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Automotive assembly plants are unique from otherindustrial facilities in that they combine highoutput volume with high part counts (over 4,000 pervehicle) and high variety in a product flow layoutinvolving a large quantity of fixed positionmaterial handling equipment. While assembly plantsshare common factory layout issues such as, dockplacement, storage placement, transport batch sizesand aisle design, it is the high material flowvolumes of large and heavy products coupled with theless layout flexibility, due to fixed equipment,that make automotive assembly plants uniquely suitedfor the evaluation and benchmarking metrics proposedin this dissertation.This dissertation proposes new metrics capable ofevaluating and comparing automotive assembly plantdesigns based on the efficiency of each plant'saisle design, dock placement and intensityallocation. These performance metrics are generatedfrom readily available information and are evaluatedagainst hypothetical "best case" and "worst case"scenarios. These metrics have been developed for useby practitioners to design and benchmark automotiveassembly plants.

Autorentext

David Sly, PE is a globally recognized expert in the design of Manufacturing Process Engineering and Factory Design tools and techniques. He received his BS, MS and PhD degrees in Industrial Engineering and an MBA from Iowa State University. David is president of Proplanner.COM, and an adjunct faculty member at Iowa State University.

Klappentext
Automotive assembly plants are unique from other industrial facilities in that they combine high output volume with high part counts (over 4,000 per vehicle) and high variety in a product flow layout involving a large quantity of fixed position material handling equipment. While assembly plants share common factory layout issues such as, dock placement, storage placement, transport batch sizes and aisle design, it is the high material flow volumes of large and heavy products coupled with the less layout flexibility, due to fixed equipment, that make automotive assembly plants uniquely suited for the evaluation and benchmarking metrics proposed in this dissertation. This dissertation proposes new metrics capable of evaluating and comparing automotive assembly plant designs based on the efficiency of each plant's aisle design, dock placement and intensity allocation. These performance metrics are generated from readily available information and are evaluated against hypothetical "best case" and "worst case" scenarios. These metrics have been developed for use by practitioners to design and benchmark automotive assembly plants.