Measurement of Operator-machine Interaction on a Chaku-chaku Assembly Line

Krugh, Matthew; McGee, Ethan T.; McGee, Stephen J.; Mears, Laine; Ivančo, Andrej; Podd, K.C.; Watkins, B.

doi:10.1016/j.promfg.2017.07.039

Cited by 14 publications

(9 citation statements)

References 17 publications

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“…[88]. Krugh et al measure human-machine interaction using the Internet of Things (IoT) to understand the impact of people on Industry 4.0 assembly systems [65]. Eye-tracking can be used to analyze the user experience of engineering design and manufacturing [89].…”

Section: Industry 40 Technologies For Improving Processes and Decisionsmentioning

confidence: 99%

“…In a similar way, Mattson et al propose a method of measuring the wellbeing and performance of operators at assembly stations using electro-dermal activity [88]. Industrial IoT is another technology that can be used for capturing human and machinery data for understanding human impact on Industry 4.0 assembly systems [65]. Understanding the operator's information needs is vital for the design of smart assembly factories [57].…”

Section: Framework For Operators In Industry 40mentioning

confidence: 99%

“…Digital technologies can also be used to obtain insights into human-machine interactions [65] or worker's wellbeing [88], which then lead to forming strategies for cognitive automation [49]. Despite recent advances, digital maturity in manufacturing companies has a long way to go, and most operator-machine interaction is done by mouse and keyboard hardware instead of by using CPS [237].…”

Section: Implications Of Smart Factories For Human Operatorsmentioning

confidence: 99%

See 2 more Smart Citations

Lean Manual Assembly 4.0: A Systematic Review

2020

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In a demand context of mass customization, shifting towards the mass personalization of products, assembly operations face the trade-off between highly productive automated systems and flexible manual operators. Novel digital technologies—conceptualized as Industry 4.0—suggest the possibility of simultaneously achieving superior productivity and flexibility. This article aims to address how Industry 4.0 technologies could improve the productivity, flexibility and quality of assembly operations. A systematic literature review was carried out, including 234 peer-reviewed articles from 2010–2020. As a result, the analysis was structured addressing four sets of research questions regarding (1) assembly for mass customization; (2) Industry 4.0 and performance evaluation; (3) Lean production as a starting point for smart factories, and (4) the implications of Industry 4.0 for people in assembly operations. It was found that mass customization brings great complexity that needs to be addressed at different levels from a holistic point of view; that Industry 4.0 offers powerful tools to achieve superior productivity and flexibility in assembly; that Lean is a great starting point for implementing such changes; and that people need to be considered central to Assembly 4.0. Developing methodologies for implementing Industry 4.0 to achieve specific business goals remains an open research topic.

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Section: Industry 40 Technologies For Improving Processes and Decisionsmentioning

confidence: 99%

Section: Framework For Operators In Industry 40mentioning

confidence: 99%

Section: Implications Of Smart Factories For Human Operatorsmentioning

confidence: 99%

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Lean Manual Assembly 4.0: A Systematic Review

2020

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“…On top of that, the high level of literacy and numeracy and the ability to understand complex written material is a basis of any occupation related to technical works (International Labor Office, 2012). The personnel must also have the human machineinteraction knowledge and understand to use the human-machine interface such as Virtual /Augmented Reality (Gehrke & Kühn, 2015;Karre et al, 2017;Krugh et al, 2017). To some extent, there are limitation on the robotics and automated system such as the requirement for human responses to uncertainties or urgent requests (Pacaux-Lemoine et al, 2017).…”

Section: Understanding the Human Role Requirement In Industry 40mentioning

confidence: 99%

A Systematic Literature Review: Human Roles, Competencies And Skills In Industry 4.0

Janis¹

2018

The European Proceedings of Social and Behavioural Sciences

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“…Among the characteristics of these systems, visualisation technologies such as augmented, virtual and mixed reality are incorporated into production processes and skills training, as they are considered useful for Industry 5.0 [14]. The immersive technologies named above [15], brain-computer and brain-machine interfaces thus improve manufacturing and instructional systems [16] and the performance of Operator 4.0 towards the transition to Operator 5.0 [12].…”

Section: Introductionmentioning

confidence: 99%

Neuro-Competence Approach for Sustainable Engineering

et al. 2021

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Manufacturing systems under Industry 4.0, and their transition towards Industry 5.0, take into account the Quintuple Helix innovation model, associated with the sustainable development goals (SDGs) set by the UN and Horizon 2030, in which companies focus on operational efficiency in terms of the use and minimisation of resources for the protection of the environment. In this respect, the implementation of the circular economy model, which requires engineers to acquire appropriate competencies, enabling companies to establish this model at the manufacturing level. Moreover, competence has always been a priority for both the professional and the company. In this sense, connectivism has been called a learning theory for the digital era; this is the reason why a review of the state-of-the-art developments of this paradigm focused on engineering has been carried out. In this sense, the potential of the digital transformation in instruction to formulate an engineering model based on neuro-competences is of great interest, taking the connectivist paradigm as a methodological axis. To this end, a first bibliometric analysis has been carried out to identify the drivers on which to base the design of the neuro-competencies of the instructional engineering environment and the trend towards curriculum development under dual training models. The bibliographical research carried out on the connectivist paradigm has served to identify the trends followed to date in education within the subject area of engineering. These trends have not fully taken into account the leading role of the human factor within the socio-technical cyber-physical systems of sustainable manufacturing (SCSSM). The focus was more on the technology than on the adaptation of the uniqueness of the human factor and the tasks entrusted to him, which entails an additional complexity that needs to be addressed in both academic and professional contexts. In light of the foregoing, an improvement to the acquisition and management of competencies has been proposed to the academic, professional and dual engineering contexts. It is based on the transversal inclusion of the concept of neuro-competence applied to the competence engineering (CE) model, transforming it into the neuro-competence engineering (NCE) model. The foregoing provides a better match between the characteristics of the human factor and the uniqueness of the tasks performed by the engineer, incorporating activity theory (AT), the law of variety required (LVR), the connectivist paradigm and neuroscience as a transversal driver of innovation through fractality. This proposal enables a ubiquitous and sustainable learning model throughout the entire academic and professional life cycle of the engineer, placing it sustainably at the heart of the instructional and professional cyber-physical socio-technical system, thus complying with the SDGs set by the UN and Horizon 2030.

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Measurement of Operator-machine Interaction on a Chaku-chaku Assembly Line

Cited by 14 publications

References 17 publications

Lean Manual Assembly 4.0: A Systematic Review

Lean Manual Assembly 4.0: A Systematic Review

A Systematic Literature Review: Human Roles, Competencies And Skills In Industry 4.0

Neuro-Competence Approach for Sustainable Engineering

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