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Theoretical Results on Single Machine Scheduling to Minimize the Number of Tardy Jobs with Periodic Maintenance

  • Feifeng Zheng
  • , Zhaojie Wang
  • , Ming Liu
  • , Yinfeng Xu
  • , Feng Chu
  • Donghua University
  • Tongji University
  • Université Paris-Saclay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In the last two decades, maintenance as an essential method to prevent machine breakdown has achieved undoubted importance in process industries and manufacturing systems. With ever increasing high-quality products demand, the number of tool change or machine maintenance become quite remarkable. Besides, industry 4.0 supports manufacturing enterprises to explore more efficient and intelligent scheduling modes. Machine periodic maintenance has a significant impact on the scheduling of many manufacturing companies, it therefore has become one of the factors they must consider. Despite this, theoretical analysis for the machine scheduling problem with periodic maintenance has not received considerable critical attention in previous studies. Motivated by scheduling practice, this work revisits a single machine scheduling problem with periodic maintenance to minimize the number of tardy jobs. First, a polynomial-time solvable case is identified. Then we propose a dynamic programming algorithm to solve the general case. At last, the non-approximability is proven.

Original languageEnglish
Title of host publicationICNSC 2021 - 18th IEEE International Conference on Networking, Sensing and Control
Subtitle of host publicationIndustry 4.0 and AI
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665440486
DOIs
StatePublished - 2021
Externally publishedYes
Event18th IEEE International Conference on Networking, Sensing and Control, ICNSC 2021 - Xiamen, China
Duration: 3 Dec 20215 Dec 2021

Publication series

NameICNSC 2021 - 18th IEEE International Conference on Networking, Sensing and Control: Industry 4.0 and AI

Conference

Conference18th IEEE International Conference on Networking, Sensing and Control, ICNSC 2021
Country/TerritoryChina
CityXiamen
Period3/12/215/12/21

Keywords

  • number of tardy jobs
  • periodic maintenance
  • scheduling
  • single machine

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