Intelligent scheduling in MES systems for Industry 4.0 - a systematic review of the scientific literature

One of the most important goals of factories and manufacturers is the development of new solutions to increase dynamism to better adapt to changing marketplaces. This is because there have been significant technological advancements in the manufacturing industry in recent years, and production plann...

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Bibliographic Details
Main Authors: Shakeri, Zohreh, Halawi-Ghoson, Nourhan, Hakam, Nisar, Talhi, Esma, Quenehen, Anthony, Benfriha, Khaled
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Decision making
Industry 4.0
Job shop scheduling
JSSP
Manufacturing industries
Production facilities
Production planning
Production systems
Service robots
Systematics
Online Access:Request full text
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Summary:One of the most important goals of factories and manufacturers is the development of new solutions to increase dynamism to better adapt to changing marketplaces. This is because there have been significant technological advancements in the manufacturing industry in recent years, and production planning is essential to ensure the completion of all production. Production Scheduling Due to the possibility of unpredictable events in the production system, problems related to scheduling problems are NP-hard and complex.This article aims to provide a systematic literature review on intelligent scheduling based on MES and in the framework of Industry 4.0. In a non-ideal situation, in complex, dynamic production systems, unpredictable disturbances can happen, including machine breakdowns, changes in the priority of orders, absence of personnel, etc. Production management has gained new opportunities in recent decades due to the growth of technologies such as artificial intelligence, the Internet of Things, big data, and data analytics. This study discovers an outstanding research topic with a high potential for further investigation through a comprehensive literature analysis of the pertinent domains.
ISSN:2835-2807
DOI:10.1109/MMAR58394.2023.10242514