A COMPARISON OF DIRECT COST SAVINGS BETWEEN FLEXIBLE AUTOMATION AND LABOR WITH LEARNING

This paper compares flexible automation with labor‐intensive manufacturing processes in a batch production environment and considers learning, forgetting, inventory carrying costs, setup costs, production demand volume, previous production experience, and the proportion of material to labor cost. While flexible automation typically can reduce setup times, and therefore inventory carrying costs through smaller optimal batch sizes, the results of this research show that the effect of forgetting on relative cost savings is difficult to predict in some situations. When using optimal lot sizes in both the automated and labor environments, cost savings from flexible automation may be smaller than expected or may occur in different ways than anticipated.     

SIMULTANEOUS BATCHING AND SCHEDULING FOR CHEMICAL PROCESSING WITH EARLINESS AND TARDINESS PENALTIES

We consider the problem of determining the allocation of demand from different customer orders to production batches and the schedule of resulting batches to minimize the total weighted earliness and tardiness penalties in context of batch chemical processing. The problem is formulated as a mixed-integer nonlinear programming model. An iterative heuristic procedure that makes use of the network nature of the problem formulation is presented to approximate an optimal solution. An algorithm polynomial in the number of batches to produce is also presented that optimally solves the problem under special cost structures.     

Networks of capital,networks for migration: political–economic integration and the changing geography of Mexico–US migration

While economic globalization has altered the geography of international migration and introduced an array of new sources and destinations, our understanding of the specific mechanisms that link economic globalization to migration remains limited. In this article, I attempt to extend previous research by undertaking an empirical case study of Mexican migration to the USA. Using a unique dataset, I construct multivariate models to test whether, in the context of economic integration, occupations channel migration between similar sectors of the Mexican and US economies. I focus on the food‐processing sector because of its role in the geographic dispersal of Mexican immigration. The results show a strong channelling of Mexican immigration along an occupational line linking the Mexican and US food‐processing sectors. The implementation of the North American Free Trade Agreement (NAFTA), which ushered in a period of intensive political and economic integration, strengthened this occupational channel. By seeing the changing geography of Mexico–US migration in the context of economic globalization, this study casts light on the micro‐level foundations of the globalization–migration nexus.     

USING SHORT-TERM DEDICATION FOR SCHEDULING MULTIPLE PRODUCTS ON PARALLEL MACHINES

In a multiproduct, parallel machine environment, it may be beneficial to dedicate one or more of the machines to a single product for consecutive time periods. However, previous lot-sizing and scheduling models usually do not allow for such short-term dedication. This paper presents a mixed-integer programming model that allows for short-term dedication in scheduling parallel machines serving multiple products with dynamic demands. It also describes a Lagrangian-based algorithm for solving such scheduling problems. An experiment verifies the effectiveness of the algorithm and demonstrates the importance of allowing for short-term dedication. Capacity utilization, one of six factors investigated, greatly affects the use of dedication. A strong interaction effect between the number of machines and the number of products is also seen with respect to the usefulness of short-term dedication. A measure of estimated production frequency incorporates these two factors along with magnitudes of periodic demands. This measure has a strong relationship with the amount of short-term dedication used in solutions. Operations managers employing parallel machines could use the experimental results in deciding whether to use short-term dedication to reduce costs.     

EMPIRICAL EVALUATION OF EXPONENTIAL AND INDEPENDENCE ASSUMPTIONS IN QUEUEING MODELS OF MANUFACTURING SYSTEMS

This paper presents actual data (processing times, interarrival times, cycles-between-failures, and time-to-repair) from two automotive body welding lines. The purpose is twofold. First, to help researchers focus their work on realistic problems, we exhibit the nature of randomness actually found in two industrial manufacturing systems and provide a data source for realistic probability distributions. Second, we assess the validity of two common assumptions regarding this randomness in automotive manufacturing. Many queueing network models assume that certain random variables are independent and exponentially distributed. Though often reasonable, the primary motivation for the independence and exponentiality assumptions is mathematical tractability.     

MINIMIZING TOTAL WEIGHTED COMPLETION TIME ON A SINGLE BATCH PROCESSING MACHINE

We study the problem of scheduling jobs on a single batch processing machine to minimize the total weighted completion time. A batch processing machine is one that can process a number of jobs simultaneously as a batch. The processing time of a batch is given by the processing time of the longest job in the batch. We present a branch and bound algorithm to obtain optimal solutions and develop lower bounds and dominance conditions. We also develop a number of heuristics and evaluate their performance through extensive computational experiments. Results show that two of the heuristics consistently generate high-quality solutions in modest CPU times.