Real-Time Process Monitoring in Industry 4.0 Manufacturing Systems: Sensing, Smart, and Sustainable Technologies

Gray-Hawkins, Malcolm; Michalkova, Lucia; Šuleř, Petr; Zhuravleva, Natalia A.

doi:10.22381/emfm14420194

Cited by 15 publications

(5 citation statements)

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Section: Resultsmentioning

confidence: 99%

“…This provides a seamless integration of the various production processes which makes new types of data and metrics available in real-time offering the chance to identify quality related causes and adjust processes without delay. In this context, Gray-Hawkins et al (2019) presented an empirical study, with data collected from Accenture, Capgemini, McKinsey, among others, to evaluate real-time process monitoring. The authors claimed that due to the intelligence and automation brought forward by technologies like IOT and CPS, increased adjustability can be offered which enhances the quality of the products facilitated by the superior and real-time process monitoring in I4.0 manufacturing systems.…”

Section: Impact Of Industry 40 On Improving Quality Management Practicesmentioning

confidence: 99%

“…Sader et al (2019a) discussed the challenges and barriers that impede achieving full advantage of I4.0 to quality management and stated that these challenges could be "scientific, technological, economic, social and political". Some of the Aspect Opportunities QC -Obtain information in real-time (Szajna et al, 2020) -Faster handling of advanced tasks (Szajna et al, 2020) -Automatic, continuous and real-time monitoring and alerting (Szajna et al, 2020;Gray-Hawkins et al, 2019) -New types of data and metrics available in real-time (Foidl and Felderer, 2016) -Availability of new techniques and inspection tools (Sader et al, 2019b) -Early failure detection and self-adaptation techniques (Sader et al, 2019b) -Identify quality related causes and adjust processes without delay (Foidl and Felderer, 2016) -Increased adjustability (Gray-Hawkins et al, 2019) -Detect new types of defects that were not possible previously (Godina et al, 2019) -QC can be made instantly on the production line and no longer needs a distinct metrology section (Godina et al, 2019) -Recording 100% of the data and ensuring 100% control (Godina et al, 2019) -Possibility of "in situ" correction of the process (correct the quality shift during the production itself) (Petritoli et al, 2020) -Improved data-driven decision making using big data analytics and cloud solutions (Miladin et al, 2019) -AR technology can be used in inspection by showing graphical instructions and tutoring the user about the inspection procedure (Etonam et al, 2019) -AI techniques support visual inspection (Chouchene et al, 2020) -Training models on potential out of control situations using ML techniques (Amini and Chang, 2018) -Recommend corrective actions using AI and ML techniques (Ramezani and Jassbi, 2020) QP -Using prescriptive analytics algorithms in QP to determine the best solutions and provide recommendations (Sony et al, 2020) -Customer specifications can be collected due to the end-to-end integration facilitated by I4.0 (Chiarini, 2020) -Data can be automatically streamed from customers to the design department in terms of specifications and quality characteristics (Chiarini, 2020) -Get feedback about the customer experience and the performance of the product in field (Foidl and Felderer, 2016; (Sony et al, 2020) -Process improvement facilitated by data driven quality prediction…”

Section: Current Challenges For Quality 40 Adoptionmentioning

confidence: 99%

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Quality 4.0: leveraging Industry 4.0 technologies to improve quality management practices – a systematic review

Saihi

Awad

Ben‐Daya

2021

IJQRM

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PurposeQuality 4.0 is an emerging research topic concerned with rethinking how quality management needs to be adopted in the digital era. The purpose of this research is to conduct a systematic review on the state of the research in the field of Industry 4.0 impact on improving quality management aspects and how technology can be leveraged to enhance its practices.Design/methodology/approachA systematic review of the literature published in the last 5 years is conducted. 52 papers were selected, mapped based on the technology they focused on and categorized based on the addressed quality aspects.FindingsThe review revealed various areas where quality management can benefit from Industry 4.0 technologies, identified several research gaps and suggested new directions for future research. Firstly, the literature provided some insights about industry 4.0 potential contributions but lacks further detail on the exact applications and solutions through use cases and case studies. Secondly, there has been a focus on the potential benefits provided for quality control while there is a clear scarcity in terms of the other quality management tools and methodologies. Thirdly, there is a lack of studies on economic analysis or detailed impacts on quality costs that justifies the substantial investments needed. Finally, there is a need for including more studies about the mapping and integration of ISO 9001 requirements and Industry 4.0 features.Originality/valueThis is the first attempt to conduct a comprehensive review on the ways industry 4.0 technologies can be leveraged for the field of quality management. Based on this review, several directions for further research in this area are identified.

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Section: Resultsmentioning

confidence: 99%

Section: Impact Of Industry 40 On Improving Quality Management Practicesmentioning

confidence: 99%

Section: Current Challenges For Quality 40 Adoptionmentioning

confidence: 99%

See 1 more Smart Citation

Quality 4.0: leveraging Industry 4.0 technologies to improve quality management practices – a systematic review

Saihi

Awad

Ben‐Daya

2021

IJQRM

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“…Therefore, in light of our first research question (RQ1), the technological components described in Table 3 are what allow the main principles of I4.0 to be outlined: interoperability, real-time access to data, virtualization, decentralized decision-making, and demand/service-oriented production (Santos et al, 2017 ). Generally speaking, people, machine, equipment, logistics systems and components are expected to communicate and cooperate with each other as these factories become adaptable and flexible (Iordache, 2017 ; Gray-Hawkins et al, 2019 ; Gajšek et al, 2020 ). Following this perspective and in contrast to previous work scenarios, new forms of human-machine interaction are supposed to assist workers safely and efficiently, in a diverse range of environments and tasks, even when these are highly dynamic and uncertain (Richert et al, 2016a ).…”

Section: Discussionmentioning

confidence: 99%

Exploring the status of the human operator in Industry 4.0: A systematic review

2022

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Industry 4.0 (I4.0) promises to transform jobs and working conditions through the implementation of unprecedented human-machine interaction modes. As the operator working in these new settings, known as the Operator 4.0, is a relatively recent concept, and although technological developments are expected to support workers and require higher labor skills, the risks and health impacts resulting from these changes remain underexplored. This systematic review aims to (i) systematize literature findings on how workers are perceived and participate in I4.0 work systems; (ii) identify the main technological changes driven by I4.0; and (iii) instigate discussion regarding the impacts these changes may have for workers and the sustainability of work systems. Following a systematic review approach using the PRISMA protocol, the articles were organized into two main analysis axes: the technical changes brought about by I4.0, and the representation of the human worker within these new work settings. The findings reveal that a techno-centered approach still seems to be dominant in guiding the implementation of I4.0 models; secondly, as a consequence, the social dimensions of work tend to remain as residual issues, overshadowed by the promises related with technology (e.g., productivity, efficiency); finally, the representation of the Operator 4.0 remains blurry, as he/she is perceived as gender neutral, skillful, and perfectly fit for work, assuring the functioning (and compensating for the limits) of these systems. While I4.0 promises safer and more productive workplaces, issues related to employment conditions, emerging risks and health impacts become more prominent when analyzed from an activity-centered perspective. In terms of future research, a more heuristic analysis could be achieved through a participatory and work-centered approach and following a gender perspective. This way, visibility could be conferred to another side of I4.0, thus guaranteeing conditions for the sustainable development of these work situations.

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“…Despite the challenges, IoT has the potential to transform SCM. By providing real-time visibility into the location and condition of inventory, as well as the ability to track and manage the flow of goods throughout the supply chain, IoT has the potential to improve efficiency, accuracy, and customer satisfaction while reducing costs (Gray-Hawkins et al, 2019).…”

Section: Internet Of Things and Supply Chain Managementmentioning

confidence: 99%

Supply chain management and industry 4.0

Kunrath

Dresch²,

Veit³

2022

BJO&PM

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Goal: The purpose of this study is to analyze how the elements of industry 4.0 relate to Supply Chain Management (SCM) by identifying mechanisms that promote or include these elements in the supply chain. The elements of industry 4.0 relate to the basic processes of Supply Chain Operations Reference (SCOR) when considering the literature on the subject. Design / methodology / approach: A systematic literature review was performed, and 126 articles were selected and analyzed. Content analyses were conducted to identify the main contributions of elements in SCM, explaining the mechanisms that promote or include elements in SCM and relating the elements to the basic processes of the SCOR model. Results: From the literature analysis, theoretical relations between the elements of industry 4.0 and SCM were established. An overview on the subject was provided, filling a gap in the literature. Identifying the mechanisms that promote or include elements in supply chains and the relations of elements to the SCOR model may help to guide managers for future applications of this model in a targeted manner. Limitations of investigation: This study covers only theoretical analysis on the concepts, that is, no real applications were made considering the topics addressed. Originality / value: The construction of a theoretical framework based on systematic literature review on SCM and Industry 4.0 is a contribution to the bibliographic database. Another contribution is the identification and analysis of the main contributions of elements to SCM in the processes of the SCOR model.

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Real-Time Process Monitoring in Industry 4.0 Manufacturing Systems: Sensing, Smart, and Sustainable Technologies

Cited by 15 publications

References 0 publications

Quality 4.0: leveraging Industry 4.0 technologies to improve quality management practices – a systematic review

Quality 4.0: leveraging Industry 4.0 technologies to improve quality management practices – a systematic review

Exploring the status of the human operator in Industry 4.0: A systematic review

Supply chain management and industry 4.0

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