Theory of Constraints Handbook - James Cox Iii [106]
1. Identify the system constraints.
2. Decide how to exploit the system constraints.
3. Subordinate everything else to the above decision.
4. Elevate the system constraints.
5. If, in the previous steps, the constraints have been broken, go back to Step 1, but don’t let inertia become the system constraint (Goldratt, 1988).
In Step 1, a company defines its drum. In Step 2, it develops buffers at shipping and the internal resource constraint if it exists. At Step 3, the rope is tied between the buffer and material release to maintain the constant buffer.
A number of articles have discussed 5FS. These include Mabin and Davies (1999), Ronen and Spector (1992), Jackson and Low (1993), Politou and Georgiadis (undated), Mabin and Davies (2003), and Trietsch (2005). In addition, Gupta et al. (2002) introduced a series of simulation models that were run with each successive model introducing another step.
Jackson and Low (1993) note that an important contribution of constraints management is the focus it provides the entire organization. When everyone understands the vital role the constraint plays in the organization, everyone measures their actions according to the effect on the constraint and thus the total productivity of the system.
Scheduling the Resource Constraint
In TOC, all workstations work to maintain the schedule set at the constraint resource. Goldratt (1990) describes how this schedule is derived in The Haystack Syndrome. For each order, we have the due date of the order. We also have an estimate of the time it will take for the order to move from the constraint resource to the shipping dock—the shipping buffer. Scheduling the resource constraint involves loading each job onto the constraint, a shipping buffer time before its due date, and resolving any timing conflicts. The Avraham Y. Goldratt Institute produced a set of production simulators (a Windows version is provided in Goldratt, 2003b) to teach potential users constraint-scheduling concepts.
The article by Schragenheim and Ronen (1990) is the most often cited description of how DBR scheduling works. They list three steps: (1) schedule the constraint, (2) determine the buffer sizes, and (3) derive the materials release schedule according to steps (1) and (2). Schragenheim and Dettmer (2001) and Schragenheim, Dettmer, and Patterson (2009) provide perhaps the most in-depth discussion of DBR, including a special case called simplified DBR, and such issues as multiple constraints, moving bottlenecks, multiple operations occurring at the bottleneck, and other complications. Simplified DBR (S-DBR) assumes that the market is the constraint and therefore uses only one buffer—the shipping buffer (frequently called the production time buffer). Of course, if there is an internal constraint, material will naturally accumulate upstream of the constraint establishing a de facto constraint buffer.
Scheduling Non-Constraints
The pure DBR methodology does not develop a formal schedule for non-constraints. Rather, the rope determines when material is to be released to the first station on a routing and material is allowed to flow naturally between workstations. If decisions made by workstation supervisors result in a hole deep in the buffer, then expediting by using small transfer batches to achieve overlapped operations at a few stations may be needed to get material into the buffer in time to avoid the hole reaching the buffer origin (starving the constraint).
The individual work center (non-constraint) supervisor is advised that when a hole deep in the buffer appears, he or she should schedule the missing job first. If there are no significant holes in the buffer, he or she is free to run any job next. The supervisor might choose a job because of a short, sequence-dependent setup time, for example. Many academics are uncomfortable with this informal, ad hoc, logic for dispatching at non-constraints. Some researchers have developed alternative mechanisms for scheduling non-constraints.
Protective Capacity
TOC breaks capacity at non-constraints