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Concurrent optimization of process parameters and product design variables for near net shape manufacturing processes

Author

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  • Daniele Marini

    (University of Strathclyde)

  • Jonathan R. Corney

    (University of Strathclyde)

Abstract

This paper presents a new systematic approach to the optimization of both design and manufacturing variables across a multi-step production process. The approach assumes a generic manufacturing process in which an initial near net shape (NNS) process is followed by a limited number of finishing operations. In this context the optimisation problem becomes a multi-variable problem in which the aim is to optimize by minimizing cost (or time) and improving technological performances (e.g. turning force). To enable such computation a methodology, named conditional design optimization (CoDeO) is proposed which allows the modelling and simultaneous optimization of process parameters and product design (geometric variables), using single or multi-criteria optimization strategies. After investigation of CoDeO’s requirements, evolutionary algorithms, in particular Genetic Algorithms, are identified as the most suitable for overall NNS manufacturing chain optimization The CoDeO methodology is tested using an industrial case study that details a process chain composed of casting and machining processes. For the specific case study presented the optimized process resulted in cost savings of 22% (corresponding to equivalent machining time savings) and a 10% component weight reduction.

Suggested Citation

  • Daniele Marini & Jonathan R. Corney, 2021. "Concurrent optimization of process parameters and product design variables for near net shape manufacturing processes," Journal of Intelligent Manufacturing, Springer, vol. 32(2), pages 611-631, February.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:2:d:10.1007_s10845-020-01593-y
    DOI: 10.1007/s10845-020-01593-y
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    References listed on IDEAS

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    1. Ullah Saif & Zailin Guan & Li Zhang & Fei Zhang & Baoxi Wang & Jahanzaib Mirza, 2019. "Multi-objective artificial bee colony algorithm for order oriented simultaneous sequencing and balancing of multi-mixed model assembly line," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1195-1220, March.
    2. Zhonglei Liu & Xuekun Li & Dingzhu Wu & Zhiqiang Qian & Pingfa Feng & Yiming Rong, 2019. "The development of a hybrid firefly algorithm for multi-pass grinding process optimization," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2457-2472, August.
    3. R. Venkata Rao & Dhiraj P. Rai & J. Balic, 2019. "Multi-objective optimization of abrasive waterjet machining process using Jaya algorithm and PROMETHEE Method," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2101-2127, June.
    4. Hao Liu & Yue Wang & Liangping Tu & Guiyan Ding & Yuhan Hu, 2019. "A modified particle swarm optimization for large-scale numerical optimizations and engineering design problems," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2407-2433, August.
    5. Nurezayana Zainal & Azlan Mohd Zain & Nor Haizan Mohamed Radzi & Muhamad Razib Othman, 2016. "Glowworm swarm optimization (GSO) for optimization of machining parameters," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 797-804, August.
    6. Albert Y. Ha & Evan L. Porteus, 1995. "Optimal Timing of Reviews in Concurrent Design for Manufacturability," Management Science, INFORMS, vol. 41(9), pages 1431-1447, September.
    7. Minghai Yuan & Hongyan Yu & Jinting Huang & Aimin Ji, 2019. "Reconfigurable assembly line balancing for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2391-2405, August.
    8. R. Venkata Rao & Dhiraj P. Rai & J. Balic, 2018. "Multi-objective optimization of machining and micro-machining processes using non-dominated sorting teaching–learning-based optimization algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1715-1737, December.
    9. Emel Kızılkaya Aydoğan & Yılmaz Delice & Uğur Özcan & Cevriye Gencer & Özkan Bali, 2019. "Balancing stochastic U-lines using particle swarm optimization," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 97-111, January.
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    Cited by:

    1. Mohd Bilal Naim Shaikh & Mohammed Ali & Umer Masood Chaudry & Muhammad Kashif Khan, 2024. "Metrics for Sustainability and Circular Economy Practices in Context to Modern Manufacturing Environment," Circular Economy and Sustainability, Springer, vol. 4(3), pages 2073-2091, September.

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