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Cutting process-based optimization model of machining feature for cloud manufacturing

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Abstract

Cloud manufacturing (CMfg), as a new service-oriented manufacturing paradigm, has experienced rapid development and has been paid wide attention all over the world in recent years. In order to realize the full-scale sharing, free circulation and transaction, and on-demand use of manufacturing resources and capabilities with making use of different kinds of cloud manufacturing service platforms in modern manufacturing enterprises, there are plenty of works that should be done; how to provide high-quality manufacturing service for consumers in cloud manufacturing system is a crucial issue. This paper presents the optimization approach of cutting process based on the analysis of the key factors of cutting process, e.g., surface integrity, tool failure, chip control, and cutting stability. Within this approach, the machining methods are determined first according to the machining features and the machining requirements. Then, the optimization model outputs the cutting tools, cutting parameters, and conditions under the boundary condition linking the user databases, cutting tool database, and machining condition database. Here, the databases related to cutting quality are utilized by the optimization algorithms, e.g., genetic algorithms (GA) and ant colony optimization. A cutting parameter optimization is as an example shown by a GA approach. Finally, a prototype of the system is developed to implement the optimization approach.

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Authors and Affiliations

  1. The Key Lab of National and Local United Engineering for High-Efficiency Cutting and Tools, Harbin University of Science and Technology, Harbin, 150080, China

    Mingyang Wu, Tingyu Huo & Jianghua Ge

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  1. Mingyang Wu
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  2. Tingyu Huo
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  3. Jianghua Ge
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Correspondence to Mingyang Wu.

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Wu, M., Huo, T. & Ge, J. Cutting process-based optimization model of machining feature for cloud manufacturing. Int J Adv Manuf Technol 84, 327–334 (2016). https://doi.org/10.1007/s00170-015-7800-0

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  • DOI: https://doi.org/10.1007/s00170-015-7800-0

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