Theory of Constraints Handbook - James Cox Iii [115]
A dummy constraint is a resource constraint that is inexpensively eliminated. Pass and Ronen (2003) note two common dummy constraints in marketing and sales: (1) Shortage of inexpensive administrative assistance and (2) lack of laptops and communications equipment such as portable fax machines. They further note three common dummy constraints in R&D: (1) Shortage of low cost components and accessories, (2) shortage of low cost administrative assistance, and (3) lack of computers and IT tools. Breaking these dummy constraints may give a significant elevation to the market constraint.
Smith et al. (1999) also mention DBR as an aid in product development at Allied Signal and Alcoa.
Re-Entrant Flows
Wu and Yeh (2006) describe the use of DBR in a situation in which a part passes through the constraint twice in flowing through the plant, known as “re-entrant flows.” This situation commonly occurs in semiconductor manufacturing. According to Wu and Yeh, the method of scheduling using DBR as described in The Haystack Syndrome (Goldratt, 1990) cannot effectively schedule environments with bottleneck re-entrant flows. They cite a number of articles describing the use of DBR in re-entrant flows including Huang et al. (2002), Kayton et al. (1996; 1997), Kim et al. (2003b), Klusewitz and Rerick (1996), Levison (1998), Mosely et al. (1998), Murphy (1994), Murphy and Dedera (1996), Rose et al. (1995a, b), Tyan et al. (2002), and Villforth (1994). Wu and Yeh (2006) then propose a scheduling method for DBR that they feel is appropriate for manufacturing facilities with bottleneck re-entrant flows. Rippenhagen and Krishnaswamy (1998) simulated a wafer fabrication facility with re-entrant flows using a variety of dispatching rules and Theory of Constraints. Kim et al. (2009) report on a simulation study of a hypothetical wafer facility with re-entrant flows and protective capacity. They are interested in, among other things, the trade-off between protective capacity and protective inventory. The study is based on a six-station line with re-entrant flows and times per part ranging from 8 min to 12 min and protective capacity ranging from 1 min per part to 4 min. They found that simply knowing the percentage of downtime at non-constraints was not sufficient to understand the need for protective capacity and inventory. Specifically, they found that infrequent long outages required more protective capacity/inventory than did frequent short outages even though the proportion of time the station was out was the same. They also found that resource downtime had more impact on the constraint than did processing time variation. They found that allocation of protective capacity throughout the line was more important than protective inventory. WIP inventory involves a tradeoff between Throughput level and cycle time. Beyond some point, adding more inventory does not improve Throughput, so an appropriate level must be chosen.
Recoverable Manufacturing and Remanufacturing
Guide (1997) discusses the successful application of DBR to recoverable manufacturing, where used products are returned from the consumer to the manufacturer, who then remanufactures the product. Guide uses the term “recoverable product environment” to describe the processes to recover materials via recycling at the end of the product life. Guide (1996) showed that DBR could be a successful production planning and control system for remanufacturing.
Buffer Management Literature
While few of the above simulation or case studies above recognize Buffer Management as a necessary condition