面向现场工程师培养的人本学习工厂构建
On the Construction of a Human-Centered Learning Factory for the Training of Field Engineers
余越凡 1赵志群1
作者信息
摘要
在"人民至上"的中国式现代化背景下,高质量的现场工程师培养是推动制造业转型升级、增进人民福祉的重要一环,但目前尚缺乏与之相适配的学习环境与路径支持.本文基于现场工程师的工作特征与产业发展的时代要求,剖析现场工程师培养的基本条件,并提出兼具"人本智造"和"人本智学"特征的"人本学习工厂"概念."人本学习工厂"构建应从物理系统、信息系统和社会系统三个逻辑层次进行结构化设计,分别支持人在回路里、人在回路上和人在回路外的学习.建立"人本学习工厂",一要建设协同高效的产教融合体系,形塑系统性生产环境;二要坚持"人民至上"的发展理念,形塑人本化决策共识;三要发展情境感知诊断技术,形塑能力本位智能学习样态.
Abstract
Under the Chinese path to modernization that puts people in the first place,the cultivation of high-quality field engineers is a crucial aspect in promoting the transformation and upgrading of manufacturing industries and enhancing people's well-being,but there is a lack of appropriate learning environments and path support.Based on the work characteristics of field engineers and the era re-quirements of industrial development,this article analyzes the basic conditions for the cultivation of field engineers,and puts forward the concept of"Human-Centered Learning Factory"which is charac-terized by the features of"human-centered intelligent manufacturing"and"human-centered intelligent learning".The construction of"Human-centered Learning Factory"should be structured at three logi-cal levels:the physical system,the information system,and the social system,to support human-in-the-loop,human-on-the-loop,and human-out-of-the-loop learning,respectively.To establish"Hu-man-centered Learning Factory",it is necessary,firstly,to build a synergistic and efficient industry-education fusion system and shape a systematic production environment;secondly,to adhere to the development concept of"people first"and shape a consensus on human-centered decision-making;thirdly,to develop context-aware diagnostic technology and shape a competence-based intelligent learning pattern.
关键词
现场工程师/人本学习工厂/学习环境/人机协同学习/人本智造/制造业转型升级Key words
field engineer/human-centered learning factory/learning environment/human-machine col-laborative learning/human-centered intelligent manufacturing/transformation and upgrading of manu-facturing industry引用本文复制引用
出版年
2025
NETL
NSTL
万方数据