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into three categories5: (1) productive capacity, (2) protective capacity, and (3) excess capacity. Productive capacity is that capacity equal to the constraint’s capacity—the ability to produce the number of units that the constraint canproduce. Protective capacity is capacity needed to restore buffers to their ideal state after a disruption—to refill the time buffer that has become depleted or to empty the space buffer that now has material awaiting processing downstream of the constraint. This restoration of the ideal state of the buffer needs to be done quickly, before another disruption occurs. Excess capacity is capacity over and above productive and protective capacity.

Protective capacity is one of the most vital aspects of DBR because if there is insufficient protective capacity, then the buffer cannot be refilled quickly enough when the buffer is low and thus the drum is vulnerable to possible starvation6 by upstream stations or blocking by downstream stations. Since an hour lost at the drum is an hour of lost output if the drum is a resource constraint, downtime at the drum can be extremely expensive. Protective capacity is idle when the buffer is in an ideal state and needs no restoration. The non-constraint station uses only enough capacity to produce at the drum’s pace. However, once a buffer leaves its ideal state, all affected non-constraints must use their protective capacity to restore the buffer to an ideal state before some other problem threatens to idle the drum.

Of course, in a deterministic environment there would be no need for protective capacity because a constant amount of inventory would be held in the time buffer. An issue related to the establishment of a DBR system is “How much protective capacity is needed and how should it be arranged?” There have been only a few studies of this issue. This issue is especially important if there are capacity constrained resources (CCRs) in the system. Recall, a CCR is defined by the TOCICO Dictionary (Sullivan et al., 2007, 7) as “any resource that, if its capacity in not carefully managed, is likely to compromise the throughput of the organization.” (© TOCICO 2007, used by permission, all rights reserved.)

Literature on DBR Scheduling

In discussing literature on DBR, I first present some overview articles that principally discuss the 5FS or the nine OPT® rules. Then I move to simulation models and case studies divided by VAT classification. V, A, and T represent types of plants with V-plants dominated by divergences in flows, A-plants dominated by assembly operations, and T-plants experiencing a huge increase in variety in the final operations. After the sections on V-, A-, and T-plants, I present those simulations and cases that could not be assigned a specific VAT class.

Overviews

When TOC first appeared, total quality management and JIT were also gaining popularity. Because Goldratt was doing most of his information transfer via workshops and his books The Goal and The Race, many people lacked a true sense of what TOC entailed. A number of people sought to fill this relative void by introducing articles covering the 5FS or the nine OPT® rules, and especially DBR and Buffer Management. Some also reported on DBR implementations. Because the articles are broader than case studies of a single implementation, this section of the chapter was developed to gather these broad overviews.

Cox and Spencer (1998) devote a chapter of The Constraints Management Handbook to the DBR scheduling method. Throughout the chapter, they give a detailed three-product, five-work-center example, showing how to develop a schedule for the drum and for shipping. They also present a section on Buffer Management and a section on how DBR works within a material requirements planning (MRP) system. Overall, this is an excellent short summary of DBR.

Mabin and Balderstone (2000) present a book containing over 300 abstracts for books and papers on TOC published prior to 2000. They present a tree showing all aspects of TOC, with DBR belonging to a branch on production