time through the steps, the system capacity and output increase. Costs and inventory often do not go up. It’s good for the bottom line.
1. Identify the system constraint.
2. Decide how to exploit the constraint.
3. Subordinate everything else to the above decision.
4. Elevate the constraint.
5. Avoid inertia. Go back to Step 1 and determine if the constraint has moved.
There is a Step 0. that is almost always done first: choke the release of orders to the shop to reduce Work-In-Progress (WIP). This by itself will reduce lead-time dramatically.
Identifying the constraint may be as simple as looking for the biggest pile of work.
Exploiting the constraint looks for ways to improve its performance, such as reducing downtime for lunch and breaks; giving it priority for repair; not having it work on non-priority or possible defective material.
Subordinating requires the rest of the system to be synchronized to the pace of the constraint. This is a paradigm shift for most people, especially managers. For example, it’s okay to be idle if there is no work to be done.
Elevating means obtaining more constraint capacity. This is usually the first point at which money is spent on the system.
Avoid inertia to keep the system improving. Go back to Step 1 to determine if there is a new constraint.
Typical manufacturing lead times have only 5 to 10% processing time. The rest of the time, orders are waiting in queues.
Drum – The constraint of a manufacturing system is called the Drum resource. It is the most heavily loaded resource. It has the least capacity. Everything else can go faster. Therefore, it should be the drumbeat to set the pace of the system.
Buffer – In order for the Drum to always have work, a Buffer of work is maintained in front of the Drum to protect it from starving. If the Drum stops working, the system throughput is stopped. An hour of downtime for the Drum is an hour of lost throughput to the system forever. Watch this drum resource carefully. Protect it.
Rope – The mechanism to release new work into the system is called the Rope. As the Drum completes work, the Rope allows new orders to be released.
If the Drum (constraint) capacity is increased, the system capacity is immediately increased. If the Drum capacity is raised above the next most loaded resource, that resource becomes the Drum.
The Five Steps in action
A very simplistic example will clarify how and why the constraint moves. The system shown in Figure 2 has five resources in sequence, with capacities of A=200/hour, B=180/hour, C=150/hour, D=170/hour and E=190/hour. It could be a production line, or any process. What is the maximum amount this system can yield in an hour?
C, with a capacity of 150 per hour, is the Constraint
Figure 2: Production sequence with different production rates
Increasing the capacity of B to 200/hour will not increase the system output because the capacity of C is limiting the system. All the other machines can keep up with C. Therefore, C is used as the drumbeat of the system. All the work-in-progress (WIP), after Raw Material and before the Constraint, is considered Buffer. (Figure 3) The Rope is a device, a method, to monitor the Buffer and advise Raw Material to
release more work to refill the Buffer.
If A produces 200 per hour, work will pile up in front of B, and B’s work will pile up in front of C. Both A and B must be subordinated to the constraint C, so they keep C supplied with work, yet don’t bury it. They maintain C’s Buffer in a predetermined range. If A or B breaks down, they have the extra capacity to refill the Buffer when they restart. If C, the constraint, breaks down, A and B sit idle until the constraint is back on line.
Figure 3: The sequence showing Drum, Rope and Buffer
Figure 3 shows the relationship of the Buffer and Rope to the Drum. Every machine can work at its capacity when it has work. When it does not have work, it doesn’t work. If B stops working, C will continue working, using the Buffer. The Buffer is sized to accommodate reasonable variation in the system.
Improving production at little cost
Increasing the capacity of constraint C to 165/hour will increase the system throughput by 10%, probably at no cost. C would still be the constraint. Since excess WIP was removed in Step 0, the increased throughput will appear very quickly. The 10% increase in Throughput is probably free! See Figure 4.
Constraint C is increased to 165/hour
Figure 4: System with element C throughput increased by 10%
Constraint C is increased to 210/hour. D becomes the new constraint with 170/hour.
Figure 5: Effect of increasing element C to 210 pc/hour
Increasing C from 165 to 210/hour will move the constraint to D as shown in Figure 5. D’s capacity is 170 versus C’s 210. That is only a 3% throughput gain for the system, even though C’s capacity increased 27% (45/hour). That is not much benefit provided by the increase in C. A smaller increase in C may be more cost effective.
The system is now limited to 170/hour, the rate of D, the new constraint.
Increase D to 185/hour and the constraint moves to B with 180/hour.
Figure 6: Effect of now increasing capacity of D
Increasing the capacity of D to 185/hour will move the constraint to B, 180/hour as shown in Figure 6. At some point, an improvement will require purchasing additional constraint capacity to increase throughput further. Up until that point, the improvements have been essentially free. No new resources were purchased and probably less overtime is required.
Always watch the constraint. Don’t let it starve or get buried in unneeded work. It’s the heartbeat of the system. If the constraint breaks down, it is the highest priority to be repaired.
The return on investment with the Theory of Constraints is powerful. It is usually straightforward to get a 50% increase in throughput very quickly. Repeat the Five Focusing Steps for further improvements. The most important changes are in the way the system is managed. Pay attention to the constraint. If any other part of the system struggles, the Buffer of work will be affected, indicating management attention
may be needed. Moderate fluctuations in the size of the Buffer are normal responses to system variation while the constraint continues working.
Theory of Constraints is simple. TOC does not aim for perfection. Good enough is perfect for now, until the next simple improvement. Just focus on the constraint. TOC is so simple that many people find it hard to believe.
One step at a time increases Throughput again and again. Each time, it’s easy to tell what will happen.
The following table shows examples of some typical results achieved by applying Theory of Constraints as described earlier:
Lead-Times are short and predictable Mean Reduction 69%
Cycle-Times Mean Reduction 66%
Due-Date-Performance Mean Improvement of 60%, @ 95+%
Inventory Levels Mean Reduction 50%
Revenue/Throughput Mean Increase 68%
Fixed costs are very slow to increase
Profits increase dramatically
Quality of life for employees improves
Demand on management attention is reduced