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Dr. Erwin Rauch
Free University of Bozen-Bolzano

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Research Keywords & Expertise

0 Axiomatic Design
0 Industry 4.0
0 Manufacturing And Assembly
0 suatainability
0 Cyber Physical Systems

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Industry 4.0
Axiomatic Design
Cyber Physical Systems

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Conference paper
Published: 13 June 2021 in Proceedings of International Conference on Big Data, Machine Learning and Applications
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This experimental study is set out to explore the effects of collaborative robotic system features on Workers’ perceived cognitive workload, usability and visual attention. This work’s primary objective is to identify strategies for lowering workers’ cognitive workload and increase usability when collaborating with robots in assembly tasks, ultimately fostering safety and performance. Perceived cognitive workload significantly decreased, and usability increased with the manipulation of workstation elements as well as the conditions of human interaction. Individual differences across participants suggest that robots should be capable of adjusting their behaviour according to the specific user.

ACS Style

Federico Fraboni; Luca Gualtieri; Francesco Millo; Matteo De Marchi; Luca Pietrantoni; Erwin Rauch. Human-Robot Collaboration During Assembly Tasks: The Cognitive Effects of Collaborative Assembly Workstation Features. Proceedings of International Conference on Big Data, Machine Learning and Applications 2021, 242 -249.

AMA Style

Federico Fraboni, Luca Gualtieri, Francesco Millo, Matteo De Marchi, Luca Pietrantoni, Erwin Rauch. Human-Robot Collaboration During Assembly Tasks: The Cognitive Effects of Collaborative Assembly Workstation Features. Proceedings of International Conference on Big Data, Machine Learning and Applications. 2021; ():242-249.

Chicago/Turabian Style

Federico Fraboni; Luca Gualtieri; Francesco Millo; Matteo De Marchi; Luca Pietrantoni; Erwin Rauch. 2021. "Human-Robot Collaboration During Assembly Tasks: The Cognitive Effects of Collaborative Assembly Workstation Features." Proceedings of International Conference on Big Data, Machine Learning and Applications , no. : 242-249.

Conference paper
Published: 26 May 2021 in Recent Advances in Computational Mechanics and Simulations
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Emerging Industry 4.0 technologies are changing very fast, and in few years, technologies reach a new level of maturity, or new technologies are introduced. This makes it difficult for manufacturing companies to keep track of the fast development and evaluate a future introduction of new technologies related to the Fourth Industrial Revolution. Therefore this work aims to realize an Industry 4.0 technology radar for industrial organizations based on the Gartner Hype Cycle Curve. This tool aims to analyze new emerging technologies that could affect manufacturing firms, enabling selecting the most suitable ones. The technology evaluation considers three parameters: a technology maturity level, enterprise value, and deployment risk of technologies. The application of such a tool highlights which technologies to include in the company’s future technology strategy. The developed technology radar was applied in a real industrial case study to prove its applicability and limitations.

ACS Style

Erwin Rauch; Eugenio Vinante. Three Dimensional Technology Radar Model to Evaluate Emerging Industry 4.0 Technologies. Recent Advances in Computational Mechanics and Simulations 2021, 233 -242.

AMA Style

Erwin Rauch, Eugenio Vinante. Three Dimensional Technology Radar Model to Evaluate Emerging Industry 4.0 Technologies. Recent Advances in Computational Mechanics and Simulations. 2021; ():233-242.

Chicago/Turabian Style

Erwin Rauch; Eugenio Vinante. 2021. "Three Dimensional Technology Radar Model to Evaluate Emerging Industry 4.0 Technologies." Recent Advances in Computational Mechanics and Simulations , no. : 233-242.

Chapter
Published: 09 May 2021 in Implementing Industry 4.0 in SMEs
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Human–robot cooperation aims to increase the flexibilization of manufacturing systems. This requires safe human–machine interaction (e.g. with collaborative robots) as well as self and environment awareness capabilities to interact autonomously and smartly between humans and machines. Therefore, the goal of this chapter is to conceptualize and identify the set of real-time information processing and decision-making capabilities required for collaborative robots to be considered as a safe companion in the context of human–robot cooperation (HRC). In particular, the chapter provides an overview of appropriate artificial intelligence (AI) and machine learning (ML) concepts, formally introduces the concept of a safety-aware cyber-physical system and defines a general taxonomy for the perceptive and cognitive problems arising in the context of intelligent and flexible HRC.

ACS Style

Manuel A. Ruiz Garcia; Erwin Rauch; Renato Vidoni; Dominik T. Matt. AI and ML for Human-Robot Cooperation in Intelligent and Flexible Manufacturing. Implementing Industry 4.0 in SMEs 2021, 95 -127.

AMA Style

Manuel A. Ruiz Garcia, Erwin Rauch, Renato Vidoni, Dominik T. Matt. AI and ML for Human-Robot Cooperation in Intelligent and Flexible Manufacturing. Implementing Industry 4.0 in SMEs. 2021; ():95-127.

Chicago/Turabian Style

Manuel A. Ruiz Garcia; Erwin Rauch; Renato Vidoni; Dominik T. Matt. 2021. "AI and ML for Human-Robot Cooperation in Intelligent and Flexible Manufacturing." Implementing Industry 4.0 in SMEs , no. : 95-127.

Review
Published: 10 March 2021 in Journal of Manufacturing Systems
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In the course of the fourth industrial revolution (also known as Industry 4.0 or I4.0) the operator itself comes to the fore. The technological and computational developments of recent years since the beginning of Industry 4.0 have led to a rapid progress in the development of technical worker assistance systems to support the worker in his daily work. So far, however, there are hardly any sufficient studies or a comprehensive overview of worker assistance systems. Therefore, in this paper, a systematic literature review of worker assistance systems in manufacturing is presented. A detailed descriptive and content analysis provide an extensive overview of the state of the art of worker assistance systems used in industrial settings. A particular focus is given to the analysis of potentials and future directions for these technical worker assistance systems. Additionally, gaps in research and in the transfer from research to industry are revealed. This information is then used to derive strategic measures addressed to stakeholders for either exploiting the benefits of such systems, for conducting further basic and applied research or for improving the applicability and potential for industry.

ACS Style

Benedikt G. Mark; Erwin Rauch; Dominik T. Matt. Worker assistance systems in manufacturing: A review of the state of the art and future directions. Journal of Manufacturing Systems 2021, 59, 228 -250.

AMA Style

Benedikt G. Mark, Erwin Rauch, Dominik T. Matt. Worker assistance systems in manufacturing: A review of the state of the art and future directions. Journal of Manufacturing Systems. 2021; 59 ():228-250.

Chicago/Turabian Style

Benedikt G. Mark; Erwin Rauch; Dominik T. Matt. 2021. "Worker assistance systems in manufacturing: A review of the state of the art and future directions." Journal of Manufacturing Systems 59, no. : 228-250.

Journal article
Published: 05 March 2021 in Robotics
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Nowadays, the wire harness assembly process is still manually performed due to the process complexity and product variability (e.g., wires of different kind, size and length). The Wire cobots project, in which this work was conceived, aims at improving the current state-of-art assembly process by introducing in it collaborative robotics. A shared workstation exploiting human abilities and machine strengths was developed to assembly automotive wire harness by means of insulated tape for a real industrial case. In the new workstation, the human deals with the complex task of wire handling, while the robot performs the repetitive and strenuous taping operations. Such a task allocation together with the workstation redesign allow for an improvement of the operator’s well-being in terms of postural conditions and for an increase of the production efficiency. In this paper, the mechanical and mechatronic design, as well as the realization and validation of this new collaborative workstation are presented and discussed.

ACS Style

Ilaria Palomba; Luca Gualtieri; Rafael Rojas; Erwin Rauch; Renato Vidoni; Andrea Ghedin. Mechatronic Re-Design of a Manual Assembly Workstation into a Collaborative One for Wire Harness Assemblies. Robotics 2021, 10, 43 .

AMA Style

Ilaria Palomba, Luca Gualtieri, Rafael Rojas, Erwin Rauch, Renato Vidoni, Andrea Ghedin. Mechatronic Re-Design of a Manual Assembly Workstation into a Collaborative One for Wire Harness Assemblies. Robotics. 2021; 10 (1):43.

Chicago/Turabian Style

Ilaria Palomba; Luca Gualtieri; Rafael Rojas; Erwin Rauch; Renato Vidoni; Andrea Ghedin. 2021. "Mechatronic Re-Design of a Manual Assembly Workstation into a Collaborative One for Wire Harness Assemblies." Robotics 10, no. 1: 43.

Original article
Published: 21 February 2021 in The International Journal of Advanced Manufacturing Technology
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Industrial collaborative robotics is an enabling technology and one of the main drivers of Industry 4.0 in industrial assembly. It allows a safe physical and human-machine interaction with the aim of improving flexibility, operator’s work conditions, and process performance at the same time. In this regard, collaborative assembly is one of the most interesting and useful applications of human-robot collaboration. Most of these systems arise from the re-design of existing manual assembly workstations. As a consequence, manufacturing companies need support for an efficient implementation of these systems. This work presents a systematical methodology for the design of human-centered and collaborative assembly systems starting from manual assembly workstations. In particular, it proposes a method for task scheduling identifying the optimal assembly cycle by considering the product and process main features as well as a given task allocation between the human and the robot. The use of the proposed methodology has been tested and validated in an industrial case study related to the assembly of a touch-screen cash register. Results show how the new assembly cycle allows a remarkable time reduction with respect to the manual cycle and a promising value in terms of payback period.

ACS Style

Luca Gualtieri; Erwin Rauch; Renato Vidoni. Methodology for the definition of the optimal assembly cycle and calculation of the optimized assembly cycle time in human-robot collaborative assembly. The International Journal of Advanced Manufacturing Technology 2021, 113, 2369 -2384.

AMA Style

Luca Gualtieri, Erwin Rauch, Renato Vidoni. Methodology for the definition of the optimal assembly cycle and calculation of the optimized assembly cycle time in human-robot collaborative assembly. The International Journal of Advanced Manufacturing Technology. 2021; 113 (7-8):2369-2384.

Chicago/Turabian Style

Luca Gualtieri; Erwin Rauch; Renato Vidoni. 2021. "Methodology for the definition of the optimal assembly cycle and calculation of the optimized assembly cycle time in human-robot collaborative assembly." The International Journal of Advanced Manufacturing Technology 113, no. 7-8: 2369-2384.

Journal article
Published: 10 February 2021 in Procedia CIRP
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This work shows how to teach axiomatic design (AD) of manufacturing processes and systems in small and medium enterprises (SMEs) to achieve long-term sustainability in the introduction of Industry 4.0. This is about how to develop profitable and ethical design solutions by exploiting emerging technologies, especially for companies with limited resources. Suh’s axiomatic approach to design selects the best solution among plausible candidates early in the design process so that resources can be focused most effectively. It is important that engineers know how to develop ethical design solutions efficiently and effectively. Sustainability rests on three pillars, economic, ecological and social. Therefore, ethical design can be achieved, with responsible use of natural resources and protection of the environment, meeting the needs of people and society as well as profitability to ensure long-term prosperity for all. Literature on Industry 4.0 shows several approaches on how Industry 4.0 can be sustainable and human-centered. However, few works focus on SMEs and there is little on teaching. Here, AD is used to create a program for teaching how to apply AD to design problems in the context of Industry 4.0 for SMEs. AD theory states that the best design solutions are those that, 1- maintain the independence of the functional elements, and 2- minimize the information content, i.e., maximize the probability of success. In AD, needs of customers and other stake holders are considered first, so that the right problems are addressed. Then top-down, parallel, functional-physical decompositions, are followed by physical integrations, all guided by Suh’s axioms to select the right solutions. In order to test new technologies in a practice-oriented way in advance of introduction for SMEs, learning factory laboratories are used.

ACS Style

Erwin Rauch; Christopher A. Brown. Teaching Axiomatic Design for a Long-Term Sustainable Introduction of Industry 4.0 in SMEs. Procedia CIRP 2021, 96, 169 -174.

AMA Style

Erwin Rauch, Christopher A. Brown. Teaching Axiomatic Design for a Long-Term Sustainable Introduction of Industry 4.0 in SMEs. Procedia CIRP. 2021; 96 ():169-174.

Chicago/Turabian Style

Erwin Rauch; Christopher A. Brown. 2021. "Teaching Axiomatic Design for a Long-Term Sustainable Introduction of Industry 4.0 in SMEs." Procedia CIRP 96, no. : 169-174.

Journal article
Published: 10 February 2021 in Procedia CIRP
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The current introduction of Industry 4.0 is very challenging for industrial companies. On the one hand, there is an urge to implement concepts such as digital worker assistance systems or cyber-physical production systems, but besides theoretical work, there is very little research that shows examples of its practical implementation. Furthermore, there is currently a lack of a clear model of how sensor-based worker assistance systems for data acquisition and analytics can be designed and systematically implemented. In the present research, a model for a vision-based worker assistance system for assembly was developed based on an industrial case study regarding a manual assembly line. The proposed model consists of five integrated modules: data acquisition, data preprocessing, data storage, data analysis, and simulation. The data acquisition module was constructed in the assembly workstation of the production line by implementing a depth camera, which together with an algorithm developed in Python for preprocessing, tracks the activities of the operator and inserts the processing times into a SQL table of the data storage module. This module contains all the relevant information of the production system, from the shop floor to the Manufacturing Execution System, enabling vertical integration. The data analysis module, aimed at the streaming and predictive analytics, was deployed in the RStudio platform. Likewise, the simulation module was conceptualized to retrieve real-time data from the shop floor and to select the best strategy. To evaluate the model testing of the proposed system in real production was performed. The results of this use case provide useful information for academia as well as practitioners how to implement vision-based worker assistance systems.

ACS Style

Carlos A. Paz Rocha; Erwin Rauch; Taavi Vaimel; Manuel A. Ruiz Garcia; Renato Vidoni. Implementation of a Vision-Based Worker Assistance System in Assembly: a Case Study. Procedia CIRP 2021, 96, 295 -300.

AMA Style

Carlos A. Paz Rocha, Erwin Rauch, Taavi Vaimel, Manuel A. Ruiz Garcia, Renato Vidoni. Implementation of a Vision-Based Worker Assistance System in Assembly: a Case Study. Procedia CIRP. 2021; 96 ():295-300.

Chicago/Turabian Style

Carlos A. Paz Rocha; Erwin Rauch; Taavi Vaimel; Manuel A. Ruiz Garcia; Renato Vidoni. 2021. "Implementation of a Vision-Based Worker Assistance System in Assembly: a Case Study." Procedia CIRP 96, no. : 295-300.

Chapter
Published: 01 January 2021 in Research Anthology on Cross-Industry Challenges of Industry 4.0
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Industry 4.0 is for most companies and especially for small and medium sized enterprises (SMEs) one of the major challenges after the wave of lean management. The aim of this chapter is to provide a methodological guidance for the practical use of the Industry 4.0 vision and principles in production system design in the specific context of SMEs. Based on the analysis of literature, a procedure model for the target-oriented introduction of Industry 4.0 principles in SMEs is proposed. A first practical evaluation of the approach is carried out based on two industrial case studies. The experiences made in the industrial cases show that Industry 4.0 is not limited to the application in large enterprises but is very suitable also for SME. This chapter contributes, with its case-study-based methodology, to the existing sparse knowledge on the introduction of Industry 4.0 in SME production systems.

ACS Style

Dominik T. Matt; Erwin Rauch; Michael Riedl. Knowledge Transfer and Introduction of Industry 4.0 in SMEs. Research Anthology on Cross-Industry Challenges of Industry 4.0 2021, 275 -302.

AMA Style

Dominik T. Matt, Erwin Rauch, Michael Riedl. Knowledge Transfer and Introduction of Industry 4.0 in SMEs. Research Anthology on Cross-Industry Challenges of Industry 4.0. 2021; ():275-302.

Chicago/Turabian Style

Dominik T. Matt; Erwin Rauch; Michael Riedl. 2021. "Knowledge Transfer and Introduction of Industry 4.0 in SMEs." Research Anthology on Cross-Industry Challenges of Industry 4.0 , no. : 275-302.

Conference paper
Published: 05 June 2020 in Recent Advances in Computational Mechanics and Simulations
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For almost a decade now, production science has been dealing with Industry 4.0. In recent years, a large number of technological innovations have been developed and introduced into practice, enabling the implementation of smart and connected manufacturing systems. Over the next years, researchers and practitioners will face new challenges in Industry 4.0 to achieve the original vision of an intelligent and self-optimizing factory. We are currently at a crossroads between the first level of Industry 4.0, which was characterized by technologically driven innovations, and a future level of Industry 4.0+, which will be based on data-driven innovation. This article introduces these two phases of Industry 4.0 and gives a direction of research trends with growing attention in manufacturing science and practice. In the context of Industry 4.0+, two research directions, in particular, are expected to generate groundbreaking changes in production and its environment. This is, on the one hand, the introduction of Artificial Intelligence into manufacturing and on the other hand the use of nature as inspiration in the form of Biological Transformation.

ACS Style

Erwin Rauch. Industry 4.0+: The Next Level of Intelligent and Self-optimizing Factories. Recent Advances in Computational Mechanics and Simulations 2020, 176 -186.

AMA Style

Erwin Rauch. Industry 4.0+: The Next Level of Intelligent and Self-optimizing Factories. Recent Advances in Computational Mechanics and Simulations. 2020; ():176-186.

Chicago/Turabian Style

Erwin Rauch. 2020. "Industry 4.0+: The Next Level of Intelligent and Self-optimizing Factories." Recent Advances in Computational Mechanics and Simulations , no. : 176-186.

Review
Published: 06 May 2020 in Sustainability
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Industry 4.0 concepts and technologies ensure the ongoing development of micro- and macro-economic entities by focusing on the principles of interconnectivity, digitalization, and automation. In this context, artificial intelligence is seen as one of the major enablers for Smart Logistics and Smart Production initiatives. This paper systematically analyzes the scientific literature on artificial intelligence, machine learning, and deep learning in the context of Smart Logistics management in industrial enterprises. Furthermore, based on the results of the systematic literature review, the authors present a conceptual framework, which provides fruitful implications based on recent research findings and insights to be used for directing and starting future research initiatives in the field of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in Smart Logistics.

ACS Style

Manuel Woschank; Erwin Rauch; Helmut Zsifkovits. A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics. Sustainability 2020, 12, 3760 .

AMA Style

Manuel Woschank, Erwin Rauch, Helmut Zsifkovits. A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics. Sustainability. 2020; 12 (9):3760.

Chicago/Turabian Style

Manuel Woschank; Erwin Rauch; Helmut Zsifkovits. 2020. "A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics." Sustainability 12, no. 9: 3760.

Journal article
Published: 01 May 2020 in Sustainability
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Far from being exclusively related to economic considerations, the advantages of Industry 4.0 applications also include environmental and social concerns. An increasing amount of scientific publications relate the implementation of the fourth industrial revolution paradigm to sustainability. Several studies reported opportunities of Industry 4.0 implementation particularly to the environmental dimension of sustainability, e.g., through improved logistics streams and lowered waste from production. The present research aims at providing evidence on whether manufacturing companies consider Industry 4.0 implementation as an advantage contributing to environmental and social sustainability in terms of lower environmental impact of production, as well as higher physical relief for workers and flexibility of work organisation. The results were an attempt to study such relations with company sizes, industry sectors, turnover and self-assessed levels of digitalization varying. The sample encompasses 65 companies located in the Marche region (Italy). The results show that overall the perception of economic opportunities prevail, while the association of a beneficial impact of Industry 4.0 on environmental sustainability is rather low across companies, regardless of their size, turnover and digital level. As for the statistically significant variables, the results suggest a strong association of the size and the digital level to specific Industry 4.0 related advantages, referring to the social and economic dimension of sustainability, respectively.

ACS Style

Riccardo Brozzi; David Forti; Erwin Rauch; Dominik T. Matt. The Advantages of Industry 4.0 Applications for Sustainability: Results from a Sample of Manufacturing Companies. Sustainability 2020, 12, 3647 .

AMA Style

Riccardo Brozzi, David Forti, Erwin Rauch, Dominik T. Matt. The Advantages of Industry 4.0 Applications for Sustainability: Results from a Sample of Manufacturing Companies. Sustainability. 2020; 12 (9):3647.

Chicago/Turabian Style

Riccardo Brozzi; David Forti; Erwin Rauch; Dominik T. Matt. 2020. "The Advantages of Industry 4.0 Applications for Sustainability: Results from a Sample of Manufacturing Companies." Sustainability 12, no. 9: 3647.

Journal article
Published: 29 April 2020 in Sustainability
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Industrial collaborative robotics is one of the main enabling technologies of Industry 4.0. Collaborative robots are innovative cyber-physical systems, which allow safe and efficient physical interactions with operators by combining typical machine strengths with inimitable human skills. One of the main uses of collaborative robots will be the support of humans in the most physically stressful activities through a reduction of work-related biomechanical overload, especially in manual assembly activities. The improvement of operators’ occupational work conditions and the development of human-centered and ergonomic production systems is one of the key points of the ongoing fourth industrial revolution. The factory of the future should focus on the implementation of adaptable, reconfigurable, and sustainable production systems, which consider the human as their core and valuable part. Strengthening actual assembly workstations by integrating smart automation solutions for the enhancement of operators’ occupational health and safety will be one of the main goals of the near future. In this paper, the transformation of a manual workstation for wire harness assembly into a collaborative and human-centered one is presented. The purpose of the work is to present a case study research for the design of a collaborative workstation to improve the operators’ physical ergonomics while keeping or increasing the level of productivity. Results demonstrate that the achieved solution provides valuable benefits for the operators’ working conditions as well as for the production performance of the companies. In particular, the biomechanical overload of the worker has been reduced by 12.0% for the right part and by 28% for the left part in terms of manual handling, and by 50% for the left part and by 57% for the right part in terms of working postures. In addition, a reduction of the cycle time of 12.3% has been achieved.

ACS Style

Luca Gualtieri; Ilaria Palomba; Fabio Antonio Merati; Erwin Rauch; Renato Vidoni. Design of Human-Centered Collaborative Assembly Workstations for the Improvement of Operators’ Physical Ergonomics and Production Efficiency: A Case Study. Sustainability 2020, 12, 3606 .

AMA Style

Luca Gualtieri, Ilaria Palomba, Fabio Antonio Merati, Erwin Rauch, Renato Vidoni. Design of Human-Centered Collaborative Assembly Workstations for the Improvement of Operators’ Physical Ergonomics and Production Efficiency: A Case Study. Sustainability. 2020; 12 (9):3606.

Chicago/Turabian Style

Luca Gualtieri; Ilaria Palomba; Fabio Antonio Merati; Erwin Rauch; Renato Vidoni. 2020. "Design of Human-Centered Collaborative Assembly Workstations for the Improvement of Operators’ Physical Ergonomics and Production Efficiency: A Case Study." Sustainability 12, no. 9: 3606.

Journal article
Published: 29 April 2020 in Procedia Manufacturing
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During the last decades, Lean Management methodologies established in the manufacturing environment have been applied and adapted to the construction industry under the term “Lean Construction”. Currently, concepts and technologies from Industry 4.0 are mainly transforming the manufacturing industry and only few applications have been implemented to construction and its connected supply chains. This paper shows how new technologies like Building Information Modeling connected with Virtual and Augmented Reality could empower Lean Construction methodologies to increase efficiency during the building execution process. The approach was tested by using the project simulation game Villego® with students from the course “Project Management” of the master degree LM-33 “Industrial Mechanical Engineering” of the Free University of Bozen-Bolzano.

ACS Style

Patrick Dallasega; Andrea Revolti; Philipp Sauer; Felix Schulze; Erwin Rauch. BIM, Augmented and Virtual Reality empowering Lean Construction Management: a project simulation game. Procedia Manufacturing 2020, 45, 49 -54.

AMA Style

Patrick Dallasega, Andrea Revolti, Philipp Sauer, Felix Schulze, Erwin Rauch. BIM, Augmented and Virtual Reality empowering Lean Construction Management: a project simulation game. Procedia Manufacturing. 2020; 45 ():49-54.

Chicago/Turabian Style

Patrick Dallasega; Andrea Revolti; Philipp Sauer; Felix Schulze; Erwin Rauch. 2020. "BIM, Augmented and Virtual Reality empowering Lean Construction Management: a project simulation game." Procedia Manufacturing 45, no. : 49-54.

Journal article
Published: 27 April 2020 in Sustainability
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Industry 4.0 has attracted the attention of manufacturing companies over the past ten years. Despite efforts in research and knowledge transfer from research to practice, the introduction of Industry 4.0 concepts and technologies is still a major challenge for many companies, especially small and medium-sized enterprises (SMEs). Many of these SMEs have no overview of existing Industry 4.0 concepts and technologies, how they are implemented in their own companies, and which concepts and technologies should primarily be focused on future Industry 4.0 implementation measures. The aim of this research was to develop an assessment model for SMEs that is easy to apply, provides a clear overview of existing Industry 4.0 concepts, and supports SMEs in defining their individual strategy to introduce Industry 4.0 in their firm. The maturity level-based assessment tool presented in this work includes a catalog of 42 Industry 4.0 concepts and a norm strategy based on the results of the assessment to support SMEs in introducing the most promising concepts. For testing and validation purposes, the assessment model has been applied in a field study with 17 industrial companies.

ACS Style

Erwin Rauch; Marco Unterhofer; Rafael A. Rojas; Luca Gualtieri; Manuel Woschank; Dominik T. Matt. A Maturity Level-Based Assessment Tool to Enhance the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises. Sustainability 2020, 12, 3559 .

AMA Style

Erwin Rauch, Marco Unterhofer, Rafael A. Rojas, Luca Gualtieri, Manuel Woschank, Dominik T. Matt. A Maturity Level-Based Assessment Tool to Enhance the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises. Sustainability. 2020; 12 (9):3559.

Chicago/Turabian Style

Erwin Rauch; Marco Unterhofer; Rafael A. Rojas; Luca Gualtieri; Manuel Woschank; Dominik T. Matt. 2020. "A Maturity Level-Based Assessment Tool to Enhance the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises." Sustainability 12, no. 9: 3559.

Journal article
Published: 01 April 2020 in Journal of Computational Design and Engineering
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With the increasing trend of the Fourth Industrial Revolution, also known as Industry 4.0 or smart manufacturing, many companies are now facing the challenge of implementing Industry 4.0 methods and technologies. This is a challenge especially for small and medium-sized enterprises, as they have neither sufficient human nor financial resources to deal with the topic sufficiently. However, since small and medium-sized enterprises form the backbone of the economy, it is particularly important to support these companies in the introduction of Industry 4.0 and to develop appropriate tools. This work is intended to fill this gap and to enhance research on Industry 4.0 for small and medium-sized enterprises by presenting an exploratory study that has been used to systematically analyze and evaluate the needs and translate them into a final list of (functional) requirements and constraints using axiomatic design as scientific approach.

ACS Style

Erwin Rauch; Andrew R Vickery. Systematic analysis of needs and requirements for the design of smart manufacturing systems in SMEs☆. Journal of Computational Design and Engineering 2020, 7, 129 -144.

AMA Style

Erwin Rauch, Andrew R Vickery. Systematic analysis of needs and requirements for the design of smart manufacturing systems in SMEs☆. Journal of Computational Design and Engineering. 2020; 7 (2):129-144.

Chicago/Turabian Style

Erwin Rauch; Andrew R Vickery. 2020. "Systematic analysis of needs and requirements for the design of smart manufacturing systems in SMEs☆." Journal of Computational Design and Engineering 7, no. 2: 129-144.

Chapter
Published: 03 January 2020 in Industry 4.0 for SMEs
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Industry 4.0 can be the starting point for implementation projects as a low-risk entry into an adapted digitization strategy. In larger companies, comprehensive digitization initiatives are already integrated into the central corporate strategy, while smaller companies often have problems putting the Industry 4.0 paradigms into practice. As the backbone of the economy, small- and medium-sized enterprises (SMEs) have an enormous leverage effect, which is why it is crucial to develop specific concepts for smaller companies. Regardless of the size of a company, a digital transformation strategy offers opportunities for growth and sustainable competitiveness. This chapter will give an introductory overview of Industry 4.0 as the fourth industrial revolution and discuss the role of SMEs in this transition towards the digital transformation.

ACS Style

Dominik T. Matt; Erwin Rauch. SME 4.0: The Role of Small- and Medium-Sized Enterprises in the Digital Transformation. Industry 4.0 for SMEs 2020, 3 -36.

AMA Style

Dominik T. Matt, Erwin Rauch. SME 4.0: The Role of Small- and Medium-Sized Enterprises in the Digital Transformation. Industry 4.0 for SMEs. 2020; ():3-36.

Chicago/Turabian Style

Dominik T. Matt; Erwin Rauch. 2020. "SME 4.0: The Role of Small- and Medium-Sized Enterprises in the Digital Transformation." Industry 4.0 for SMEs , no. : 3-36.

Chapter
Published: 03 January 2020 in Industry 4.0 for SMEs
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Collaborative robotics, human-machine interaction (HMI), and human–robot collaboration (HRC) introduce a new concept of collaborative workspaces by allowing a mixed manufacturing environment where humans and machines can work hand-in-hand in a safe, ergonomic, and efficient way. The main issue is to ensure operators’ safety and ergonomics when they are collaborating hand-in-hand with high-performance collaborative robots. This chapter shows a case study of human–robot collaborative assembly applied to the production of a pneumatic cylinder in a learning factory laboratory. Starting from an existing situation, the transformation process between pure manual assembly and collaborative assembly is analysed, and the implementation of safe, ergonomic, and efficient solutions for the cell layout and workflow design are discussed. Finally, future improvements are proposed.

ACS Style

Luca Gualtieri; Rafael A. Rojas; Manuel A. Ruiz Garcia; Erwin Rauch; Renato Vidoni. Implementation of a Laboratory Case Study for Intuitive Collaboration Between Man and Machine in SME Assembly. Industry 4.0 for SMEs 2020, 335 -382.

AMA Style

Luca Gualtieri, Rafael A. Rojas, Manuel A. Ruiz Garcia, Erwin Rauch, Renato Vidoni. Implementation of a Laboratory Case Study for Intuitive Collaboration Between Man and Machine in SME Assembly. Industry 4.0 for SMEs. 2020; ():335-382.

Chicago/Turabian Style

Luca Gualtieri; Rafael A. Rojas; Manuel A. Ruiz Garcia; Erwin Rauch; Renato Vidoni. 2020. "Implementation of a Laboratory Case Study for Intuitive Collaboration Between Man and Machine in SME Assembly." Industry 4.0 for SMEs , no. : 335-382.

Chapter
Published: 03 January 2020 in Industry 4.0 for SMEs
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SME manufacturers face the challenge of implementing smart and highly adaptable manufacturing systems to produce individual products at the lowest price and with the shortest lead time. This chapter shows an approach based on an explorative field study combined with Axiomatic Design theory to collect the specific requirements of SMEs introducing Industry 4.0 in their production. Customer/user needs for the design of smart and adaptable SME manufacturing systems are transferred into functional requirements. These functional requirements are then used to define a set of design parameters and guidelines, which are addressed to support practitioners from industry in the implementation of smart manufacturing systems. These guidelines help system designers to improve their design at an early stage before making costly decisions and to reduce complexity to a minimum.

ACS Style

Erwin Rauch; Andrew R. Vickery; Christopher A. Brown; Dominik T. Matt. SME Requirements and Guidelines for the Design of Smart and Highly Adaptable Manufacturing Systems. Industry 4.0 for SMEs 2020, 39 -72.

AMA Style

Erwin Rauch, Andrew R. Vickery, Christopher A. Brown, Dominik T. Matt. SME Requirements and Guidelines for the Design of Smart and Highly Adaptable Manufacturing Systems. Industry 4.0 for SMEs. 2020; ():39-72.

Chicago/Turabian Style

Erwin Rauch; Andrew R. Vickery; Christopher A. Brown; Dominik T. Matt. 2020. "SME Requirements and Guidelines for the Design of Smart and Highly Adaptable Manufacturing Systems." Industry 4.0 for SMEs , no. : 39-72.

Conference paper
Published: 02 December 2019 in MATEC Web of Conferences
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Industry 4.0 and digitization are currently changing shop floor management in production. Especially in the production of highly customized and individual products, digitization offers many opportunities for more efficient processes. Providing the right information in the right time at the right place can help to reduce lead time as well as production costs. This paper shows the use of Axiomatic Design to develop a conceptual design for an innovative and digital shop floor information system for supporting assembly operators in machine industry in their daily work. The research is based on a real industrial case study with a medium sized manufacturer of customized machines. Needs from practice were collected through workshops with the industry partner and were translated into functional requirements. These functional requirements were derived with an Axiomatic Design decomposition to design solutions. The results of the AD analysis were used as a basis for the concept design of an operator information system in the company.

ACS Style

Matthias Tauber; Andreas Gallmetzer; Erwin Rauch; Christopher A. Brown; Dominik T. Matt. Concept Design of a Digital Shop Floor Information System for Assembly Operators in Machine Industry. MATEC Web of Conferences 2019, 301, 00017 .

AMA Style

Matthias Tauber, Andreas Gallmetzer, Erwin Rauch, Christopher A. Brown, Dominik T. Matt. Concept Design of a Digital Shop Floor Information System for Assembly Operators in Machine Industry. MATEC Web of Conferences. 2019; 301 ():00017.

Chicago/Turabian Style

Matthias Tauber; Andreas Gallmetzer; Erwin Rauch; Christopher A. Brown; Dominik T. Matt. 2019. "Concept Design of a Digital Shop Floor Information System for Assembly Operators in Machine Industry." MATEC Web of Conferences 301, no. : 00017.