Publications Repository - Gdańsk University of Technology

Knowledge-based support has become an indispensable part not only to the traditional manufacturing set-ups but also to the new fast-emerging Industry 4.0 scenario. In this regard, successful research has been performed and extensively reported to develop Decisional DNA based knowledge representation models of engineering object and engineering process called Virtual engineering object (VEO), Virtual engineering process (VEP) and Virtual engineering factory (VEF). These models are the virtual representation of manufacturing resources, and with the help of IoT, are capable of capturing the past experience and formal decisions. In this chapter, a complete virtual manufacturing environment is summarized. Furthermore, the scope of this work is explained in the Cyber-Physical Systems (CPS) based Industry 4.0 framework. Four case studies are presented to validate the practical implementation of the proposed concept. In the first case the idea of VEO-VEP-VEF is applied to design an intelligent factory framework to achieve contextual information through real-time visualization. In the second study, the smart tool performance analysis is presented in which data of key tool parameters like tool life, surface integrity, tool forces, and chip formation can be sensed in real-time; also predictions can be made according to the specific requirements. In the third case study, the technique of Decisional DNA (DDNA) is applied to FMS to develop a generic model to achieve effective scheduling and manufacturing flexibility. In the last study, the framework to manage the storage, analysis, and processing of data, information, and knowledge of a typical CIM is presented. The benefits of this approach are manifold as it creates manufacturing DNA of a factory, felicitates in effective decision making, increases the rate of production, reduces errors and production waste, and streamlines manufacturing sub-systems. Moreover, and can be instrumental in designing Industry 4.0.

Authors

• Imran Shafiq,
• Cesar Sanin,
• prof. dr hab. inż. Edward Szczerbicki link open in new tab