Rediscovering scientific management. The evolution from industrial engineering to industrial data science

Authors

DOI:

https://doi.org/10.4995/ijpme.2022.16617

Keywords:

Scientific Management, Industrial Engineering, Industrial Data Science, Data Science, Data Analytics, Process Chain

Abstract

Industrial Engineering, through its role as design, planning and organizational body of the industrial production, has been crucial for the success of manufacturing companies for decades. The potential, expected over the course of Industry 4.0 and through the application of Data Analytic tools and methods, requires a coupling to established methods. This creates the necessity to extend the traditional job description of Industrial Engineering by new tools from the field of Data Analytics, namely Industrial Data Science. Originating from the historic pioneers of Industrial Engineering, it is evident that the basic principles will remain valuable. However, further development in view of the data analytic possibilities is already taking place. This paper reviews the origins of Industrial Engineering with reference to four pioneers, draws a connection to current day usage, and considers possibilities for future applications of Industrial Data Science.

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Author Biographies

Jochen Deuse, University of Technology Sydney; Technical University Dortmund

Prof. Dr.-Ing. Jochen Deuse, born 1967, is head of the Institute of Production Systems (IPS) at the TU Dortmund and professor at the University of Technology Sydney (UTS), Faculty of Engineering and Information Technology, School of Mechanical and Mechatronic Engineering, Centre for Advanced Manufacturing (CAM).

Nikolai West, Technical University Dortmund

Institute of Production Systems

Marius Syberg, Technical University Dortmund

Institute of Production Systems

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Published

2022-01-31

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