A Perspective on Industry 4.0: From Challenges to Opportunities in Production Systems

Khan, Altaf; Turowski, Klaus

doi:10.5220/0005929704410448

Cited by 74 publications

(45 citation statements)

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“…Additionally, the capabilities needed in the workforce vary on an individual, cultural, gender or generational basis [28]. For example, older workers may be more reluctant to use new technologies [29] or may present different needs in training and skills development [30].…”

Section: Technological Change In Organizationsmentioning

confidence: 99%

Human-Machine Interaction and Human Resource Management Perspective for Collaborative Robotics Implementation and Adoption

Libert¹,

Mosconi²,

Cadieux³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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The shift towards human-robot collaboration (HRC) has the potential to increase productivity and sustainability, while reducing costs for the manufacturing industries. Indeed, it holds great potential for workplaces, allowing individuals to forsake repetitive or physically demanding jobs to focus on safer and more fulfilling ones. Still, integration of humans and machines in organizations presents great challenges to IS scholars due to the complexity of aligning digitalization and human resources. A knowledge gap does persist about organizational implications when it comes to implement collaborative robotics in the workplace and to support proper HRC. Thus, this paper aims to identify recommended human resources management (HRM) practices from previous research about human-robot interaction (HRI). As our results highlight that few studies attempted to fill the gap, a conceptual framework is proposed. It integrates HRM practices, technology adoption dimensions and main determinants of HRC, in the objective to support collaborative robotics implementation in organizations.

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Section: Technological Change In Organizationsmentioning

confidence: 99%

Human-Machine Interaction and Human Resource Management Perspective for Collaborative Robotics Implementation and Adoption

Libert¹,

Mosconi²,

Cadieux³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Section: Pilot Projects In Digital Transformation Initiativesmentioning

confidence: 99%

“…An iterative approach for industry 4.0 is presented in Khan and Turowski (2016), starting with the definition of the goals that need to be achieved. A cycle evolves in nine phases that are aligned with the Plan-Do-Check-Act approach and includes proofs of concept and continuous learning (Khan and Turowski 2016). The year-long pilot project presented by Flatscher and Riel (2016) highlights the importance of creating the project team and a shared understanding of the topic.…”

Section: Pilot Projects In Digital Transformation Initiativesmentioning

confidence: 99%

“…The year-long pilot project presented by Flatscher and Riel (2016) highlights the importance of creating the project team and a shared understanding of the topic. This initial phase (a) can be compared to the goals and strategy definition presented in Khan and Turowski (2016). The case evolves to (b): the design of the "to-be" situation; (c): describing "as-is"; (d): identifying the gaps between both b and c; (e): clustering the deviation causes, and (f): describing each field of action, resources, and specific actions for each field.…”

Section: Pilot Projects In Digital Transformation Initiativesmentioning

confidence: 99%

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Guidelines for Using Pilot Projects in the Fourth Industrial Revolution

Barata¹,

Cunha²,

Coyle³

2018

Australasian Conference on Information Systems 2018

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Pilot projects are popular in companies for experimenting with industry 4.0 concepts. However, few studies have addressed the specificities of piloting transformation, whose requirements are quite different than those for implementing a project with clear goals. Pilot projects can be used for the purpose of exploring, demonstrating, optimizing and disseminating solutions. In this paper we identify the role of pilot projects in digital transformation and define a successful pilot project so that it transcends to a full project. We provide accessible guidelines for the deployment of pilot projects in industry 4.0, drawing from a structured literature review and from lessons learned in an action research project implementing mixed reality in household ceramics production. A sound approach to pilot projects is important to reduce unknowns and risks in ensuing full projects and to contributing to organizational knowledge, offering an opportunity to rethink business strategies and train employees in digital transformation.

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“…The digitization introduced around the 1970s helped use advanced electronics and information technology for process automation, which formed the era of Industry 3.0. The current (r)evolution, termed Industry 4.0, is driven by the emergence of concepts, such as cloud-computing, smart sensors, internet of things (IoT), big data analytics, augmented reality, and human-machine interfaces [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Gray-box Soft Sensors in Process Industry: Current Practice, and Future Prospects in Era of Big Data

et al. 2020

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Virtual sensors, or soft sensors, have greatly contributed to the evolution of the sensing systems in industry. The soft sensors are process models having three fundamental categories, namely white-box (WB), black-box (BB) and gray-box (GB) models. WB models are based on process knowledge while the BB models are developed using data collected from the process. The GB models integrate the WB and BB models for addressing the concerns, i.e., accuracy and intuitiveness, of industrial operators. In this work, various design aspects of the GB models are discussed followed by their application in the process industry. In addition, the changes in the data-driven part of the GB models in the context of enormous amount of process data collected in Industry 4.0 are elaborated.

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A Perspective on Industry 4.0: From Challenges to Opportunities in Production Systems

Cited by 74 publications

References 0 publications

Human-Machine Interaction and Human Resource Management Perspective for Collaborative Robotics Implementation and Adoption

Human-Machine Interaction and Human Resource Management Perspective for Collaborative Robotics Implementation and Adoption

Guidelines for Using Pilot Projects in the Fourth Industrial Revolution

Gray-box Soft Sensors in Process Industry: Current Practice, and Future Prospects in Era of Big Data

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