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Influence of Materials Properties on Process Planning Effectiveness
ISSN: 0148-7191, e-ISSN: 2688-3627
Published March 28, 2017 by SAE International in United States
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Process planning, whether generative or variant, can be used effectively as through the incorporation of computer aided tools that enhance the evaluator impact of the dialogue between the design and manufacturing functions. Expert systems and algorithms are inherently incorporated into the software tools used herein. This paper examines the materials related implications that influence design for manufacturing issues. Generative process planning software tools are utilized to analyze the sensitivity of the effectiveness of the process plans with respect to changing attributes of material properties. The shift that occurs with respect to cost and production rates of process plans with respect to variations in specific material properties are explored. The research will be analyzing the effect of changes in material properties with respect to the design of a specific product that is prismatic and is produced exclusively by machining processes. The three process plans that have been developed illustrate the importance of consideration of alternate work materials without impacting the product functionality, in attempts to decrease production cost, increase quality, and increase throughput. The results for the three process plans show their effectiveness as related to the utilization of product, process, and system level parameters such as surface finish, heat treated condition of the material, geometry, material hardness, melting point, production quantity, cutting tools, cutting fluids, cutting conditions, and machine tools. Criteria for effectiveness include the machining cost, tool cost, production rate, and throughput. The importance of the parameters and variables can be observed through the information presented in the tables.
CitationAl-Shebeeb, O. and Gopalakrishnan, B., "Influence of Materials Properties on Process Planning Effectiveness," SAE Technical Paper 2017-01-0227, 2017, https://doi.org/10.4271/2017-01-0227.
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