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Open AccessJournal ArticleDOI

Review of job shop scheduling research and its new perspectives under Industry 4.0

TLDR
This paper explores the future research direction in SDS and discusses the new techniques for developing future new JSP scheduling models and constructing a framework on solving the JSP problem under Industry 4.0.
Abstract
Traditional job shop scheduling is concentrated on centralized scheduling or semi-distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and distributed manufacturing system supported by novel and emerging manufacturing technologies such as mass customization, Cyber-Physics Systems, Digital Twin, and SMAC (Social, Mobile, Analytics, Cloud). The scheduling research needs to shift its focus to smart distributed scheduling modeling and optimization. In order to transferring traditional scheduling into smart distributed scheduling (SDS), we aim to answer two questions: (1) what traditional scheduling methods and techniques can be combined and reused in SDS and (2) what are new methods and techniques required for SDS. In this paper, we first review existing researches from over 120 papers and answer the first question and then we explore a future research direction in SDS and discuss the new techniques for developing future new JSP scheduling models and constructing a framework on solving the JSP problem under Industry 4.0.

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Journal ArticleDOI

The future of manufacturing industry: a strategic roadmap toward Industry 4.0

TL;DR: In this paper, the authors conduct a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0.
Journal ArticleDOI

Industry 4.0, digitization, and opportunities for sustainability

TL;DR: In this paper, the authors present a systematic analysis of the sustainability functions of Industry 4.0, including energy sustainability, harmful emission reduction, and social welfare improvement, and show that sophisticated precedence relationships exist among various sustainability functions.
Journal ArticleDOI

Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0

TL;DR: The so-called “smartization” of manufacturing industries has been conceived as the fourth industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and progressive maturity of the global economy.
Journal ArticleDOI

The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review

TL;DR: In this paper, a plethora of digital technologies effecting on manufacturing enterprises is discussed. But the authors focus on the effects in the smart factory domain, focusing on the effect in the manufacturing domain.
References
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Tabu Search

TL;DR: This book explores the meta-heuristics approach called tabu search, which is dramatically changing the authors' ability to solve a host of problems that stretch over the realms of resource planning, telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics, pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservation and scores of other problems.
Journal ArticleDOI

Future paths for integer programming and links to artificial intelligence

TL;DR: Four key areas of Integer programming are examined from a framework that links the perspectives of artificial intelligence and operations research, and each has characteristics that appear usefully relevant to developments on the horizon.
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