Optimization of the tool selection based on big data. (2nd January 2017)

• Record Type: Journal Article
• Authors: Wang, Chao-Yu; Zhao, Wu; Liu, Qiao; Chen, Hua-Wei
• Is Part Of: Journal of discrete mathematical sciences & cryptography. Volume 20:Number 1(2017)
• Page Start: 341
• Page End: 360
• Publication Date: 2017-01-02
• Subjects: Tool selection -- Big data -- Optimization scheme -- Optimization algorithm; Computer science -- Mathematics -- Periodicals; Cryptography -- Periodicals; Computer science -- Mathematics; Cryptography; Periodicals; 004.0151
• DOI: 10.1080/09720529.2016.1183310
• Languages: English
• ISSNs: 0972-0529

Abstract

Abstract: A tool selection process and optimization method based on big data was proposed during the stage of tool selection in order to effectively utilize the production-process-data(PPD) to drive the selection of tools, and to improve the precision of tool selection .An intelligent tool selection model was built according to the mapping characteristics of PPD during the process of tool selection .On this basis, key influencing factors were analyzed and calculated, then the topological relationship among data was mined. According to the cosine similarity algorithm, optimization algorithm of tool selection was derived. By inputting the PPD as impact factor, outputting the tool selection importance value, this optimization algorithm can support the users to select tools. A tool selection optimization system was developed based on Java by using the intelligent tool selection model. The feasibility and effectiveness of the optimization method were verified by this system.