Printed circuit board scheduling in an openshop manufacturing environment

Printed circuit boards are used in a myriad of commercial and consumer products in today’s marketplace. In this paper, we address the problem of inserting/placing components on printed circuit boards using automated insertion/placement machines. The motivation to examine this problem stems from joint work with a major electronics manufacturer who not only introduced us to the manufacturing environment but also provided data for testing and validating our component allocation and scheduling methodology. The results of our analysis can be used to trade-off operational savings of reduced cycle times versus tactical costs of reorganizing the equipment on the shop floor. Further, we also are able to develop and validate a three step hierarchical scheduling methodology for use in similar manufacturing environments

Tool capacity planning in semiconductor manufacturing

The demand for distinct wafer types in semiconductor manufacturing is an explicit function of the electronic components in which these wafers are used. Given that the component demands vary not only by the product type but also over time, it is obvious that wafer demands are also lumpy and time varying. In this paper, we discuss strategic level investment decisions on procuring new equipment and aggregate level capacity planning. In this context, we examine the problem of planning wafer production over multiple time periods within a single facility assuming that a demand forecast for each wafer type for each period is known. To address this problem, we develop a multi-period mixed integer programming model to minimize the machine tool operating costs, new tool acquizition costs, and inventory holding costs. Given that production of wafers requires a large number of operations with multiple tools capable of performing each operation, tool operating costs are explicitly minimized by integrating the assignment of specific operations to tools in our model. Since our model is computationally intractable, we propose a Lagrangean-based relaxation heuristic to find efficient tool procurement plans

Provider selection and task allocation issues in networks with different QoS levels and all you can send pricing

We investigate an optimization problem a firmfaces when acquiring network capacity from multiple providers.We define two types of tasks the firm performs using data networks, and show that the time, bandwidth and quality requirements of each type are quite different. We formulate the associated problem as a cost minimization problem subject to quality and capacity requirements and offer multiple solution approaches. We analyze how different prices, quality and task distribution affect the optimal behavior of the firm.We also implement Generalized Bender's Decomposition to solve a relaxation of this problem in order to obtain a tight lower bound