TY - GEN A1 - Schou, Casper A1 - Colli, Michele A1 - Berger, Ulrich A1 - Heidemann Lassen, Astrid A1 - Madsen, Ole A1 - Møller, Charles A1 - Vejrum Wæhrens, Brian ED - Andersen, Ann-Louise ED - Andersen, Rasmus ED - Brunoe, Thomas Ditlev ED - Stoettrup Schioenning Larsen, Maria ED - Nielsen, Kjeld ED - Napoleone, Alessia ED - Kjeldgaard, Stefan T1 - Deconstructing Industry 4.0: Defining the Smart Factory T2 - Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems : Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2021) and the 10th World Mass Customization & Personalization Conference (MCPC2021), Aalborg, Denmark, October/November 2021 N2 - The advent of the industrial digital transformation and the related technologies of the Industry 4.0 agenda has uncovered new concepts and terminology in the manufacturing domain. Clear definitions represent a solid foundation for supporting the manufacturing research community in addressing this field consistently. This paper addresses this need focusing on the “smart factory”. Starting from a review of the extant literature and integrating it with the outcome of a Delphi study, we propose a new definition of a “smart factory” and discuss its key characteristics. These are related to interconnectivity capabilities and adaptability to the surrounding environment in order to generate and appropriate value. Eventually, such characteristics are exemplified in an empirical context. The aim of this paper is to provide the research community with an updated definition of a smart factory taking both industrial and societal values into account. Furthermore, it may represent a reference for practitioners engaged in the digital transformation of their factories. Y1 - 2021 UR - https://link.springer.com/book/10.1007/978-3-030-90700-6 SN - 978-3-030-90699-3 U6 - https://doi.org/10.1007/978-3-030-90700-6_40 SP - 356 EP - 363 PB - Springer CY - Cham ER - TY - GEN A1 - Madsen, Ole A1 - Berger, Ulrich A1 - Cavalieri, Sergio A1 - Krüger, Volker T1 - Introduction to the Minitrack on Transforming Traditional Production Systems into Smart Production Systems T2 - Hawaii International Conference on System Sciences 2020 : Proceedings of the 53rd Annual Hawaii International Conference on System Sciences N2 - This minitrack will address scientific and technical research on how traditional production systems are transformed into next generation smart production systems. It comprises a mix of presentations from leading industries (automotive and aircraft) as well as from well-known research institutions (Fraunhofer society, Germany) and universities (Brandenburg University of Technology Cottbus-Senftenberg, University of Bergamo, Aalborg University). The minitrack will foster discussions concerning the strategies companies are adopting for managing such transformation, the need for new competences for sustaining it, the implementation of new digital technologies and their impact on the existing production systems. Y1 - 2020 SN - 978-0-9981331-3-3 U6 - https://doi.org/10.24251/HICSS.2020.560 SN - 1530-1605 SP - 4579 EP - 4580 ER - TY - GEN A1 - Colli, Michele A1 - Madsen, Ole A1 - Berger, Ulrich A1 - Møller, Charles A1 - Vejrum Wæhrens, Brian A1 - Bockholt, Markus T1 - Contextualizing the outcome of a maturity assessment for Industry 4.0 T2 - 16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 : Bergamo, Italy, 11–13 June 2018 N2 - The transformation of the manufacturing sector towards Industry 4.0 is setting the scene for a major industrial change. Currently, the need for assisting companies in this transformation is covered by a number of maturity models that assess their digital maturity and provide indications accordingly. However, in order to provide operational recommendations to diverse companies, there is a need for making the assessment company-specific. To cope with this challenge, this paper provides an illustration of a new digital maturity assessment approach - 360 Digital Maturity Assessment - which is based on the Problem Based Learning (PBL) model. Y1 - 2018 U6 - https://doi.org/10.1016/j.ifacol.2018.08.343 SN - 1474-6670 SN - 2405-8963 VL - 51 IS - 11 SP - 1347 EP - 1352 ER - TY - CHAP A1 - Sarivan, Ioan-Matei A1 - Baumann, Stefan Andreas A1 - Díez Álvarez, Daniel A1 - Euteneuer, Felix A1 - Reichenbach, Matthias A1 - Berger, Ulrich A1 - Madsen, Ole A1 - Bøgh, Simon ED - Weißgraeber, Philipp ED - Heieck, Frieder ED - Ackermann, Clemens T1 - Deep Learning-Enabled Real Time In-Site Quality Inspection Based On Gesture Classification T2 - Advances in Automotive Production Technology – Theory and Application; Stuttgart Conference on Automotive Production (SCAP2020) N2 - In this paper we present a novel method for performing in site real time quality inspection (QI) and consequently, digitalization of manual processes performed by human workers. It complements and improves our previous work in this area, which makes use of telemetry gathered from a smartwatch to classify manual actions as successful or unsuccessful. This new methodology provides the worker with a real time capable, robust and more accurate quality inspector. This work enhances the existing system through the elimination of input from the user by making use of a BIOX bracelet that detects gestures. The signal processing and classification methods are simplified and optimised by using assembled neural networks thus merging together the data gathered from multiple signal sources. Consequently, the overall QI system is improved with around 70%, thus furthering the necessary development needed to have a system ready to be used on a production environment. Y1 - 2021 SN - 978-3-662-62961-1 U6 - https://doi.org/10.1007/978-3-662-62962-8_26 SP - 221 EP - 229 PB - Springer CY - Berlin ER - TY - GEN A1 - Colli, Michele A1 - Berger, Ulrich A1 - Bockholt, Markus A1 - Madsen, Ole A1 - Møller, Charles A1 - Vejrum Wæhrens, Brian T1 - A maturity assessment approach for conceiving context-specific roadmaps in the Industry 4.0 era T2 - Annual Reviews in Control N2 - The digital transformation of the production sector is setting the scene for a major industrial change. The need for supporting companies in this transformation is currently covered by several maturity models, generally operationalized through standardized questionnaires, which provide, as an outcome, an assessment of the current maturity stage and a set of general improvement recommendations according to it. However, to provide companies with a more tangible support, there is a need for more individual approach. In order to deal with this need, this paper proposes, following a design science research framework, a novel approach based on Problem-Based Learning for structuring the assessment procedure as a dialectic process. This approach aims at facilitating the contextualization of the assessed company and, consequently, the identification of context-specific improvement recommendations. The proposed approach, supported by a maturity model used for framing information collected during the assessment process, is tested in three industrial cases. Although these have been assessed at the same maturity stage, different improvement recommendations have been proposed according to contextual factors such as strategic goals, core processes and key performance indicators. Y1 - 2019 U6 - https://doi.org/10.1016/j.arcontrol.2019.06.001 SN - 1367-5788 SN - 1872-9088 VL - Vol. 48 SP - 165 EP - 177 ER - TY - CHAP A1 - Borck, Christian A1 - Schmitt, Randolf A1 - Berger, Ulrich A1 - Hentschel, Christian T1 - IIoT and Smart Sensors in Human-Centered Manufacturing T2 - The Future of Smart Production for SMEs N2 - Borck et al. evaluate the challenges and opportunities of Industrial Internet of Things (IIoT) and smart sensors in human-centered manufacturing. Particularly in small and medium-sized manufacturing with fewer machines and smart tools, it is significantly more difficult to automate processes and get the required information from the shop floor. Therefore, they give proven recommendations for the use of sensors based on a set of frequently occurring tasks in assembly, maintenance and logistics to achieve the support of smart data models in the context of Industry 4.0. “IIoT and smart sensors in human-centered manufacturing” concludes with concrete sample scenarios and describe the challenges and one solution using smart sensors and data models. Y1 - 2022 SN - 978-3-031-15427-0 SN - 978-3-031-15428-7 U6 - https://doi.org/10.1007/978-3-031-15428-7_18 SP - 213 EP - 224 PB - Springer Nature Switzerland AG CY - Schweiz ER - TY - GEN A1 - Walter, Elias Fabian A1 - Günther, Norman A1 - Prell, Bastian A1 - Wilbers, Simon A1 - Reiter, Philipp A1 - Reiff-Stephan, Jörg A1 - Berger, Ulrich T1 - Optimierung visueller Benutzeroberflächen zur Stressreduzierung T2 - Tagungsband AALE 2023 N2 - Durch die Menschzentrierung in der Industrie 5.0 [1] sollten bestehende Ansätze hinterfragt und geprüft werden [2]. Gerade der, durch die Digitalisierung hervorgerufene, Technostress sollte neben dem Fachkräftemangel einen zunehmenden Betrachtungsfaktor im Produktionsumfeld erhalten. Da trotz bisheriger Maßnahmen eine stetige Zunahme von Stress zu verzeichnen ist [3]. Auffällig sind dabei die Arbeitsunfähigkeits-Fehltage, welche im letzten Jahr um weitere 6 % bzw. um 18,2 Fehltagegestiegen sind. Womit durchschnittlich jede Erwerbsperson 3,17 Tage unter der Diagnose „psychische Störung“ krankgeschrieben wurde [4]. Um diesen Trend entgegenzuwirken, betrachtet der Beitrag die Möglichkeiten der Software-Ergonomie, womit die Gestaltung von HMIs (Mensch-Maschinen-Interfaces) den Menschen gezielter berücksichtigt um etwaige Belastungen zu reduzieren [5]. Im Rahmen der komplementären Industrie 4.0 und der einhergehenden Informationsflut, bestimmen immer komplexer werdende Schnittstellen und Bedienoberflächen einen Großteil des Arbeitsalltags. Diese ermöglichen den Anwenderinnen und Anwendern neben einem schnellen Überblick über Maschinendaten, Prozessabläufe und Handlungsempfehlungen die Möglichkeit zur einfachen Bedienung der technischen Anlagen. Der hier vorgestellte Ansatz betrachtet am Beispiel einer Bestandsanlage, wo sich Potenziale in der Stressreduzierung im Bereich der visuellen Benutzerschnittstellen befinden und welche Auswirkungen eine Veränderung der Leitführung ermöglicht. Hierfür wurde eine mehrphasige Studie durchgeführt dessen Ergebnisse im Bereich des Eye-Trackings sowie anhand von Vitalwerten im vorliegenden Beitrag diskutiert werden. Y1 - 2023 SN - 978-3-910103-01-6 U6 - https://doi.org/10.33968/2023.13 SP - 119 EP - 129 PB - Hochschule für Technik, Wirtschaft und Kultur Leipzig CY - Luxemburg ER - TY - CHAP A1 - Møller, Charles A1 - Madsen, Ole A1 - Berger, Ulrich A1 - Shou, Casper A1 - Heidemann Lassen, Astrid A1 - Vejrum Wæhrens, Brian T1 - The Smart Production Vision T2 - The Future of Smart Production for SMEs: A Methodological and Practical Approach Towards Digitalization in SMEs N2 - In this chapter, the Smart Production vision is discussed. The Smart Production approach is developed and described, and Smart Production is positioned in relation to Industry 4.0. Smart Production operationalize the journey towards Industry 4.0 and beyond. First, the need for a new approach to manufacturing is discussed, and from the perspectives of Industry 4.0, the Smart Production concept is derived. Then the framework is explored and finally, the approach is outlined. The Smart Production vision is an approach to make an integrated production system smarter by continuous digitizing, automating, and organizing towards supporting the company specific missions. Y1 - 2022 SN - 978-3-031-15428-7 SP - 13 EP - 28 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Berger, Ulrich A1 - Madsen, Ole ED - Madsen, Ole ED - Berger, Ulrich ED - Møller, Charles ED - Heidemann Lassen, Astrid ED - Vejrum Wæhrens, Brian T1 - Introduction to Part 2 - Transformation of SMEs Toards Smart Production T2 - The Future of Smart Production for SMEs: A Methodological and Practical Approach Towards Digitalization in SMEs N2 - This chapter will introduce the second part of the book. This part contains a collection of chapters aimed at supporting the SMEs in the transformation toward the Smart Production vision. In this part, different approaches are presented, which can assist SMEs in the formulation of a smart production vision and in the identification and prioritization of relevant initiatives, guiding the outline of a project roadmap. Furthermore, the part will introduce different regional innovation platforms in Denmark and Germany which support the SME transformations. Finally, it will be discussed how subscription-based methods could be used by SMEs to cut upfront investments and reduce requirements for digital competencies. Y1 - 2022 SN - 978-3-031-15428-7 SP - 69 EP - 75 PB - Springer International Publishing CY - Cham ER -