An approach based on timed Petri nets and tree encoding to implement search algorithms for a class of scheduling problems

Lefebvre, Dimitri; Basile, Francesco

doi:10.1016/j.ins.2020.12.087

Cited by 9 publications

(8 citation statements)

References 53 publications

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“…Thus, the computation SPE index is difficult in the KPCA method. Kim [ 31 ] and Lahdhiri [ 32 ] proposed a simple expression to calculate SPE in the feature space H, which is shown as follows:

where

is the matrix of the first

principal eigenvectors of

is the diagonal matrix of the first

eigenvalues of

[ 33 ], and

.…”

Section: Kernel Principal Component Analysis (Kpca)mentioning

confidence: 99%

Investigating Machine Learning and Control Theory Approaches for Process Fault Detection: A Comparative Study of KPCA and the Observer-Based Method

Lajmi

Mhamdi

Abdelbaki

et al. 2023

Sensors

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The paper focuses on the importance of prompt and efficient process fault detection in contemporary manufacturing industries, where product quality and safety protocols are critical. The study compares the efficiencies of two techniques for process fault detection: Kernel Principal Component Analysis (KPCA) and the observer method. Both techniques are applied to observe water volume variation within a hydraulic system comprising three tanks. PCA is an unsupervised learning technique used for dimensionality reduction and pattern recognition. It is an extension of Principal Component Analysis (PCA) that utilizes kernel functions to transform data into higher-dimensional spaces, where it becomes easier to separate classes or identify patterns. In this paper, KPCA is applied to detect faults in the hydraulic system by analyzing the variation in water volume. The observer method originates from control theory and is utilized to estimate the internal states of a system based on its output measurements. It is commonly used in control systems to estimate the unmeasurable or hidden states of a system, which is crucial for ensuring proper control and fault detection. In this study, the observer method is applied to the hydraulic system to estimate the water volume variations within the three tanks. The paper presents a comparative study of these two techniques applied to the hydraulic system. The results show that both KPCA and the observer method perform similarly in detecting faults within the system. This similarity in performance highlights the efficacy of these techniques and their potential adaptability in various fault diagnosis scenarios within modern manufacturing processes.

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“…Thus, the computation SPE index is difficult in the KPCA method. Kim [ 31 ] and Lahdhiri [ 32 ] proposed a simple expression to calculate SPE in the feature space H, which is shown as follows:

where

is the matrix of the first

principal eigenvectors of

is the diagonal matrix of the first

eigenvalues of

[ 33 ], and

.…”

Section: Kernel Principal Component Analysis (Kpca)mentioning

confidence: 99%

Investigating Machine Learning and Control Theory Approaches for Process Fault Detection: A Comparative Study of KPCA and the Observer-Based Method

Lajmi

Mhamdi

Abdelbaki

et al. 2023

Sensors

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“…This model combines a GA with local search (L-GA) and an optimal computing budget allocation (OCBA) is embedded into it. A class of timed Petri nets, namely, structured nets, has been proposed by Lefebvre and Basile (2021), along with tree encoding, which will help solve the scheduling problems. A metaheuristic based on a GA and integer linear program has been proposed by Dang et al (2021), claiming that it would yield a 20%-40% improvement compared with current practices.…”

Section: Research Front 1scheduling Problems In Flexible Manufacturin...mentioning

confidence: 99%

Mapping and visualizing flexible manufacturing system in business and management: a systematic review and future agenda

Priyadarshini¹,

Gupta²

2023

JM2

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Purpose A flexible manufacturing system (FMS) helps improve the system’s performance, thus increasing its overall competitiveness. FMS is an essential component of Industry 4.0 (I4.0), which has revolutionized the way firms manufacture their products. This study aims to investigate the diverse focus of the research being published over the years and the direction of scholarly work in applying FMSs in business and management. Design/methodology/approach A total of 1,096 bibliometric data were extracted from the Scopus database from the years 2001 to 2021. A systematic review and bibliometric analysis were performed on the data and related articles for performance measurement and scientific mapping on the FMS themes. Findings Based on co-keyword, the study reveals four major themes in the FMS field: mathematical models and quantitative techniques, scheduling and optimization techniques, cellular manufacturing and decision-making in FMSs. Based on bibliometric coupling on 2018–2021 bibliometric data, four themes emerged for future research: scheduling problems in FMS, manufacturing cell formation problem, interplay of FMS with other latest technologies and I4.0 and FMS. Originality/value The originality lies in answering the following research questions: What are the most highlighting themes in FMS, and how have they evolved over the past 20 years (2001–2021)? What topics have been at the forefront of research in FMS in the past five years (2016–2021)? What are the promising avenues of research in FMS?

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“…Its concentration affects the final product's quality. When deciding whether or not to approve the product, this index is taken into account [14].…”

Section: Description Of the Process To Be Modeledmentioning

confidence: 99%

“…Its concentration affects the final product's quality. When deciding whether or not to approve the product, this index is taken into account [14]. Through the two valves V1 and V2, two ingredients Q1 and Q2, respectively, in tanks R1 and R2 are discharged into the mixing tank.…”

Section: Description Of the Process To Be Modeledmentioning

confidence: 99%

Construction of a Dynamic Diagnostic Approach for a Fuzzy-Interval Petri Network

et al. 2023

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Fault diagnosis plays a crucial role in enhancing system dependability and minimizing potential catastrophic consequences for both equipment and human safety. This article presents a research study focused on developing a diagnosis and control approach for discrete event systems using the Petri net Fuzzy Interval (IFPN). The Petri net is utilized as a modeling tool for the target system. The paper describes a case study conducted on an ingredient mixing system, where the objective is to maintain the concentration of ingredients within a valid range. A diagnostic framework is constructed and successfully applied to identify faults in the system. The proposed approach is further validated through simulation tests conducted on a mixing system.

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An approach based on timed Petri nets and tree encoding to implement search algorithms for a class of scheduling problems

Cited by 9 publications

References 53 publications

Investigating Machine Learning and Control Theory Approaches for Process Fault Detection: A Comparative Study of KPCA and the Observer-Based Method

Investigating Machine Learning and Control Theory Approaches for Process Fault Detection: A Comparative Study of KPCA and the Observer-Based Method

Mapping and visualizing flexible manufacturing system in business and management: a systematic review and future agenda

Construction of a Dynamic Diagnostic Approach for a Fuzzy-Interval Petri Network

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