Thomas E. Vollmann

Performance Measures: Gaps, False Alarms, and the “Usual Suspects”

Using a two‐round Delphi process among 92 manufacturing managers from around the world, assesses the appropriateness of a variety of performance measures. The Delphi process used a survey technique that was pioneered by Dixon, Nanni, and Vollmann to highlight gaps (high perceived importance to the company but low weight in the performance measurement system) and false alarms (low perceived importance to the company but high weight in the performance measurement system). Direct cost reduction, machine efficiency, and labour efficiency are almost universally seen as false alarms. On the other hand, new product introduction, customer satisfaction, and employee involvement are frequently revealed to be gaps, although with less consistency. Cross‐industry comparisons are a distinctive feature of this research.

Reducing vendor delivery uncertainties in a JIT environment

Abstract Just-in-time (JIT) manufacturing systems have found wide acceptance in the automotive industry as well as in other industries such as electronic assembly. One of the key features of JIT systems is frequent reliable deliveries from local vendors. This article considers two major points related to managing inbound transportation from these local vendors. The first point is that vendor delivery uncertainties can be reduced if the JIT manufacturer takes over the responsibility for inbound logistics from all JIT vendors. In other words, we are suggesting that the manufacturing firm (vendee) pick up raw materials and purchased parts from its vendors rather than having the vendors deliver. The second major point is that a simple economic analysis and a computer-based decision support system (like that we propose in this article) could be used to help schedule the JIT pickups. The article begins with a description of why deliveries are critical in the JIT environment and why vendee pickup from local vendors can be a better alternative than vendor delivery. When a manufacturer manages its own inbound local deliveries it benefits from more timely information on upsets, reduced transportation costs, reduced transaction costs, and most importantly, reduced uncertainty in deliveries. We then turn to a model for how to schedule JIT pickups. This model addresses the following “JIT Vendor Pickup Problem”: For a given number of vehicles with limited capacity, find a one-week JIT vendor pickup schedule that will minimize the total incremental carrying, travel, and pickup costs subject to the constraint that the vendee does not run out of any item from any vendor. In the above problem definition, the demand rates for all items are assumed to be constant over the short term. This model can be imbedded in a computer-based decision support system to facilitate the daily scheduling of the pickups from the vendors. In the conclusion, we deal with the expected benefits to the vendee for managing its own incoming JIT pickups and then propose a model that could be used to implement this concept.

Critical Ratio Scheduling: Dynamic Due-Date Procedures under Demand Uncertainty

Abstract This paper is concerned with the problem of maintaining order due dates in job shops that manufacture products to replenish a finished goods inventory controlled by an order point system. Two different strategies for maintaining order due dates—static and dynamic due date procedures—are analyzed using both shop and inventory system performance measures. This study examines the influence of the degree of predictability of the final product demand pattern on the performance of the static and dynamic procedures. The demand pattern for individual products is characterized by a long-run demand rate, a period-to-period serial correlation coefficient of demand, and a coefficient of demand variation. The results indicate that the dynamic due-date procedure does not provide a significant improvement in the performance of the production system in comparison with the static procedure - even when the predictability of the demand during the replenishment lead time is improved.