Manufacturing Data Analysis in Internet of Things/Internet of Data (IoT/IoD) Scenario

TLDR

Computer integrated manufacturing can boost production speed, reduce errors, and cut waste, but operating in IoT/IoD environments introduces the challenge of managing massive data flows between CIM components. This paper proposes a decisional DNA‑based knowledge representation framework to store, analyze, and process data, information, and knowledge within a typical CIM. The framework employs virtual engineering objects and processes to build knowledge models for components such as automated storage systems, guided vehicles, robots, and CNC machines. The resulting model captures real‑time manufacturing data at object, process, and factory levels, enabling decision‑making and rendering the CIM system intelligent for virtual Industry 4.0 operation.

Abstract

Computer integrated manufacturing (CIM) has enormous benefits as it increases the rate of production, reduces errors and production waste, and streamlines manufacturing sub-systems. However, there are some new challenges related to CIM operating in the Internet of Things/Internet of Data (IoT/IoD) scenarios associated with Industry 4.0 and cyber-physical systems. The main challenge is to deal with the massive volume of data flowing between various CIM components functioning in virtual settings of IoT. This paper proposes decisional DNA-based knowledge representation framework to manage the storage, analysis, and processing of data, information, and knowledge of a typical CIM. The framework utilizes the concept of virtual engineering object and virtual engineering process for developing knowledge models of various CIM components such as automatic storage and retrieval systems, automatic guided vehicles, robots, and numerically controlled machines. The proposed model is capable of capturing in real time the manufacturing data, information and knowledge at every stage of production, that is, at the object level, the process level, and at the factory level. The significance of this study is that it will support decision-making by reusing the experience, which will not only help in effective real-time data monitoring and processing, but also make CIM system intelligent and ready to function in the virtual Industry 4.0 environment.