Managing production systems with machine learning: a case analysis of Suzhou GCL photovoltaic technology
通过对苏州协鑫光伏的案例分析，研究了基于机器学习和工业大数据优化生产系统与精益战略规划的关系，发现机器学习对质量管理有积极影响，为制造业智能化转型提供参考。
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.