Knowledge and agent-based system for decentralised scheduling in manufacturing

Saeidlou, Salman; Saadat, Mozafar; Jules, Guiovanni

doi:10.1080/23311916.2019.1582309

Cited by 7 publications

(2 citation statements)

References 34 publications

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“…A central aspect of cloud manufacture architecture comprising the service layer is knowledgebased scheduling (Lu & Xu, 2017;Saeidlou et al, 2019a). Tools employed currently for rescheduling in the cloud include a database and system of data capture, and a form of multi-objective optimisation: Monte Carlo simulation (Bölöni & Turgut, 2017;Guo et al, 2015).…”

Section: Facilitating Cloud-based Scheduling For Manufacturingmentioning

confidence: 99%

Towards decentralised job shop scheduling as a web service

2021

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This paper aims to investigate the fundamental requirements for a cloudbased 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

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Section: Facilitating Cloud-based Scheduling For Manufacturingmentioning

confidence: 99%

Towards decentralised job shop scheduling as a web service

2021

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“…To aid in an environment that is dynamic and has multiple requirements, research has been made on the use Multi-Criteria Decision Making (MCDM) algorithms, aiding in the decision-making process [20][21] [22]. Furthermore, current trends on the theme, as shown by [23] [24], present the use of machine learning techniques and algorithms to solve multi-criteria problems. This happens due to the inherent ability of these methods to judge different alternatives through several criteria (attributes or requirements) to provide the most suitable alternative.…”

Section: Issues On Decision-making Process With Multiple Requirementsmentioning

confidence: 99%

An Analysis of Flexible Manufacturing on the Support of the Development of Smart Product-Service Systems

Leite¹,

Canciglieri²,

Szejka³

et al. 2020

IFIP Advances in Information and Communication Technology

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Currently, changes in the customer's mindset and increased flexibility in manufacturing shifted competition between companies to focus on the product's value rather than its cost. In this context, Product-Service Systems (PSSs) are an alternative to traditional value propositions (i.e. pure products, pure services) by combining services with products and providing an experience to customers. In recent decades, PSSs were expanded from solely business aspects to engineering aspects and technical considerations in their scope, such as the paradigms of Technical PSS, Industrial PSS, Digitalized PSS and Cyber-Physical PSS. More recently, due to the application of Industry 4.0 concepts, there is a significant increase of "smart technologies", i.e. sensors; connectivity; mobile application, in PSSs, naming it a new paradigm on the field, known as Smart PSSs. In this context, this research aims to explore and discuss current issues related to the integration of flexible manufacturing processes and Smart PSSs through a literature review and analysis, regarding information sharing, traceability and system reconfiguration based on customer's requirements. Found literature points to gaps in the theme related to semantic issues and design issues regarding the dynamic reconfiguration of the manufacturing process and the Smart PSS. The modern approaches to the theme, as found in literature, are still not able to cope with the semantic barriers and high volume of heterogeneous information in a holistic manner. Conclusions point that further investigation of the cited issues is required in a systematic manner, as well as the development of models that can cope with the presented issues.

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Final Remarks and Conclusion on AHP/ANP Inability for Solving Complex Scenarios

Munier¹,

Hontoria

2021

Management for Professionals

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Knowledge and agent-based system for decentralised scheduling in manufacturing

Cited by 7 publications

References 34 publications

Towards decentralised job shop scheduling as a web service

Towards decentralised job shop scheduling as a web service

An Analysis of Flexible Manufacturing on the Support of the Development of Smart Product-Service Systems

Final Remarks and Conclusion on AHP/ANP Inability for Solving Complex Scenarios

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