The “Theory of Constraints” approach

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Leveraging on the common idea that “a chain is no stronger than its weakest link”, the Israeli physicist E.M. Goldratt firstly introduced the Theory of Constraints (TOC) in his most famous business novel “the Goal”1. Looking to a production flow-shop as a chain, the weakest link is represented by the line bottleneck. Compared to the TPS approach of reducing wastes, this approach is focused on improving bottleneck operations, trying to maximize the throughput (production rate), minimizing inventory and operational expenses at the same time.

Its implementation is based on a loop of five steps:

Again, Deming’s concept of “improvement cycle” is recalled. However, improvements are only focused on the bottleneck, the Critical Constraint Resource (CCR), whereas in the Lean Production’s Kaizen approach bottom-up, an improvement may arise wherever wastes are identified; moreover, improvements only aim to increase throughput. It is though noticeable that the author includes, as a possible throughput constraint, not only machinery problem but also people (lack of proper skills) and policies (bad working). To this extent, Goldratt coined the “Drum-Buffer-Rope” (DBR) expression: the bottleneck workstation will define the production takt-time, giving the beat as with a drum. The remaining upstream and downstream workstations will follow this beat. This requires the drum to have an optimized schedule, which is imposed to all the production line. Thus, takt-time is not defined from the final demand anymore, but is set equal to the CCR minimal cycle time, given that the bottleneck capacity cannot be overcome. A “buffer” stock is only placed before the CCR, assuring that no upward issue could affect the process pace, reducing line throughput. This helps in reducing the inventory level in comparison to replenishment approaches, where buffers are placed among all the workstations. Eventually, other stock buffers may be placed in few synchronization points in the processes, besides the final product warehouse, which prevents stock-outs due to oscillating demand. The “rope” represents the job release authorization mechanism: a CONWIP approach is used between the CCR and the first phase of the process. Thus, the advanced entrance of a job in the system is proportional to the buffer size, measured in time. Failing to comply with this rule is likely to generate too high work-in-process, slowing down the entire system, or to generate a starvation condition on the CCR, with the risk of reducing the throughput. Several authors2, 3, 4 ] analyzed the DBR rule in comparison to planning with mathematical linear programming techniques. Results on the most effective approach are controversial.