Document Type



There has been a paradigmatic shift in manufacturing as computing has transitioned from the programmable to the cognitive computing era. In this paper we present a theoretical framework for understanding this paradigmatic shift in manufacturing and the fast evolving role of artificial intelligence. Policy, Strategic and Operational implications are discussed. Implications for the future of strategy and operations in manufacturing are also discussed. Future research directions are presented.


Artificial Intelligence and Robotics | Business Administration, Management, and Operations | Manufacturing | Operations and Supply Chain Management


Description of Data File:


The data file is a list of references to articles in the Web of Science database for search results combining terms from the domains of machine learning (machine learning, deep learning, Artificial Intelligence, and neural networks) and manufacturing (manufacturing, production, maintenance and quality control). This list consists of 250 articles which have been arrived at after selecting the most relevant articles from a pre-final list of 1843 articles.

Relation to Project:

Out of the 250 papers in this list, 139 have been cited in our paper. However, it was not possible to cite all of the papers. The purpose of this list is to provide a full list of the articles that we closely reviewed as part of our literature review of research at the confluence of artificial intelligence and manufacturing.


In the course of this research, the title has been updated; previously the project was referred to as "Interpretive Model of Manufacturing: A Review of Machine Learning in Manufacturing"


report: 10.22237/waynestaterepo/business_frp/1592438460 Data File: 10.22237/waynestaterepo/business_frp/1592438400

Sharma_MLinManufacturing.pdf (129 kB)
Full listing of articles reviewed/cited in the paper: first update.