Classification Criteria of Manufacturing Systems

There is a variety of criteria that have been used to distinguish and classify man-ufacturing systems. According to Carper & Snizek (1980), there are “virtually

Batch/Mix

Figure 2.2.1.– Typology of Process Industries (Fransoo & Rutten 1994, p. 52)

as many different ways to classify organizations as there are people who want to classify them” (p. 70).

An early attempt to classify production systems was made by Woodward (1965). She identified three types of production systems and related each to one type of management structure (in terms of centralization and level fo bu-reaucracy). Her three types of production systems are

• small batch and unit production

• large batch and mass production

• Continuous process production.

The work by Woodward (1965) is frequently cited and has been updated by other scholars (e.g., Hull & Collins 1987).

Fransoo & Rutten (1994) elaborate on the differences within the process industry. They establish the two extreme poles process/flow production and batch/mix production between which there is a continuum of differences (cf.

Figure 2.2.1). The authors thereby simplify some earlier typologies of produc-tion processes in which two dimensions – producproduc-tion process (ranging from “job shop” to “flow shop”) and customization of the product (ranging from “custom”

to “commodity”) – are defined to only one dimension. Fransoo & Rutten (1994) justify this simplification by pointing out the strong correlation of the two axes (customized products tend to be produced in job shops whereas commodities tend to be produced in flow shops) with the values lieing on a curve with a slope of 45° (similar to Figure 2.2.3).

They describe seven predominant criteria along which the differences can be established. The criteria are

• throughput time (process/flow: low; batch/mix high),

• determination of capacity, routing options for products, and volume flex-ibility (process/flow: clear determination of capacity/one routing for all products, no volume flexibility; batch/mix: difficult determination of ca-pacity, complex routing options, many configurations),

• product complexity (process/flow: low; batch/mix: higher),

• added value (process/flow: low; batch/mix: high),

• impact of changeover times (process/flow: high; batch/mix: low),

• number of production steps (process/flow: low; batch/mix: high), and

• number of products (process/flow: small; batch/mix: large).

Generally, process/flow production tends to require large and expensive produc-tion assets since large quantities of output are demanded, as the authors main-tain, whereas lower output demanded suggests batch/mix production.

Another important point Fransoo & Rutten (1994) raise concerns the number of different inputs and outputs in process industries and in discrete manufac-turing industries. They propose that in discrete manufacmanufac-turing, the number of inputs tends to be high, whereas the number of outputs tends to be low. That is, several components make up one product at the end of the production process.

In process industries, this ratio is reversed: the number of inputs is low whereas the number of different outputs is high. When products experience greater dif-ferentiation, then the number of different outputs increase in either case. The concept is illustrated in Figure 2.2.2.

A well-established classification was introduced by Hayes & Wheelwright (1979). They use the two criteria process structure and product structure to classify manufacturing systems (cf. Figure 2.2.3). Their underlying assumption is that a mismatch between product structure and process structure is likely to

Number of diff. Outputs

Number of diff. Inputs Discrete

Discrete with Product Options

Process

Process with Product Options

Figure 2.2.2.– Input to Output Ratio in Discrete Manufacturing and in Process Industries (Fransoo & Rutten 1994, p. 49)

cause inefficiencies. A position on the diagonal represents the “natural” choice (Hayes & Wheelwright 1979) for most manufacturing companies, and a position significantly above or below the diagonal may lead to unintended distortions, especially when chosen unconsciously.

The different characteristics of the two criteria reflect stages of product and process life cycle. Production starts off in a flexible way – Hayes & Wheel-wright (1979) refer to this process stage as “fluid” – and develops into a stan-dardized and automated stage as the product matures and volumes increase.

Each stage of the life cycle is linked to different management foci. As prod-uct and process maturity increase, more attention is given to process efficiency while flexibility tends to decline. In that respect, companies closer to the lower right-hand corner of the diagram arguably are more sensitive to interruptions in supply. Increased awareness and the existence of strategies to prevent, as well as contingency plans to resolve, supply shortages thus are likely to be more im-portant than for companies that are located closer to the upper left-hand corner.

McCarthy (1995, p. 45) suggests classifying production according to differ-ent types of complexity¹:

• “Product complexity: An indicator of the degree of manufacturing dif-ficulty associated with the product (number of parts, number of

connec-1Cf. Section 2.4 on page 48 for a more detailed discussion of complexity.

Jumbled Flow

Figure 2.2.3.– Product-Process Matrix according to Hayes & Wheelwright (1979)

tions, product variety and volumes, etc.). A primary influence on struc-tural and dynamic complexity.

• Open Complexity: The complexity of the environment that the manufac-turing system must interact with (customers, suppliers, legislation, etc.).

Also, a primary influence on structural and dynamic complexity.

• Structural Complexity: An internal complexity relating to the static/structural aspect of the manufacturing system. It is associated with hierarchy, size, flow structures, etc.

• Dynamic Complexity: Related to structural complexity, but deals with the activity and time aspects (operational) of the manufacturing system. De-scribes the interaction between resources (material, machines, labour).”

The description of these four types of complexity suggests that the first two types are independent variables of complexity whereas the latter two types are dependent variables as they are determined by the first two types. Indeed, prod-uct characteristics determine the number and type of operations that need to be applied in order to create the desired output. Product complexity, as described by McCarthy (1995) in terms of number of parts, connections, product vari-ety, volumes, and other characteristics, determine (not fully, but to considerable extent) what organizational resources are needed and how they should be orga-nized. Additionally, the environment poses certain requirements on the organi-zation. Besides customers, suppliers, and legislation, competitors are a major stakeholder that may have influence on how the firm will organize itself. Like-wise, dynamics of the production process depend on the type of product and its (complexity) characteristics as well as on the environment, e.g., customer demand and industry standards.

Melcher et al. (2002) classify production systems in a 5x5 matrix along the two dimensions

• “level of technology of production systems” as a technological variable and

• “workflow interdependence” as an organizational variable.

The result are 25 theoretical variations between the two extreme poles “low-tech job shop (residential construction)” and “CIMS²-dedicated focused automated factory (Saturn Auto Plant)”.