CLAug 2, 2022

MBSE analysis for energy sustainability improvement in manufacturing industry

arXiv:2208.01514v13 citationsh-index: 19
Originality Synthesis-oriented
AI Analysis

This addresses energy sustainability challenges for manufacturing industries, but it appears incremental as it applies existing MBSE methods to a specific domain without claiming major breakthroughs.

The paper tackles the complexity of energy management in Industry 4.0 by proposing a Model-Based Systems Engineering approach to develop an autonomous Energy Management System for manufacturing, implemented using SysML to enable continuous improvement in assessing, predicting, and acting on energy sustainability.

With the ever increasing complexity of Industry 4.0 systems, plant energy management systems developed to improve energy sustainability become equally complex. Based on a Model-Based Systems Engineering analysis, this paper aims to provide a general approach to perform holistic development of an autonomous energy management system for manufacturing industries. This Energy Management System (EMS) will be capable of continuously improving its ability to assess, predict, and act, in order to improve by monitoring and controlling the energy sustainability of manufacturing systems. The approach was implemented with the System Modeling Language (SysML).

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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