Ma Jing, Wang Qiang, Zhao Zhibiao
Department of Industrial Engineering, Tsinghua University, Beijing 100084, China.
China Norinco Group Planning and Research Institute, Beijing 100053, China.
Sensors (Basel). 2017 Jun 28;17(7):1500. doi: 10.3390/s17071500.
In the context of Industry 4.0, the demand for the mass production of highly customized products will lead to complex products and an increasing demand for production system flexibility. Simply implementing lean production-based human-centered production or high automation to improve system flexibility is insufficient. Currently, lean automation (Jidoka) that utilizes cyber-physical systems (CPS) is considered a cost-efficient and effective approach for improving system flexibility under shrinking global economic conditions. Therefore, a smart lean automation engine enabled by CPS technologies (SLAE-CPS), which is based on an analysis of Jidoka functions and the smart capacity of CPS technologies, is proposed in this study to provide an integrated and standardized approach to design and implement a CPS-based smart Jidoka system. A set of comprehensive architecture and standardized key technologies should be presented to achieve the above-mentioned goal. Therefore, a distributed architecture that joins service-oriented architecture, agent, function block (FB), cloud, and Internet of things is proposed to support the flexible configuration, deployment, and performance of SLAE-CPS. Then, several standardized key techniques are proposed under this architecture. The first one is for converting heterogeneous physical data into uniform services for subsequent abnormality analysis and detection. The second one is a set of Jidoka scene rules, which is abstracted based on the analysis of the operator, machine, material, quality, and other factors in different time dimensions. These Jidoka rules can support executive FBs in performing different Jidoka functions. Finally, supported by the integrated and standardized approach of our proposed engine, a case study is conducted to verify the current research results. The proposed SLAE-CPS can serve as an important reference value for combining the benefits of innovative technology and proper methodology.
在工业4.0的背景下，对大规模生产高度定制化产品的需求将导致产品复杂化，对生产系统灵活性的需求也与日俱增。单纯实施基于精益生产的以人为本的生产方式或高度自动化以提高系统灵活性是不够的。当前，利用信息物理系统（CPS）的精益自动化（自働化）被认为是在全球经济萎缩的情况下提高系统灵活性的一种经济高效的方法。因此，本研究提出了一种基于CPS技术的智能精益自动化引擎（SLAE-CPS），该引擎基于对自働化功能和CPS技术智能能力的分析，旨在提供一种集成化、标准化的方法来设计和实现基于CPS的智能自働化系统。应提出一套全面的架构和标准化的关键技术以实现上述目标。因此，提出了一种将面向服务的架构、代理、功能块（FB）、云及物联网相结合的分布式架构，以支持SLAE-CPS的灵活配置、部署和性能。然后，在该架构下提出了几种标准化的关键技术。第一种技术是将异构物理数据转换为统一服务，以便后续进行异常分析和检测。第二种技术是一组自働化场景规则，该规则基于对不同时间维度下的操作员、机器、物料、质量等因素的分析而抽象得出。这些自働化规则可支持执行功能块执行不同的自働化功能。最后，在所提出的引擎的集成化、标准化方法的支持下，进行了案例研究以验证当前的研究成果。所提出的SLAE-CPS可为结合创新技术和适当方法的优势提供重要的参考价值。
