传统制造业精益数字化水平评估方法

立足智能制造背景,在解析精益数字化内涵和已有相关研究的基础上,围绕"人机料法环",立足于投入-过程-产出的企业生产运作过程系统地提取精益数字化驱动因素,构建包含数字化的人员素质培养、基础设施建设、制度建设、信息利用、物流-供应链智能一体化、生产改进、产品和生产绿色化等8个子系统的企业精益数字化水平评估指标体系并确定指标评估标准。在此基础上,应用直觉模糊熵和模糊集对分析法构建评估模型,并以某A传统制造业企业为例进行案例分析。研究结果表明:运用上述方法的评估结果与案例企业现实情况基本吻合,较为科学地反映了企业精益数字化推进水平和转型短板,其中基础设施配备、数字化技术或精益文化员工培训、数字信息安全管理、数字信息双向传递、数据分析、车间物流准确配送、供应链协同、生产信息流畅通及生产柔性化等9个方面是企业推进精益数字化的关键所在。期望为传统制造业智能转型顺利推进和精益数字化水平科学评估提供一定的决策依据和理论支持。

Evaluation Method of Lean Digitalization Level for Traditional Manufacturing

Based on the background of intelligent manufacturing,this paper analyzes the connotation of lean digitalization and existing related research,focuses on the"man,machine,material,method,environments",and systematically extracts the driving factors of lean digitalization according to the production operation process which is composed of input-process–output,constructs the evaluation index system of lean digital level of enterprise and confirms the index evaluation criteria,which including personnel quality training,infrastructure construction,system construction,information utilization,logistics and supply chain intelligent integration,production improvement,products and green production.Based on this,the paper uses intuitionistic fuzzy entropy and fuzzy set pair analysis method to construct evaluation model,and takes A company of a traditional manufacturing enterprise as an example to carry on the case analysis.The results show that evaluation results using the above methods are basically consistent with the actual situation of A company,and more scientifically reflect the enterprise lean digitization advancement level and the transformation short board,among them,infrastructure equipment,digital technology or lean culture training for employee,security management of digital information,two-way transmission of digital information,data analysis,accurate distribution of workshop logistics,supply chain coordination,smooth production information,and production flexibility are the key to the promotion of lean digitalization.The research is expected to provide a certain decisionmaking basis and theoretical support for the smooth advancement of intelligent transformation and scientific evaluation of lean digitalization level for the traditional manufacturing industry.