Managing production systems with machine learning: a case analysis of Suzhou GCL photovoltaic technology

Abstract

Production control in the manufacturing industry involves complex circumstances and high demand for timeliness. Unlike traditional production control methods, the approach that integrates machine learning and industrial big data can enable manufacturing industries to dynamically adapt to the changing environment and respond in a timely manner to market changes due to production optimisation and improve economic benefits. In order to explore the relationship between production system optimisation and lean strategic planning based on machine learning and big data, the paper conducts an exploratory case analysis based on Suzhou GCL Photovoltaic Technology, a successful company in the photovoltaic industry in China. We sort and investigate the first-hand interview data and second-hand news and video data, and then use the qualitative research method. Based on the analysis and observation, we find that machine learning has a positive impact on quality management. Data, information, knowledge, intelligence collectively impact the performance of intelligence production systems. Our research provides valuable insights for practitioners to effectively accelerate the transformation to intelligent manufacturing.

Keywords:

• Intelligent manufacturing
• industrial big data
• production process
• knowledge management

Additional information

Funding

This research has been supported by the National Natural Science Foundation of China [71871172, Model of Risk knowledge acquisition and Platform governance in FinTech based on deep learning; 71571139, Outlier Analytics and Model of Outlier Knowledge Management in the context of Big Data]. We thank the management leaders for the case data from Suzhou GCL Photovoltaic Technology Co., Ltd. We deeply appreciate the suggestions from fellow members of Xia’s project team and Research center of Enterprise Decision Support, Key Research Institute of Humanities and Social Sciences in Universities of Hubei Province [DSS20180204].

Notes on contributors

Huosong Xia

Dr. Huosong Xia is a professor in the School of Management at Wuhan Textile University and was a visiting scholar at Eller College of Management of the University of Arizona from 2006 to 2007. He graduated from Huazhong University of Science and Technology of China. His main research interests include knowledge management, data mining, e-Commerce, and logistics information system. He has published more than 100 research papers in referred journals, book chapters, and conferences. He has obtained research funding from 4 projects with National Social Science Foundation of China and National Science Foundation of China.

Wuyue An

Wuyue An is a master candidate in the School of Management at Wuhan Textile University. She got her bachelor’s degree from the School of Software at Zhengzhou University. Her main research interests are knowledge management, data mining and, e-Commerce, and logistics information system.

Zuopeng (Justin) Zhang

Dr. Zuopeng (Justin) Zhang is a faculty member in the Coggin College of Business at University of North Florida. He was previously an Associate Professor of Information Systems and Analytics at State University of New York at Plattsburgh. He received his Ph.D. in Business Administration with a concentration on Management Science and Information Systems from Pennsylvania State University, University Park. His research interests include economics of information systems, knowledge management, electronic business, business process management, information security, and social networking. He is the editor-in-chief of the Journal of Global Information Management, an ABET program evaluator, and an IEEE senior member.

Genwang Liu

Genwang Liu is an undergraduate student in the College of Transportation Engineering at Tongji University, Shanghai, China. He is affiliated with the Key Laboratory of Road and Traffic Engineering of the Ministry of Education at Tongji University.