Mining big data in manufacturing: Requirement analysis, tools and techniques

Utpal Roy, Bicheng Zhu, Yunpeng Li, Heng Zhang, Omer Yaman

Research output: Contribution to conferencePaper

2 Scopus citations

Abstract

Data Mining has tremendous potential and usefulness in improving the effectiveness of decision-making in manufacturing. Tools and techniques of data mining can be intelligently applied from product design analysis to the product repair and maintenance. Vast amount of data in the form of documents (text), graphical formats (CAD-file), audio/video, numbers, figures and/or hypertext are available in any typical manufacturing system. Our ultimate goal is to develop data-driven methodologies to solve manufacturing problems using data mining techniques. As a precursor, based on a literature study, this paper investigates selective manufacturing areas to identify the requirements for applying data mining techniques in solving potential manufacturing problems. The reviewed manufacturing areas are: (i) the "Design Intent" retrieval process for the product design and manufacturing, (ii) selection of materials, (iii) performance evaluations of manufacturing process design and operation management, and (iv) product inspection, and after-sales services (repair and maintenance). Industrial efforts towards addressing "Big Data" issues have also been briefly narrated in this paper. Lastly, the paper discusses two important data-related issues that may affect any applications of the data mining tools and techniques - (i) uncertainty involved in data collection, and (ii) interoperability of data collected at different levels of an enterprise.

Original languageEnglish (US)
DOIs
StatePublished - Jan 1 2014
EventASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014 - Montreal, Canada
Duration: Nov 14 2014Nov 20 2014

Other

OtherASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014
CountryCanada
CityMontreal
Period11/14/1411/20/14

Keywords

  • Big data
  • Data analytics
  • Data Mining
  • Knowledge discovery
  • Mining in manufacturing
  • Requirement analysis

ASJC Scopus subject areas

  • Mechanical Engineering

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  • Cite this

    Roy, U., Zhu, B., Li, Y., Zhang, H., & Yaman, O. (2014). Mining big data in manufacturing: Requirement analysis, tools and techniques. Paper presented at ASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014, Montreal, Canada. https://doi.org/10.1115/IMECE2014-38822