WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 21, 2022
A Hybrid Method integrating Industry 4.0's Energy Digitization
Authors: ,
Abstract: Industrial firms must face important environmental challenges (greenhouse gas emissions, energy efficiency) and business imperatives. For this sector to accomplish a lower-cost energy transition, digitalization is a key lever. Today, the fourth industrial revolution is constructing a forward-thinking first industry known as industry 4.0, which combines many developing technologies to produce digital and efficient solutions. In this paper, we examine the impact of Industry 4.0 on the evolution of a new simulation modeling paradigm embodied by the concept of Digital Twin. To begin, we will discuss the industry 4.0 paradigm, its history, current state of development, and its impact on the development of the simulation modeling paradigm. A needs-based approach can result in the faster, deeper, and more extensive implementation of efficient systems. Furthermore, we present the methodology's multiple case studies and discuss several research and development projects involving the modeling of automated industrial processes that have been presented in recent scientific publications. The lack of tools, however, is not a problem because the current generation of general-purpose simulation modeling tools provides adequate integration options. However, to build on several physical levels of the integrated model system, close collaboration between academia and industrial partners is required to demonstrate industry and scientific community acceptance of the new analog modeling paradigm. Adoption and development of relevant morality in a needs-based process can lead to more efficient industrial automation implementation that is faster, deeper, and more extensive.
Search Articles
Keywords: Industry 4.0, Digital Twin, SME (Small and Medium-sized Enterprises), energy digitalized, simulation and modeling, automated modeling ICT: Information and communication technologies, OEMs: original equipment manufacturers, CPS: cyber-physical system, CPPS: physical production systems, DES: discrete event simulation, SQL: Structured Query Language, XML: Extensible Markup Language, ABM: Agent-Based Modeling, CMSD: Core Manufacturing Simulation Data, UML: Unified Modeling Language, MES: Manufacturing Execution System, ERP: Enterprise Resource Planning
Pages: 157-167
DOI: 10.37394/23202.2022.21.17