Theory of Constraints Example in Manufacturing

Most factory managers are familiar with the Theory of Constraints; the idea that there is always an upper limit to the throughput of a production system that is set by a capacity constrained resource or operation. In fact, many operations managers describe their job as removing these restraints in order to increase profit. 

Theory of Constraints Origin

This theory was first developed by Dr. Eliyahu Goldratt in conjunction with his 1979 manufacturing scheduling software program. This early predecessor to the APS programs of today was designed to help factories determine where the weak links in their production chains were. According to Dr. Goldratt, the purpose of the program was to identify bottlenecks in the manufacturing process by analyzing the production data from multiple line runs. By doing so, he believed that he could improve efficiency by correcting or improving the areas of a production facility that were identified as limiting the entire manufacturing process.

For example, imagine a factory line that produces 100 widgets an hour. In order to increase the number of items produced, a manager conducts a line evaluation and determines that the speed of the line is really controlled by how fast the workers can paint the final product. The Theory of Constraints says that even if he or she makes the machines run faster, the worker is only capable of painting so fast. That means that in order to increase production output, more paint workers have to be added or parts of the painting process need to be automated. Once this constraint is removed, the manager can repeat the line evaluation and identify the area that is now causing the most “hold up” on the production line.

Advanced Planning & Scheduling Utilization of Theory of Constraints

Of course, every manager knows that these studies are time consuming, and the answers aren’t always so clear. Results from line evaluations vary from day to day, and can change drastically because of a variety of factors such as fluctuating product mix or process changes. In many manufacturing facilities, it’s not uncommon to have hundreds of actual and possible limiting constraints.

Keeping track of these variables, as well as determining which ones are really hampering productivity, is one of the many functions of APS software. By analyzing the data associated with your line productivity, it’s possible for the software to determine and show where the “constraints” in your facility really are. Even better, your APS system can automatically create schedules that buffer your constraint resources against variability to avoid starving them so that your throughput is maximized and customer delivery is protected.