Theory of Constraints Handbook - James Cox Iii [686]
Applications
An example of a systems approach using TOC tools for managing the development of bio medical devices is depicted in Fig. 35-9.
A mid-size company developed new pharmaceutical and biomedical devices. Typically, the company takes a partially developed new product through the R&D phase, then laboratory testing, and then clinical trials. They would build a manufacturing plant to provide the product for testing. Every step in this very complex and exacting process must comply with the Federal Drug Administration (FDA) requirements and is subject to close oversight at every step. It is very expensive and can take years to obtain FDA approval.
Once FDA approval is achieved, this company would deliver the new product to one of the large multinational companies who in turn markets, mass produces, and sells the product. The benefit of reducing the new product development cycle is very significant. The large multinational companies fund the entire development effort at great expense; it could range from tens of millions to hundreds of millions of dollars. The company that brings the new product to market first will end up owning the market and will always be the predominant supplier. This is a very high stakes game indeed.
FIGURE 35-9 Integrated scheduling algorithm for a new product development.
The company has all three of the different types of variation present in their operations. As discussed earlier, it is crucial they recognize this and develop a synchronized solution set. In Fig. 35-9 the overall, or master schedule, is notionally presented as a 14-task critical chain project. This is Type 1 variability, where most of the variation is within the tasks themselves. The white “tasks” are not actually tasks, but rather are the aggregated time buffers that provide protection to the project when disturbances to the schedule happen. These buffers push the tasks to start earlier in time and since the safety time previously embedded in the tasks is removed, the duration of the project is significantly less while providing much greater protection.
The construction of the manufacturing plant is depicted in Fig. 35-9 as a subordinate critical chain project, which is also Type 1. The construction of the plant is synchronized to finish and be operational when required by a task on the master critical chain schedule. The company delayed starting construction of the plant by six months and it was completed and operational with time to spare. This allowed the company, in essence, to have an additional six months before the production line had to be baselined. The maturity of the product, due to having the results of six additional months of data, was such that zero changes were made to the schedule.
When the manufacturing plant became operational, it was now subject to Type 2 variation. The manufacturing lines, the processes, and the individual tasks had very little variability as required in order to obtain FDA approval. The scheduling algorithm used was Simplified Drum-Buffer-Rope (S-DBR; Schragenheim and Walsh, 2004), a version of DBR developed by Eli Schragenheim, (See Chapter 9) which released the raw material for manufacturing the product, delivering to the task on the master critical chain project in a timely manner. The manufacturing time was 50 percent less than what the company