A NOVEL PRODUCTION PROCESS MODELING FOR ANALYTICS

Authors

  • Rich Lee
  • Ing-Yi Chen

Keywords:

Smart Factory, Production Modeling, Business Analytics, Knowledge Management, Process Modeling

Abstract

Nowadays the manufacturing is facing the critical challenges from various aspects including
the trend of moving towards the new era of Industrial 4.0 [1]—an analytical and predictive driven production
thinking, the Smart Factory. To effectively embed the necessary processes for analytics, a new way of
modeling the process flows is essential to realize the goal of the predictive lean production. To reach these
objectives, this paper presents a novel process modeling approach for analytics which is vital to the
practitioners and the industries. The analysis of the smart factory theme includes the statistics, the data
mining, and the operation research approaches [2] based on the various management improvements or the
prediction objectives. The proposed process modeling for analytics extends the XML (eXtensible Markup
Language), which is also commonly used in software engineering [3]. The purpose of using this is to
streamline the latter integration with the analytical processes among the software systems and will play a key
part of the factory knowledge management for continuous optimization.

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Published

2017-04-12

How to Cite

Rich Lee, & Ing-Yi Chen. (2017). A NOVEL PRODUCTION PROCESS MODELING FOR ANALYTICS. GEOMATE Journal, 11(24), 2370–2377. Retrieved from https://geomatejournal.com/geomate/article/view/2078

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