
Towards a Smart Manufacturing Maturity Assessment Framework: A Socio-Technical Perspective
Author(s) -
Lei Yue,
Pei Niu,
Yifang Fang,
Zhonghua Han
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1345/4/042063
Subject(s) - maturity (psychological) , capability maturity model , perspective (graphical) , relevance (law) , productivity , knowledge management , investment (military) , process management , smart manufacturing , return on investment , computer science , business , risk analysis (engineering) , engineering , production (economics) , manufacturing engineering , economics , psychology , developmental psychology , software , artificial intelligence , politics , political science , law , macroeconomics , programming language
Researchers of information technology (IT) have often suggested that there is no clear relevance between the IT investment and return on investment (ROI) of enterprises. This phenomenon is called “productivity paradox”. However, research on smart manufacturing capability maturity did not reflect empirically the fact that enterprises rarely benefit from information systems. Therefore, the aim of this article attempts to explore how humans and technologies are related and propose a smart manufacturing maturity assessment framework that can reveal the interaction between humans and technologies. This research addressed two questions, (a) what domains can be identified for smart manufacturing, and (b) how to harmonize all of the technical and social factors affecting maturity and benefits. A complicated concept “socio-technical system” was surveyed for interpreting how enterprises benefit from technologies. Results of this study showed a smart manufacturing maturity assessment framework from the socio-technical perspective. As an explanation, the understanding of manufacturing operations management (MOM) capability maturity model (CMM) within the framework in the case study and its results were presented. To conclude, this study may be regarded as a meta-model or reference model for specific maturity models, as well as has the merit of offering valuable insights into the maturity assessment.