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Influence of Materials Properties on Process Planning Effectiveness
Technical Paper
2017-01-0227
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
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.
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Al-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.Data Sets - Support Documents
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References
- Qiao L , Yang Z , Wang HB A computer-aided process planning methodology Comput Ind . 1994 25 1 83 94
- Wong T , Chan L , Lau HC Machining process sequencing with fuzzy expert system and genetic algorithms Engineering with Computers 2003 19 2-3 191 202
- Kang S , Park D Application of computer-aided process planning system for non-axisymmetric deep drawing products J Mater Process Technol . 2002 124 1 36 48
- Li L , Fuh J , Zhang Y , Nee A Application of genetic algorithm to computer-aided process planning in distributed manufacturing environments Robot Comput Integrated Manuf . 2005 21 6 568 578
- Gupta D , Gopalakrishnan B Energy sensitive machining parameter optimisation International Journal of Industrial and Systems Engineering 2010 5 4 405 423
- Fuh J , Chang C , Melkanoff M A logic-based integrated manufacturing planning system Computers in Engineering 1992 1 391 391
- Tisza M Recent achievements in computer aided process planning and numerical modelling of sheet metal forming processes Journal of Achievements in Materials and Manufacturing Engineering 2007 24 1 435 442
- Kabir , Md Deloyer Jahan1 Golam Development of computer aided process planning (CAPP) for rotational parts 2010
- Leonesio M , Tosatti LM , Pellegrinelli S , Valente A An integrated approach to support the joint design of machine tools and process planning CIRP Journal of Manufacturing Science and Technology 2013 6 3 181 186
- Gopalakrishnan B , Pandiarajan V Materials and manufacturing processes selection system for product designs in concurrent engineering J Mater Process Technol . 1991 28 1 93 103
- Enache S , Strajescu E , Opran C , Minciu C , Zamfirache M Mathematical model for the establishment of the materials machinability CIRP Annals-Manufacturing Technology 1995 44 1 79 82
- Wang L Machine availability monitoring and machining process planning towards cloud manufacturing CIRP Journal of Manufacturing Science and Technology 2013 6 4 263 273
- Ciurana J , Garcia-Romeu M , Ferrer I , Casadesús M A model for integrating process planning and production planning and control in machining processes Robot Comput Integrated Manuf . 2008 24 4 532 544
- Wang L An overview of function block enabled adaptive process planning for machining J Manuf Syst . 2015 35 10 25
- Wang S , Lu X , Li X , Li W A systematic approach of process planning and scheduling optimization for sustainable machining J Clean Prod . 2015 87 914 929
- Veldhuis S , Dosbaeva G , Yamamoto K Tribological compatibility and improvement of machining productivity and surface integrity Tribol Int . 2009 42 6 1004 1010
- Kuttolamadom , M. , Hamzehlouia , S. , and Mears , L. Effect of Machining Feed on Surface Roughness in Cutting 6061 Aluminum SAE Int. J. Mater. Manuf. 3 1 108 119 2010 10.4271/2010-01-0218
- Raja SB , Baskar N Application of particle swarm optimization technique for achieving desired milled surface roughness in minimum machining time Expert Syst Appl . 2012 39 5 5982 5989
- Qehaja N , Jakupi K , Bunjaku A , Bruçi M , Osmani H Effect of machining parameters and machining time on surface roughness in dry turning process Procedia Engineering 2015 100 135 140
- Gopalakrishnan B Computer integrated machining parameter selection in a job shop using expert systems Journal of Mechanical Working Technology 1989 20 163 170
- Pamphlet A Logistics machining data Metcut Research Association Inc . 1966
- Machinability Data Center Machining data handbook 1 MDC 1980