Theory of Constraints Handbook - James Cox Iii [105]
In a simple line, it is easy to see that constraints determine non-bottleneck performance. If there are two or more bottlenecks in a line, the constraint will be the station with the least capacity. Stations downstream of the constraint can process no faster than the constraint because material must pass through the constraint to get to them. Stations upstream of the constraint could work faster than the constraint, but this will build inventory at the constraint and eventually the futility of having upstream non-constraints working faster than the constraint will be recognized and the practice will be stopped.
To activate (a non-constraint producing more work that the constraint can process) a resource when the resulting output cannot get through the constraint is the meaning of Rule 3. Activating a non-bottleneck resource to produce more than can be processed by the constraint does not add any value to the company.
A bottleneck is a bottleneck only if it cannot keep up with market demand working 24/7. Thus, there is no reservoir of time from which an hour lost at the constraint can be replaced. It is simply lost to the system.
It has long been known that the slowest station in a line determines output. OPT® extends this principle to job-shop type flows. In a job shop, the constraint may shift around somewhat as the mix of orders varies from season to season but there is generally one machine that is the heart of the plant and the reason most of the orders are obtained. This machine or work center tends to be needed on almost every job and becomes a long-term constraint on the system. Thus, even beyond simple lines, the constraint determines the output of the system.
By having the transfer batch (the number transferred between two stations) be less than the process batch (the number processed between setups), it is possible to have several stations working on an order simultaneously. This gets the order through the facility very quickly. It could be done to expedite the order. Alternatively, it could be done simply to use a short lead time as a competitive weapon in the marketplace.
Process batches should be variable, not fixed. If a product is seasonal and a shop always makes one week’s worth of demand as a process batch, then the process batch will vary naturally over the course of the year. This approach allows little inventory to accumulate. If a fixed process batch large enough to cover a week’s demand during the peak season was to be used, inventory covering several weeks demand would be created during the off-peak periods. Having a variable process batch makes more sense. Traditional plants may use the Economic Batch Quantity (EBQ) (the number of units processed at a time to minimize setup and carrying costs) formula to determine a fixed process batch size, but the EBQ formula assumes a fixed demand so its use really is not appropriate in this situation.
Derivation of DBR Using the Five Focusing Steps
TOC says that constraints (anything that limits a system from achieving a higher performance versus its goal) determine the performance of a system and TOC provides methods for efficiently and effectively utilizing these constraints. Since it is not the main topic of this chapter, here I will present only a key definition and the Five Focusing Steps (5FS) without elaboration or delving into ramifications. There is expanded coverage of 5FS in Chapter 8 and elsewhere in the book.
The 5FS are as follows: