Theory of Constraints Handbook - James Cox Iii [109]
There are several overviews of TOC including some discussion of DBR published since the Mabin and Balderstone (2000) book appeared. Rahman (1998, 337) states that TOC contains two major components—the logistics paradigm, including DBR, and the Thinking Processes, which he calls a “generic approach for investigating, analyzing, and solving complex problems.” He includes the 5FS, the nine OPT® rules, and the definitions of the three operational measures (Throughput, Inventory and Operating Expense). He also includes a table of 139 articles and conference proceedings broken down by year and journal. Gupta (2003) provides an overview that relies heavily on both Rahman and Mabin and Balderstone as an introduction to a special issue of International Journal of Production Research. Watson et al. (2007) update the comprehensive discussion of the evolution of TOC previously discussed in Gardiner et al. (1994).
Boyd and Gupta (2004) give an excellent overview of TOC, comparing its philosophy to several somewhat similar philosophies but giving only a rudimentary overview of DBR.
Applying DBR to Different Types of Facilities: VATI Analysis7
The TOCICO Dictionary (Sullivan et al., 2007, 51) defines “VATI analysis—The stratification of operations environments into four generic types referred to as: V, A, T, and I. Each environment has an inherent set of undesirable effects that, properly understood, make operations management easier. Each type is named for the letter that resembles a diagram of the logical flow (not the physical flow) of materials. Usage: A single plant may be a combination of more than one type.” (© TOCICO 2007, used by permission, all rights reserved.)
Umble and Umble (1999) discuss VAT analysis; that is, classifying plants as one of these three types and recognizing that certain characteristics are common to each type. They state that VAT classification was developed around 1980 by Goldratt.
Product flow diagrams for V-plants are characterized by divergence points (hence the V-shape). Three characteristics are typical of V-plants:
1. The number of end items is large compared to the number of raw materials.
2. All end items sold by the plant are processed in essentially the same way.
3. The equipment is generally capital-intensive, highly specialized, and typically requires lengthy setups.
A-plants are characterized by convergent assembly points throughout the process. In such plants, a large number of purchased or fabricated component parts and materials, generally produced in a job shop environment, are combined to form subassemblies that are used to build unique end products.
T-plants are dominated by a major divergent assembly point at final assembly, where many different end items are assembled from a relatively limited number of component parts.
Umble and Umble (1999) go on to discuss the specific placement of buffers in each type of plant.
I-Plant Research
Many simulation models used to study aspects of DBR are simple I-plants. This is because issues such as what constitutes adequate protective capacity or the buffer’s impact on lead time can be studied in an I-environment without complicating factors that occur in A-, V-, or T-plants.
Fry et al. (1991) simulate an I-plant to show how having little WIP at non-constraints in DBR gives strong control of lead time.
Finch and Luebbe (1995) simulate a five-station system in which the constraint moves over time because of different learning curve rates at the five stations. Because of shifting work center times during much of the simulation, there is little or no protective capacity at non-constraints. The authors conclude that there are significant interactions between learning curve effects and constraint production and that there is need for further study of this issue.
Atwater and Chakravorty (1996) simulated