Frameworks for data-driven quality management in cyber-physical systems for manufacturing: A systematic review

Cassoli, Beatriz Bretones; Jourdan, Nicolas; Nguyen, Phu H.; Sen, Sagar; Garcia-Ceja, Enrique; Metternich, Joachim

doi:10.1016/j.procir.2022.09.062

Cited by 11 publications

(4 citation statements)

References 6 publications

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“…Finally, regarding data security concerns in the integration of SPC with Industry 4.0, attention must be given to the gathering and sharing of sensitive production data. Sensitive data can raise concerns about privacy, data security, and the possibility of unauthorized access [41]. A strategic response to these concerns involves implementing cybersecurity measures such as access control [42], encryption [43], data masking, and anonymization [44] using secure data transmission protocols [45].…”

Section: Resultsmentioning

confidence: 99%

“…A strategic response to these concerns involves implementing cybersecurity measures such as access control [42], encryption [43], data masking, and anonymization [44] using secure data transmission protocols [45]. Additionally, it is crucial to adhere to established security regulations when implementing such types of measures [41].…”

Section: Resultsmentioning

confidence: 99%

“…SSPC signifies the integration of cutting-edge technologies, such as artificial intelligence (AI), natural language processing (NLP), and machine learning (ML), into conventional SPC frameworks. This transformative approach not only facilitates real-time monitoring and analysis of production processes but also endows the system with predictive capabilities and adaptive control, thereby contributing to overall operational excellence in advanced manufacturing [41]. The importance of incorporating advanced technologies is particularly pronounced in advanced manufacturing systems, ensuring heightened quality, minimized defects, and enhanced overall efficiency [14].…”

Section: Application Example: Guidelines For An Sspcmentioning

confidence: 99%

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Industry 4.0 and Smart Systems in Manufacturing: Guidelines for the Implementation of a Smart Statistical Process Control

Goecks,

Habekost,

Coruzzolo

et al. 2024

ASI

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Digital transformations in manufacturing systems confer advantages for enhancing competitiveness and ensuring the survival of companies by reducing operating costs, improving quality, and fostering innovation, falling within the overarching umbrella of Industry 4.0. This study aims to provide a framework for the integration of smart statistical digital systems into existing manufacturing control systems, exemplified with guidelines to transform an existent statistical process control into a smart statistical process control. Employing the design science research method, the research techniques include a literature review and interviews with experts who critically evaluated the proposed framework. The primary contribution lies in a set of general-purpose guidelines tailored to assist practitioners in manufacturing systems with the implementation of digital, smart technologies aligned with the principles of Industry 4.0. The resulting guidelines specifically target existing manufacturing plants seeking to adopt new technologies to maintain competitiveness. The main implication of the study is that practitioners can utilize the guidelines as a roadmap for the ongoing development and implementation of project management. Furthermore, the study paves the way for open innovation initiatives by breaking down the project into defined steps and encouraging individual or collective open contributions, which consolidates the practice of open innovation in manufacturing systems.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Application Example: Guidelines For An Sspcmentioning

confidence: 99%

See 1 more Smart Citation

Industry 4.0 and Smart Systems in Manufacturing: Guidelines for the Implementation of a Smart Statistical Process Control

Goecks,

Habekost,

Coruzzolo

et al. 2024

ASI

View full text Add to dashboard Cite

show abstract

“…However, the development of increasingly complex technologies has exacerbated this situation in the industrial environments of Industry 4.0 [21]. This has been of interest to researchers, and the existing literature already includes several frameworks proposed to facilitate integration [22]. Butt proposes a conceptual framework that supports digital transformation in manufacturing through a business process management (BPM) approach.…”

Section: Framework For Incorporating Technology Into the Production P...mentioning

confidence: 99%

A Framework for Sustainable Manufacturing: Integrating Industry 4.0 Technologies with Industry 5.0 Values

Martín-Gómez,

Agote-Garrido,

Lama-Ruiz

2024

Sustainability

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The limitations imposed by resource scarcity and the imperative to mitigate adverse environmental and societal impacts have intensified the urgency of developing more sustainable manufacturing systems. Simultaneously, the rapid development and implementation of new technologies is exacerbating the digital divide among vulnerable workers. Concomitantly, the enabling technologies stemming from Industry 4.0 offer significant potential to enhance the competitiveness of manufacturing systems. However, the impact of these enabling technologies on achieving sustainable manufacturing remains uncertain. This paper embarks on a comprehensive exploration to address this knowledge gap. Initially, it assesses the suitability of each enabling technology within Industry 4.0 across the economic, social, and environmental dimensions of sustainability. Subsequently, the needs of the production process are studied to characterize its sustainable performance. For this, the ASTM E3012-22 standard is introduced. Building upon this foundation, the incorporation of Industry 5.0 is introduced to guide the selection of enabling technologies for sustainability based on its core values, encompassing sustainability, human-centricity, and resilience. The integration of new technologies guided by these values can help bridge the technological divide among vulnerable workers. Finally, a theoretical framework is proposed to enable the design of sustainable manufacturing systems guided by Industry 5.0 values. This framework enables the seamless integration of enabling technologies, machinery, and human expertise throughout the system life cycle.

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Industrial Cyber-Physical Systems: Control Problems and Solutions. A Bibliometric Analysis Approach

Kravets,

Borzin,

Rogozhnikov

2024

Studies in Systems, Decision and Control

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Frameworks for data-driven quality management in cyber-physical systems for manufacturing: A systematic review

Cited by 11 publications

References 6 publications

Industry 4.0 and Smart Systems in Manufacturing: Guidelines for the Implementation of a Smart Statistical Process Control

Industry 4.0 and Smart Systems in Manufacturing: Guidelines for the Implementation of a Smart Statistical Process Control

A Framework for Sustainable Manufacturing: Integrating Industry 4.0 Technologies with Industry 5.0 Values

Industrial Cyber-Physical Systems: Control Problems and Solutions. A Bibliometric Analysis Approach

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