Academic journal article Issues in Informing Science & Information Technology

Informing Implementers of Lean Strategy in Process Industries-The Central Role of Schedulers

Academic journal article Issues in Informing Science & Information Technology

Informing Implementers of Lean Strategy in Process Industries-The Central Role of Schedulers

Article excerpt


Among production and manufacturing businesses, Lean strategy is widely recognized as being important to business success and competitive advantage (Lewis, 2000; MacDuffie, 1995; Pfeffer, 1994; Shah & Ward, 2003). Lean strategy has successfully enabled businesses around the world to address customer demand, while maintaining high production volume (Ohno, 1988; Sohal & Egglestone, 1994; Sriparavastu & Gupta, 1997; White, Pearson, & Wilson, 1999). This strategy reduces throughput times and customer-response times (Fullerton & McWatters, 2001; White et al., 1999;), while paradoxically permitting (or in fact, requiring) lower inventory, contrary to traditional practice. However, not all industries have taken up this strategy to the same degree (Dennis & Meredith, 2000). For example, the origins of Lean strategy are grounded in automotive manufacturing and other forms of discrete industry where assembly activities dominate (Holweg, 2007). In these industries, value-add is gained through the assembly and handling of whole discrete components (e.g., computer assembly, clothing manufacturers, automotive industries, etc.), and they have been more successful than process industries at reducing waste and inventory levels (Abdullah & Rajgopal, 2003; Dennis & Meredith, 2000; Schonberger, 1982). In contrast, process industries add value by modifying the physical or chemical properties of materials. These industries lag behind discrete industries in the uptake of Lean strategy (Abdullah & Rajgopal, 2003; Belvedere & Grando, 2005; Dennis & Meredith, 2000).

The difference in uptake between the two industry sectors suggests that process industries are innately unsuitable for the successful adoption of Lean strategy, but this is not the case. The steel industry is an example of a process industry that is a potential candidate for the adoption of Lean strategy, and several reports of successful adoptions and executions of Lean strategy in the steel industry exist (Abdulmalek & Rajgopal, 2007; Dhandapani, Potter, & Naim, 2004; Harrison, 2005; Storck & Lindberg, 2007). These reports suggest that the steel industry can adopt at least some of the principles on which Lean strategy is based. However, these reports do not explain why Lean strategy is not accepted more widely in process industries, such as steel-making, chemical, paper, and oil industries.

Lean strategy varies from traditional production strategy in several ways. Primary differences are (Alony, 2010; Hopp & Spearman, 2004; Monden, 1994; Ohno, 1988; Taylor & Taylor, 2008; Womack & Jones, 2003): (1) Lean adopts a customer-centric view as opposed to the more traditional cost-centric focus. Therefore, Lean prioritizes quick delivery rather than scale advantages. (2) Lean focuses on overall supply chain optimization rather than localized optimization. Therefore, emphasis is placed in the production of small batches and paced production (i.e. Kanbans). (3) Lean focuses on continuous improvement, rather than episodic improvement and thus reduces levels of buffer inventory.

Lean is driven by a single strategic imperative, which is central for the successful execution of Lean strategy: that is, to maintain low levels of intermediate product inventory, also termed work-in-process (WIP). Maintaining low WIP levels throughout the supply chain of a business is central to sustaining Lean strategy (Hopp & Spearman, 2004). This requirement also represents the focal point of difficulty for process industries, as WIP levels are often used to buffer process-related problems (Abdullah & Rajgopal, 2003; Crama, Pochet, & Wera, 2001).

A further difficulty in executing Lean strategy stems from the way WIP levels are controlled. WIP inventory levels are not controlled directly (Sterman, 1989). Rather, they result from indirect daily operational decisions regarding batch sizes, number of changeovers, and aspired inventory levels. …

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