A Framework Based on Predictive Maintenance, Zero-Defect Manufacturing and Scheduling Under Uncertainty Tools, to Optimize Production Capacities of High-End Quality Products

Dreyfus, Paul-Arthur; Kyritsis, Dimitrios C.

doi:10.1007/978-3-319-99707-0_37

Cited by 15 publications

(9 citation statements)

References 9 publications

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“…Finally, the VM output is composed of a quality estimation and a drift detection alarm, which are used by two main applications: First, the SDS, presented in Section 4.4, optimises the product measurement rate; then, the production machine can be controlled based on the quality estimated, which is discussed in Section 4.8. Noteworthily, other Industry 4.0 applications can benefit from VM quality estimation (Dreyfus and Kyritsis 2018). For instance, predictive maintenance could benefit from VM since product quality is strongly linked to machines' health (Roeder et al 2012;Hsieh et al 2013;Hsieh, Cheng, and Yang 2012).…”

Section: Virtual Metrology Frameworkmentioning

confidence: 99%

Virtual metrology as an approach for product quality estimation in Industry 4.0: a systematic review and integrative conceptual framework

Dreyfus

Psarommatis

May

et al. 2021

International Journal of Production Research

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Virtual metrology (VM) involves estimating a product's quality directly from production process data without physically measuring it. This enables the product quality of each unit of production to be monitored in real time, while preserving the process efficiency. Initially developed for the semiconductor industry, VM has recently been examined for use in other industrial fields. VM is enabled by components such as quality estimators and drift detectors. It enhances various industrial applications such as machine control and sampling decision systems. The literature lacks a comprehensive summary and a systematic review of the state of the art in VM. To fill this gap, this study followed a systematic methodology to conduct a complete and structured literature review of VM. This paper presents a detailed analysis of the 199 papers that we identified based on our search and selection criteria. Following our methodological framework, we assigned these papers to categories and highlighted shortcomings. Finally, we discussed VM's use in various industrial fields, underlining its potential for every manufacturing industry. This study and the proposed framework are useful for both practitioners and academicians since they raise crucial theoretical and managerial questions as well as provide suggestions for further research on this critical topic.

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Section: Virtual Metrology Frameworkmentioning

confidence: 99%

Virtual metrology as an approach for product quality estimation in Industry 4.0: a systematic review and integrative conceptual framework

Dreyfus

Psarommatis

May

et al. 2021

International Journal of Production Research

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“…This solution was evaluated based on product quality and other KPIs (Psarommatis, 2021). A more generic model that links scheduling with ZDM is proposed by Dreyfus and Kyritsis (2018), who aim to increase production capabilities without large investments. Their model is developed based on the combination of three different strategies: ZDM, predictive maintenance, and scheduling algorithms.…”

Section: Product or Quality-oriented Reschedulingmentioning

confidence: 99%

A Generic Methodology for Calculating Rescheduling Time for Multiple Unexpected Events in the Era of Zero Defect Manufacturing

et al. 2021

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Nowadays, the manufacturing industry is constantly changing. Production systems must operate in a highly dynamic environment where unexpected events could occur and create disruption, making rescheduling inevitable for manufacturing companies. Rescheduling models are fundamental to the robustness of production processes. This paper proposes a model to address rescheduling caused by unexpected events, aiming to achieve the zero-defect manufacturing (ZDM) concept. The goal of the model is to incorporate traditional and ZDM–oriented events into one methodology to calculate when the next rescheduling will be performed to effectively react to unexpected events. The methodology relies on the definition of two key time parameters for each event type: event response time (RT) and event delay response time (DRT). Based on these parameters, an event management algorithm is designed to identify the optimal rescheduling solution. The DRT parameter is calculated based on a multi-parametric dynamic formula to capture the dynamics of production. Moreover, ANOM, and ANOVA methods are used to analyse the behaviour of the developed method and to assess the level of robustness of the proposed approach. Finally, a case study based on real production scenarios is conducted, a series of simulation experiments are performed, and comparisons with other rescheduling policies are presented. The results demonstrate the effectiveness of the proposed event management algorithm for managing rescheduling.

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“…Downtime of a machine is known to be very costly. Reducing this downtime by a predictive maintenance of higher accuracy is a strong quality of ZDM (Dreyfus and Kyritsis, 2018).…”

Section: Evolution Toward Zdmmentioning

confidence: 99%

Product Quality Improvement Policies in Industry 4.0: Characteristics, Enabling Factors, Barriers, and Evolution Toward Zero Defect Manufacturing

Psarommatis

Prouvost

May

et al. 2020

Front. Comput. Sci.

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In the competitive market of manufacturing, quality is a criterion of primary importance in order to win market share. Quality improvement must be coupled with performance point of view. Lean Manufacturing, Six Sigma, Lean Six Sigma, Total Quality Management, Theory of Constraints, and their combination are philosophies dedicated to this goal. This study is a literature review on the implementation of these philosophies to improve quality of processes and products in a system, and also covers the commonalities and differences with Zero Defect Manufacturing (ZDM) philosophy. In this study, 45 articles have been analyzed. These articles have been selected by a research on several scientific libraries with specific keywords. The methodology is based on a list of information extracted from each paper. The data searched are on the tool selections, critical factors of implementations and the benefits obtained from them. Based on the review and analysis of the literature and practices, we provide the top 10 main components of the tools used for quality improvement, enabling factors, benefits, and barriers to implementation. Moreover, we present and discuss categorization of quality improvement methods and the way toward ZDM. The need of standardized toolkits for different levels of maturity in quality management systems and a better education have been enlightened. Thanks to technological improvement in information flow management, ZDM seems close to be achieved even though some new risks and wastes have to be taken care of within the implementation.

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A Framework Based on Predictive Maintenance, Zero-Defect Manufacturing and Scheduling Under Uncertainty Tools, to Optimize Production Capacities of High-End Quality Products

Cited by 15 publications

References 9 publications

Virtual metrology as an approach for product quality estimation in Industry 4.0: a systematic review and integrative conceptual framework

Virtual metrology as an approach for product quality estimation in Industry 4.0: a systematic review and integrative conceptual framework

A Generic Methodology for Calculating Rescheduling Time for Multiple Unexpected Events in the Era of Zero Defect Manufacturing

Product Quality Improvement Policies in Industry 4.0: Characteristics, Enabling Factors, Barriers, and Evolution Toward Zero Defect Manufacturing

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