Abstract
This paper aims to investigate the fundamental requirements for a cloud-based scheduling service for manufacturing, notably manufacturer priority to scheduling service, resolution of schedule conflict, and error-proof data entry. A flow chart of an inference-based system for manufacturing scheduling is proposed and a prototype was designed using semantic web technologies. An adapted version of the Muth and Thompson 10 × 10 scheduling problem (MT10) was used as a case study and two manufacturing companies represented our use cases. Using Microsoft Project, levelled manufacturer operation plans were generated. Semantic rules were proposed for constraints calculation, scheduling and verification. Pellet semantic reasoner was used to apply those rules onto the case study. The results include two main findings. First, our system effectively detected conflicts when subjected to four types of disturbances. Secondly, suggestions of conflict resolutions were effective when implemented albeit they were not efficient. Consequently, our two hypotheses were accepted which gave merit for future works intended to develop scheduling as a web service. Future works will include three phases: (1) migration of our system to a graph database server, (2) a multi-agent system to automate conflict resolution and data entry, and (3) an optimisation mechanism for manufacturer prioritisation to scheduling services.
Original language | English |
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Article number | 1938795 |
Number of pages | 26 |
Journal | Cogent Engineering |
Volume | 8 |
Issue number | 1 |
DOIs | |
Publication status | Published - 22 Jun 2021 |
Bibliographical note
Funding Information:The authors received no direct funding for this research. The authors would like to show our gratitude to GFM S.r.l. and Mapna (TUGA) P.J.S. for supplying the use case data for this research paper.
Publisher Copyright:
© 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
Keywords
- Ontology
- conflict resolution
- disturbance
- graph database
- inference
- multi-agent system
- semantic web
ASJC Scopus subject areas
- Computer Science(all)
- Chemical Engineering(all)
- Engineering(all)