Using Analytic Hierarchical Process for Scheduling Problems Based on Smart Lots and Their Quality Prediction Capability

Zimmermann, Emmanuel; El-Haouzi, Hind Bril; Thomas, Philippe; Pannequin, Rémi; Noyel, Mélanie

doi:10.1007/978-3-030-03003-2_26

Cited by 2 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The collaboration mechanism between Intelligent Products can also be formalized using Multi-criteria Decision Making (MCDM) techniques. In [10], [14], the collaboration mechanism is based on the AHP/ANP (Analytic Hierarchy Process / Analytic Network Process).…”

Section: 1mentioning

confidence: 99%

Intelligent Products through SOHOMA Prism

Derigent

McFarlane

El-Haouzi

2021

Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future

View full text Add to dashboard Cite

In the framework of the SOHOMA 2020 special session "SOHOMA 10 th -year anniversary", this paper aims to make a review of the evolution of one important concept studied in the SOHOMA community, namely the Intelligent Product concept. This paper is not review of Intelligent Products -there are several of these already -but rather examines the history of the development of this concept through the 1 st to 9 th editions of SOHOMA, while also proposing future developments on this concept.

show abstract

Section: 1mentioning

confidence: 99%

Intelligent Products through SOHOMA Prism

Derigent

McFarlane

El-Haouzi

2021

Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future

View full text Add to dashboard Cite

show abstract

“…The proposed hybrid control system was designed with the aim of reducing the non-quality while limiting the consumption of raw materials. To ensure this objective, Zimmermann et al (2018) proposed a hybrid manufacturing system that combines a smart batches-based distributed control system and centralized schedule optimization. Consequently, the proposal here is to embed the batches (minimal product agent entities) with their own instance of the NN quality prediction model, to trigger it before setting up a batch on the workstation.…”

Section: Propositionmentioning

confidence: 99%

“…5. Flow in a stable environment (Zimmermann et al, 2018) Before entering the lacquering robot, batch B1 in q5 launches the computation of its embedded NN to determine its non-quality risk. If the risk is higher than the threshold of 25%, as established in Section 3, the AHP-based application is recalled, addressing the procedure for selecting the best replacement.…”

Section: Validation Approachmentioning

confidence: 99%

“…6. Flow in case of non-quality risk detection (Zimmermann et al, 2018) The variables of this new model are listed below, and Table 7 presents a summary of their numerical values. o Variables related to production range:…”

Section: Validation Approachmentioning

confidence: 99%

“…Further, a hybrid control system is proposed in this paper, coupling predictive scheduling and a proactive multicriteria decision method focused, in particular, on non-quality production risk. This is an extension of the work of Zimmermann et al (2018) with significant improvements in problem modeling and including the presentation of a statistical study evaluating social myopia (number of active/smart batches in the decision-making process). This evaluation approach can be used to identify the optimal number of smart batches that provides a good trade-off between algorithm performance and results quality.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multicriteria decision-making method for scheduling problem based on smart batches and their quality prediction capability

Zimmermann

Mezgebe

Haouzi

et al. 2021

Computers in Industry

Self Cite

View full text Add to dashboard Cite

The scheduling problem in manufacturing companies with high rework rates remains a complex research area to date. This paper presents a new approach for manufacturing scheduling that combines a predictive schedule with a proactive multicriteria decision-making method based on smart batches and their quality prediction capability. Each batch embeds an algorithm that allows it to predict its quality out of the next workstation. As soon as a batch determines that its process is too hazardous, a collaborative rescheduling decision, using the analytic hierarchy process (AHP), is initiated with its peer. This article details the proposed approach along with the AHP structure and presents the considered decision problem. A simulation model inspired by a lacquering-robot case study is described to validate this proposition. Then, the results of different scenarios are presented and discussed, highlighting the impact of social myopia on smart batches.

show abstract

Using Analytic Hierarchical Process for Scheduling Problems Based on Smart Lots and Their Quality Prediction Capability

Cited by 2 publications

References 12 publications

Intelligent Products through SOHOMA Prism

Intelligent Products through SOHOMA Prism

Multicriteria decision-making method for scheduling problem based on smart batches and their quality prediction capability

Contact Info

Product

Resources

About