An ontology-based multi-criteria decision support system to reconfigure manufacturing systems

Abstract

There is extensive literature on the reconfiguration of manufacturing systems; however, there are only a few decision support approaches that allow full advantage to be taken of the flexibilities introduced by this paradigm. Existing approaches do not consider expert knowledge to deal with new occurrences of similar, previously encountered disturbances. Most approaches are preventive and off-line planning and scheduling approaches, thus missing updated accurate data about plant activities that may trigger reconfiguration decisions and make such decisions worth consideration. In this article, we design a decision support system to suggest candidate configurations and select a suitable configuration considering a knowledge-based multi-criteria decision making approach. Expert knowledge is captured using an ontology, which is used both to monitor the manufacturing system and to make configuration recommendations. A multi-criteria decision-making approach based on TOPSIS relies on the recommended configurations to select a suitable configuration. An industrial case study shows how the suggested approach can be used to reconfigure the system at the execution stage to cope with disturbances in a reactive manner.

Keywords:

• Reconfiguration
• decision support system
• ontology
• multi-criteria decision-making
• TOPSIS

Acknowledgment

The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through Research Group No (RG-1439-56).

Additional information

Funding

This research was funded by the Deanship of Scientific Research at King Saud University through research group No (RG-1439-56).

Notes on contributors

Mohammed M. Mabkhot

Mohammed M. Mabkhot has a B.Sc. degree in industrial engineering from King Khalid University, Abha, KSA. He has an M.Sc. degree in industrial engineering from King Saud University, Riyadh, KSA, which is one of the Middle-East top universities of Engineering Research and Education. Currently, he is a Ph.D. candidate in industrial engineering at King Saud University. His research interests focus on distributed control of manufacturing and cyber-physical systems using artificial intelligence. Mabkhot is exploring the use of distributed artificial intelligence (multi-agent, bio-inspired systems) and knowledge based systems to monitor and control disruptions and risks in manufacturing and cyber-physical systems. Mabkhot is participating in several funded research projects in industry 4.0, smart manufacturing and human-machine interaction.

Sana Kouki Amri

Dr. Sana Kouki Amri has B.Sc. and M.Sc. degrees in industrial engineering, and a Ph.D. degree in computer engineering from the National Institute of Applied Sciences and Technology (Institut National des Sciences Appliquées et de Technologie, INSAT), which is one of Tunisia’s renowned universities of Engineering Education and Research. Her expertise areas are related to quality engineering in manufacturing and service systems, with emphasis on integrated quality management systems, industrial information systems, and lean management. Her research interests focus on the design, monitoring and control of manufacturing systems using artificial intelligence, with particular emphasis on knowledge-based systems for requirements engineering.

Saber Darmoul

Dr. Saber Darmoul has B.Eng. and M.Sc. degrees in automation and control engineering with highest distinction from the National Institute of Applied Sciences and Technology (Institut National des Sciences Appliquées et de Technologie, INSAT), which is one of Tunisia’s renowned universities of Engineering Education. He has a Ph.D. degree in computer engineering from Université Clermont Auvergne (formerly known as Université Blaise Pascal), France. Currently, he is Professor of Industrial Engineering at Ecole Centrale Casablanca, Morocco, which is member of the international network of French Ecole Centrale (Groupe Ecole Centrale, GEC), with campuses in France, China, India, and Morocco. His expertise areas are related to systems engineering, with emphasis on system design, performance optimization, industrial information systems, and production planning, monitoring and control. His research interests focus on distributed control of manufacturing, service, and cyber-physical systems using artificial intelligence. Dr. Darmoul is exploring the use of distributed artificial intelligence (multi-agent, holonic and bionic/bio-inspired systems) to monitor and control disruptions and risks in manufacturing, service and cyber-physical systems. Applications include Intelligent Manufacturing Systems, and Intelligent Transportation Systems (ITS). Dr. Darmoul is leading several funded research projects in industry 4.0 and smart manufacturing, transportation and traffic engineering, human machine interaction and virtual reality.

Ali M. Al-Samhan

Prof. Ali M. Al-Samhan has a B.Sc. and M.Sc. degrees in industrial engineering from King Saud University, Riyadh, KSA. He obtained his Ph.D. from the School of Manufacturing and Mechanical Engineering, Birmingham University, United Kingdom. Currently, he is a Full Professor and Chairman of the Industrial Engineering Department, King Saud University. Prof. Al-Samhan served as a vice dean of scientific research at King Saud University. He is serving as a consultant for leading manufacturers in Saudi Arabia and member of SASO committee for industrial standardization. His research interests focus on engineering materials and manufacturing processes, monitoring and control of manufacturing systems using artificial intelligence, product design and development, automation and mechatronics, and biomechanical engineering. Prof. Al-Samhan has many registered patents and published papers in leading journals of Industrial and Manufacturing Engineering. He is leading a number of projects in industry 4.0 and smart manufacturing funded from different organizations in Saudi Arabia. [CrossRef]

Sabeur Elkosantini

Dr. Sabeur Elkosantini obtained his Ph.D. in computer science from Blaise Pascal University (France) and his M. Sc. in computer science from University of Lyon 2 (France). His research interests are related to: 1) Development of new AI approaches for the reactive decision making in manufacturing and transportation systems; and 2) discrete event simulation. He is involved in several research projects funded by CNRS (France), Tunisian ministry of high education (Tunisia) and KACST (KSA).