Automated task scheduling for automotive industry

R. Lewandowski, J. I. Olszewska

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

6 Citations (Scopus)
175 Downloads (Pure)


Nowadays, the automotive industry requires an increased use of intelligent systems to endure. In this paper, we present a new solution for automated task scheduling to help automotive industry in efficiently managing garage employees’ time and improving the effectiveness of the servicing and maintenance tasks of vehicles. The developed approach consists in a set of interconnected web applications with a model-view-controller based-on architecture and expert-knowledge temporal logic rules to automate the assignment of the daily workload for engineers working on multiple workstations within an automotive company. The proposed intelligent system prioritises and selects tasks for these engineers; the scheduled tasks being automatically ordered and displayed accordingly on screens visible in the related garage workstations. This automated task scheduling system has been successfully deployed within Arnold Clark Automobiles Ltd Company, and the performance of this new application used by a group of engineers under real-world operational conditions have been assessed and analysed.
Original languageEnglish
Title of host publication2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES)
Place of PublicationPiscataway, NJ
Number of pages6
ISBN (Electronic)9781728110592
Publication statusPublished - 27 Jul 2020
Event24th IEEE International Conference on Intelligent Engineering Systems 2020 - Online, Reykjavik, Iceland
Duration: 8 Jul 202010 Jul 2020

Publication series

NameIEEE Conference Proceedings
ISSN (Electronic)1543-9259


Conference24th IEEE International Conference on Intelligent Engineering Systems 2020
Abbreviated titleINES 2020


  • intelligent systems
  • industry 4.0 and smart factory
  • manufacturing-oriented data analytics
  • intelligent human-machine interaction
  • expert systems


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