283588 Simultaneous Design and Scheduling of a Material Handling System

Monday, October 29, 2012
Hall B (Convention Center )
Chuanyu Zhao, Jie Fu and Qiang Xu, Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX

In multi-stage material handling processes, such as electroplating and polymeric coating, the design of production line is very important.  A typical production line includes a series of units/tanks for different processing purposes; each unit may be built with different capacities; and there is a hoist above the production line to transport jobs among different processing units.  In previous research, hoist scheduling problems have been broadly studied in order to maximize the productivity of a material handling system.  But the design of the production line draws little attention.  Actually, the design of the production line affects the productivity critically.  Because the design contains the allocation of each unit, which inherently determines the distance, and hence the travelling time between each pair of units.  The design also contains the capacity of each unit, which determines the system processing capability, and the job processing time in each unit.  If the production line in a material handling system is designed optimally, with a corresponding superior hoist scheduling, the productivity of the system will be even boosted. 

In this paper, an MILP model has been developed to design an optimized production line; and through the same model, a corresponding optimal hoist scheduling can also be provided.  The objective for the model is to maximize the productivity of a material handling system, and various constraints need to be met.  For instance, there is a budget limit for the design, and the hoist scheduling has to meet all the production requirements of various jobs.  The major merit in this work is that through this model, an optimal design and an optimal hoist scheduling can be generated simultaneously.  The efficacy of the proposed methodology is demonstrated by a case study.  The comparisons between an optimal design and a heuristic design have also been conducted.


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