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Article Excerpt
Ball Aerospace, which manufactures highly innovative products, recently implemented a just-in-time (JIT) manufacturing system to reduce costs, improve lead times, and enhance customer satisfaction. The company manufactures under customer requirements that dictate the timing and quantities of sales. In the first phase of our study, we used value stream mapping (VSM), a precursor to implementing JIT, for two products in the company's advanced antenna and video systems division. Using this approach, we reduced the lead times and identified opportunities for improvement in the manufacturing facility. In the second phase, we quantified the trade-off between operational and financial considerations of the JIT implementation. Using detailed data from the facility, we analyzed these trade-offs by investigating batch-sizing decisions under different types of demand patterns. Our analysis provided the company with the input it needed to make resource-allocation decisions and current and planned process improvements under changes in external demand.
Key words: manufacturing: performance, productivity; production, scheduling: applications.
History: This paper was refereed.
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Companies implement just-in-time (JIT) manufacturing systems to reduce manufacturing costs dramatically and achieve long-term profitability goals, thereby enhancing their competitiveness. Often, they implement JIT without aligning their products and processes (Wheelwright and Hayes 1979). This mis-alignment's impact on competitiveness can be particularly damaging when the company's portfolio consists of unique products manufactured in a job-shop flow and when the company carries out product-design iterations concurrently with manufacturing operations. Despite the reductions in inventory and lead time companies can achieve with JIT systems, the unanticipated consequence of using small batches or no batching at all in a job-shop flow can be severe because costs can significantly increase even with reduced batch sizes. Concerning quick-response manufacturing, Fisher and Raman (1996, p. 97) argued, "... it is not valid to judge the quality of decisions based on outcomes. Because of randomness, a good outcome does not necessarily imply a good decision." Improvements in outcomes do not necessarily reflect sound judgment in implementing JIT manufacturing.
We quantified the trade-off between operational and financial considerations in implementing JIT in Ball Aerospace's manufacturing facility under customer requirements that dictate the timing and quantities of sales. To examine the robustness of the manufacturing system to changes in external demand, we concentrated on three scenarios under fixed annual customer orders: (1) a base case in which the demand over time is stationary, (2) a pull case in which the demand over time is stationary and the customer will accept any quantity at any time, and (3) a mixed case in which the demand over time is nonstationary, for which we used the insights gained from the base case and the pull case. Ball Aerospace's manufacturing facility provided an ideal research setting because (1) it operates its manufacturing process to meet fixed customer orders, thereby providing us with an opportunity to experiment with operational and financial trade-offs through customer involvement, and (2) the manufacturing process typically involves new products and hence represents a jobshop flow, enabling us to focus on production flexibility. These characteristics of the facility insure that our study is generalizable to other industries. Understanding the impact of external demand on the manufacturing system can help managers to plan and control internal operations and external relationships with customers.
Background
In his seminal work, Harris (1913) asked the fundamental question in managing operations of how many flow units (or what production batch size) to manufacture at once and answered it by developing the economic order quantity (EOQ) model. The EOQ model seeks to analytically minimize the total cost of procuring and holding stock (Hopp and Spearman 2000). Modifying the assumptions of static and independent demand embedded in the original inventory model (Wilson 1934), many researchers subsequently developed several variants across many contexts considering perishability, reducing or increasing demand, and quantity discounts (Johnston 1996).
To survive and prosper in a global and highly competitive environment, manufacturing firms are implementing best practices, such as the JIT manufacturing system (Schonberger 1986). A JIT system manufactures products in very small batches, ideally single units, to achieve multiple strategic objectives (for example, low cost, high quality, and high flexibility) simultaneously. While efficiency is central to the EOQ model, production flexibility is at the heart of JIT philosophy. Thus, we consider batching as an operational constraint on flexibility to reconcile the cost consequences of limiting production flexibility in a given business environment. In a complex marketplace, inadequate flexibility can create financial risks (Betts and Johnston 2001).
In his early work, Beranek (1967) indicated that inventory holding costs could be the source of financial infeasibility, nonoptimal inventory, or both. According to Singhal and Raturi (1990, p. 408), financial risk increases as inventory holding costs increase. Financial researchers have also considered holding inventory as an option for companies bearing a price risk (Bollen et al. 2003). Gaur and Seshadri (2005) used options to construct an optimal hedging transaction to increase the expected utility for inventory decisions made by risk-averse firms when demand is correlated with the price of a financial asset.
Researchers have not addressed two interesting questions. First, decision makers must consider the operational and financial trade-offs in their business environments. Specifically, in the aerospace industry, the trades-offs relate to operational issues, for example, expensive parallel batch processes and changeovers, and to financial issues, for example, major resources tied up in holding finished goods inventory, costs for delayed receipt of sales revenues, and the soaring costs of direct labor. Second, the...
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