Knowledge that Transforms

Each year the Manufacturing and Service Operations Management (MSOM) Society of INFORMS conducts a student paper competition. In Volume 2, Issue 2 of M&SOM, we published the extended abstracts of the 1999 winners in the hopes that this could become an annual event. Our hopes have become a reality. Sridhar Seshadri and Ravi Anupindi, New York University, cochaired the 2000 competition. The judges for the final round were Garrett van Ryzin, Columbia University; Yehuda Bassok, University of Southern California; and Michael Pinedo, New York University. The first-prize winner received $400, while second prize received $200. Prizes were awarded at the INFORMS meeting in San Antonio, Texas in November 2000. All finalists received a $50.00 discount coupon redeemable at an “e-tailer.” The winners and their faculty mentors were: First Prize Jérémie Gallien, Massachusetts Institute of Technology Faculty Mentor: Lawrence M. Wein, MIT “Design and Analysis of a Smart Market for Industrial Procurement” Second Prize Serguei Netessine, University of Rochester Faculty Mentors: Gregory Dobson and Robert A. Shumsky, University of Rochester “Flexible Service Capacity: Optimal Investment and the Impact of Demand Correlation” M&SOM would like to congratulate the winners as well as all five finalists. The extended abstracts of these papers follow.

Each year the Manufacturing and Service Operations Management (MSOM) Society of INFORMS conducts a student paper competition. In Volume 2, Issue 2 ofMS Yehuda Bassok, University of Southern California; and Michael Pinedo, New York University.The first-prize winner received $400, while second prize received $200. Prizes were awarded at the INFORMS meeting in San Antonio, Texas in November 2000. All finalists received a $50.00 discount coupon redeemable at an e-tailer.The winners and their faculty mentors were:First Prize JA©rA©mie Gallien, Massachusetts Institute of TechnologyFaculty Mentor: Lawrence M. Wein, MITDesign and Analysis of a Smart Market for Industrial ProcurementSecond Prize Serguei Netessine, University of RochesterFaculty Mentors: Gregory Dobson and Robert A. Shumsky, University of RochesterFlexible Service Capacity: Optimal Investment and the Impact of Demand CorrelationM&SOM would like to congratulate the winners as well as all five finalists. The extended abstracts of these papers follow.

Traditionally, assembly lines are laid out in a straight-line configuration where a worker covers only adjacent stations. In a U-line layout, on the other hand, two or more non-adjacent stations can be physically close to each other, making it possible for a worker to cover nonadjacent stations. This added flexibility increases the decision space for U-line layouts and can result in better balanced lines. This paper examines the impact of stochastic task times on the relative performance of U-line and straight-line layouts. Several analytical and simulation results are presented, and insights are provided to explain the difference in the performance of U-line and straight-line layouts. To summarize our main results, although balanced U-line layouts are at least as productive as balanced straight-line layouts given deterministic task times, they can be less productive given stochastic task times if they are balanced deterministically using mean times.

We examine leadtime-quoting polices for minimizing average lead time subject to customer service constraints on fill rate, tardiness, or relative tardiness in simple systems with exponential and normal processing times. By studying the resulting safety leadtimes implied by each policy we gain insight into why some policies perform more robustly with respect to different measures of customer service than do others. This analysis suggests that a simple constant safety leadtime policy should work reasonably well under most conditions. A series of simulation experiments of more complex production environments indicates that the constant safety leadtime policy does indeed exhibit robust performance. This, plus the fact that it is extremely simple to adapt to a wide range of production environments, makes it an attractive basis for real-world leadtime-quoting systems.

Every week, motion picture exhibitors must decide whether to keep or replace the movies playing in their theaters in light of the past week's sales data. This decision is complex because of the dynamic decision environment, the uncertainty of demand, the complex revenue-sharing terms between the retailer and the distributor, the need to commit to new movies for several weeks, and the competitive release patterns of movies. We formulate this problem as a Markov Decision Process (MDP) model, using it to obtain replacement policies for the exhibitor. We examine the effect of differences in quality and quantity of available movies, and their respective release dates on the returns from model-based normative solutions. We also show that two practical heuristics are significantly outperformed by the optimal policy for the MDP model. We conclude by applying the model to industry data.

The study examines the sustainability of manufacturing quality improvements following the implementation of work teams on production lines. We posit that the impact on manufacturing quality, measured as the defect rate trajectory, is monotonically nonincreasing over time and may, more specifically, assume the shape of an inverted S-curve. Employing a longitudinal research design, we investigate four work teams over a 28-month period in a field setting. Each team corresponds to one of the four interconnected production lines in an electromechanical assembly plant operated by a Fortune 500 firm. Results of our empirical analysis support the sustainability of quality improvements associated with work team implementation and partially support the S-shaped trajectory as the particular form of sustainability. However, variations in the manufacturing quality trajectories reflect the characteristics of the work team and the production line on which each the team is instituted. From the standpoint of practice, this study highlights the importance of work-team design and implementation decisions, especially the need to be proactive in identifying and resolving initial implementation difficulties.

We analyze the problem of minimizing average inventory costs subject to fill-rate type of service-level constraints in serial and assembly production/distribution systems. We propose optimal and heuristic procedures to solve this problem. Our model and solution procedures can be used to manage the fill rate or fill rate within a “time window” service measures. We also relate our service-constrained model to the traditional model with back-order costs and show that it is possible to prespecify backorder cost rates to achieve desired service levels. We explore the inventory cost impact of such a practice, and we find that the cost penalty can be very high.

We study the coordination of a two-echelon distribution system where a vendor distributes a single product to a set of independent buyers. The problem is analyzed as a Stackelberg game in which the vendor acts as the leader and buyers act as followers. A simple strategy is developed for the vendor to employ a uniform quantity-discount policy to coordinate buyers' replenishment times by the power-of-two policy. Solution procedures are developed for the equilibrium strategy. It is shown that time coordination generally has a substantial benefit for the vendor, although the benefit to the buyers may be limited. Furthermore, uniform quantity discounts to all buyers are normally feasible but not sufficient to achieve perfect channel coordination when buyers act independently. The proposed strategy obtains a high proportion of the maximum benefit under perfect channel coordination.