One of the most frequently mentioned conceptual problems with DBR is the issue of wandering bottlenecks, that is, frequent changes in the resource constraint station. The usual cause for this is given that in the case of job shops, shifting of the order mix causes such shifts in the most overloaded resource. Goldratt disputes this issue as a problem out of both his experience and using the logic that even in a job shop there is usually one primary machine or skill that is driving the bulk of orders. An occasional shift in bottlenecks is not a problem as the shop can change its focus occasionally. Hurley and Kadipasaoglu (1998) speculate on the causes of wandering bottlenecks. They demonstrate that changing product mix is a minor contributor to this problem and that the primary cause is management actions in response to inappropriate performance measures. One such policy is the continuing use of non-bottleneck utilization as a performance measure-seeing unused protective capacity as a waste. Releasing material faster than the rope requires builds up inventory at many stations and disrupts the drum schedule with unneeded work delaying needed work. Increasing batch sizes to minimize setups can lead to large jobs at non-bottlenecks clogging the shop and creating an unnecessary shift of the bottleneck. They conclude that only in a small number of cases is a product-mix-driven wandering bottleneck truly an issue.

Riezebos, Korte, and Land (2003) report on a problem with maintaining lead times in a DBR implementation, which they corrected using Workload Control to better manage the release of material into the shop, thereby maintaining an appropriate buffer size.

Simons et al. (1996) discuss the difficulty of scheduling a DBR managed system with multiple CCRs where they correctly stipulate that a CCR need not be a bottleneck. They follow the process for applying DBR as outlined by Goldratt (1990, 241-3) in The Haystack Syndrome. They created a "diverse set of benchmark problems" on which to test the efficacy of the general DBR algorithm. They used a branch-and-bound approach to obtain optimal schedules and found that in the presence of multiple CCRs, the DBR solution averaged within 3 percent of optimal.

Floating or Multiple Bottlenecks

A situation that is frequently proposed to give DBR problems is the existence of multiple or floating bottlenecks; that is, bottlenecks that change over time because of seasonal or long-run changes in the product mix. Lawrence and Buss (1994) state that balanced utilization rates increase the shifting bottleneck problem. They further state that increasing capacity at non-bottleneck work centers is the "best hope" for improving shop performance.

Simons and Simpson (1997) defend DBR's ability to contend with multiple constraints. The Goal System utilizes an iterative procedure to schedule multiple constraints to "accommodate interaction."

Guan et al. (2007) report simulating an electronics manufacturing system with multiple bottlenecks. Lenort and Samolejova (2007) report on identifying floating bottlenecks in metallurgical production and using such identification to maximize output.

Summary and Conclusions

This literature amply demonstrates that DBR is an effective and efficient system for planning and control of both manufacturing and service organizations. It has been applied successfully in a wide range of organizations. Reported problems are few and seem to occur primarily where implementers develop inadequate protective capacity. Two remaining issues for research are the ideal levels of protective capacity and the correct initial buffer sizes. Buffer sizing is a short-term problem because buffer sizes can be adjusted quickly using information developed through Buffer Management. Protective capacity usually cannot be established precisely as a manager might hope, as equipment is available only in certain sizes so a piece of equipment yielding the desired amount of protective capacity may not exist. The most recent application of DBR is to supply chains. Early papers on this issue have argued that application of the 5FS and DBR within supply chains is both possible and beneficial.

For future research on cases, it would be helpful if the investigators would be specific about whether the plant was a V, A, or T configuration; whether the market or internal resource was the constraint; how buffers were sized initially; and how Buffer Management was achieved. This information would enable the reader to understand the implementation more thoroughly.

Future simulation research on more complex plants regarding protective capacity and protective inventory is needed. Most of such simulation research to date has involved only a few stations in an I formation.

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