Tangible Industry 4.0: A Scenario-Based Approach to Learning for the Future of Production

By Selim Erol, Andreas Jäger, Philipp Hold, Karl Ott, Wilfried Sihn. 2016

518 citations recorded by the source corpus.

Abstract Industry is currently undergoing a transformation towards full digitalization and intelligentization of manufacturing processes. Visionary but quite realistic concepts such as the Internet of Things, Industrial Internet, Cloud-based Manufacturing and Smart Manufacturing are drivers of the so called Fourth Industrial Revolution which is commonly referred to as Industry 4.0. Although a common agreement exists on the necessity for technological advancement of production technologies and business models in the sense of Industry 4.0, a major obstacle lies in the perceived complexity and abstractness which partly hinders its quick transformation into industrial practice. To overcome these burdens, we suggest a Scenario-based Industry 4.0 Learning Factory concept that we are currently planning to implement in Austria's first Industry 4.0 Pilot Factory. The concept is built upon a tentative competency model for Industry 4.0 and the use of scenarios for problem-oriented learning of future production engineering.

Subfields: Industrial and Manufacturing Engineering, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/f6739d1460a8782b774f6ee7929a93a8d2ead527

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In Industrial and Manufacturing Engineering

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Citations in the corpus

Smart operators in industry 4.0: A human-centered approach to enhance operators' capabilities and competencies within the new smart factory context (2017, methodology): “0 can be attributed to Erol et al. (2016). Although still in a planning stage, Erol et al. (2016) devise the TU Wien Industry 4.0 Pilot Factory where a learning Factory approach and scenario-based learning are combined to: promote research in the smart production, involve SMEs without own research i”
Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers (2020, methodology): “A few authors (e.g. Erol et al., 2016; Shamim et al., 2016; Hecklau et al., 2016) advised that misinterpretations or inadequate integration of I4.”
Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2020, background): “…around the integration of AI at nearly every level to drive predictive maintenance, future business strategies, and floor production, with humans working alongside AI to make vital decisions for the company (Erol et al., 2016; Kang et al., 2016; Lee et al., 2015; Mabkhot et al., 2018; Omron, 2020).”
What Drives the Implementation of Industry 4.0? The Role of Opportunities and Challenges in the Context of Sustainability (2018, background): “, understanding network technologies as well as data analysis and processing) [42].”
The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics (2018, methodology): “0 technology enables new production strategies with the use of cyber-physical system principles based on highly customised assembly systems with flexible manufacturing process design (Erol et al. 2016; Kumar et al. 2016; Nayak et al. 2016; Oesterreich and Teuteberg 2016; Liao et al. 2017).”
Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review (2020, background): “The problem of the competence framework implies a three-dimensional approach, involving the level of the enterprise management, the fields of the production process and the types of competences [24].”
From Industry 4.0 towards Industry 5.0: A Review and Analysis of Paradigm Shift for the People, Organization and Technology (2022, background): “…of ergonomics [60]: • Physical domain—the Industry 4.0 technologies help with the automatization of manual repetitive tasks or hard-muscular tasks [61]; the devices to use on workplace are improving ergonomic feedback and new digital technologies improve internal logistics and transportation [62].”