An industrial Internet of things based platform for context-aware information services in manufacturing

Alexopoulos, Kosmas; Σίψας, Κωνσταντίνος; Xanthakis, Evangelos; Makris, Sotiris; Mourtzis, Dimitris

doi:10.1080/0951192x.2018.1500716

Cited by 68 publications

(15 citation statements)

References 12 publications

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“…Various authors use the Internet of Things to obtain information on the status of the production system and to make it available to employees, corresponding to the monitoring level (e.g. Alexopoulos et al 2018;Brintrup, Ranasinghe, and McFarlane 2010;Bonci, Pirani, and Longhi 2016;Cao et al 2017;Davies, Coole, and Smith 2017;Hwang et al 2017;Mayr et al 2018;Mousavi and Siervo 2017;Saez et al 2018;Zhong et al 2015;Zhuang, Liu, and Xiong 2018). Tao et al (2017) and Zhong et al (2015Zhong et al ( , 2016 suggest using cloud computing to make information related to the production system available.…”

Section: Foundationsmentioning

confidence: 99%

Impacts of Industry 4.0 technologies on Lean principles

Rosin

Forget

Lamouri

et al. 2019

International Journal of Production Research

316

205

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Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies. On the other hand, many companies have already partially or fully implemented principles and tools from the Lean management approach, which is also aimed at improving productivity. While the two approaches use very different strategies, they share some common principles. The objective of this article is to highlight the links between the principles and tools proposed by Industry 4.0 and those proposed by the Lean management approach, with a particular focus on how some of Industry 4.0's technologies are improving the implementation of Lean principles, depending on the technologies' capability levels. As such, this study aims to provide a characterisation of the impacts of Industry 4.0 technologies on Lean principles according to targeted capability levels. The results obtained show strong support for Industry 4.0 technologies for Just-in-time and Jidoka, but little or no support for waste reduction and People and Team work. There is, therefore, a clear need to pursue the deployment of Lean management while improving certain Lean principles using Industry 4.0 technologies.

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Section: Foundationsmentioning

confidence: 99%

Impacts of Industry 4.0 technologies on Lean principles

Rosin

Forget

Lamouri

et al. 2019

International Journal of Production Research

316

205

View full text Add to dashboard Cite

show abstract

“…These systems focus on getting a particular piece of information and none of them automatically instantiate more than one concept. The system proposed by Alexopoulos et al [36] could provide answers to most aspects of our research issue. It uses rules to interpret location sensors, a weather station and energy sensors on machines to detect a worker in predefined zones and automatically assign a suited set of tasks.…”

Section: Modelling Of a Crisis Situation In Real Time From Raw Datamentioning

confidence: 99%

“…Abbreviations: N No, Y Yes, (n of 1) n attributes of 1 concept. [28] 3 (sensors of an underwater vehicle) n of 1 (fault) Y N [29] n (traffic data) n of 1 (road) Y N [30] 2 (speed, location of vessels) n of 1 (threat) Y N [31,32] 3 (time, position, role) n of 1 (anomaly) Y N [33] 4 (!door, time, presence, light) 1 of 1 (!room) Y N [34,35] 4 (time, location, weather, company) 1 of 1 (!trip) Y N [36] 3 (weather, energy, location) n of 1 (task) Y N crisis (information variety & velocity), (iv) automatically update the model of an on-going crisis situation by instantiating a metamodel common to all kinds of crisis situations (information variety), (v) display the corresponding common operational picture to support the decision-making of the emergency managers and (vi) allow the emergency managers to manually edit available information (information veracity)?…”

Section: The Gaps To Be Filled By Emergency Decision Support Systemsmentioning

confidence: 99%

A new emergency decision support system: the automatic interpretation and contextualisation of events to model a crisis situation in real-time

Fertier

Barthe‐Delanoë

Montarnal

et al. 2020

Decision Support Systems

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“…More specifically, digital applications can be used to increase the visibility of operations and performance status, to gain a systematic understanding of the system, and to make real-time decisions based on the context of the factory (Alexopoulos et al 2018). In light of this, it is important to consider what the literature states as being enablers of such processes.…”

Section: Enablers and Barriersmentioning

confidence: 99%

Development and implementation processes of digitalization in engineer-to-order manufacturing: enablers and barriers

2021

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This study seeks to gain knowledge about key conditions in the process of digitalization using a socio-technical systems design as a theoretical framework and a case-study approach. Semi-structured interviews with 15 relevant stakeholders are conducted to learn about barriers to and enablers of the development and implementation process in a manufacturing company. After conducting a thematic analysis, eight higher-ranked themes relevant to the digitalization process are identified. These are grouped to describe the overarching phenomena, resulting in four enablers (shared trust, shared visual understanding, shared user perspective, and shared learning) and four barriers (trusting the system, understanding benefits, perspective of economics, and learning to manage scope). The study takes a holistic view of digitalization in its investigation of the development and subsequent implementation processes. The findings contribute to the literature via three key takeaways for stakeholders of a digitalization process in manufacturing. First, it is vital to understand and strengthen the role of the key enablers identified in this paper. Second, managers should observe and identify barriers in their own organizations, related both to technical and social aspects. Third, some of the enablers described in this paper can serve managers as helpful tools to approach the expected barriers to digitalization. This paper also challenges the research literature by arguing that research conducted on digitalization that sets new standards and premises for the working life in industry needs to use up-to-date socio-technical design concepts and theories.

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An industrial Internet of things based platform for context-aware information services in manufacturing

Cited by 68 publications

References 12 publications

Impacts of Industry 4.0 technologies on Lean principles

Impacts of Industry 4.0 technologies on Lean principles

A new emergency decision support system: the automatic interpretation and contextualisation of events to model a crisis situation in real-time

Development and implementation processes of digitalization in engineer-to-order manufacturing: enablers and barriers

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