TY - GEN A1 - Kilimis, Panagiotis A1 - Zou, Wenchao A1 - Lehmann, Marlon Antonin A1 - Berger, Ulrich T1 - A Survey on Digitalization for SMEs in Brandenburg, Germany T2 - 9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019: Berlin, Germany, 28–30 August 2019 N2 - Digitalization is widely accepted as a principal technological strategy and is expected to vastly impact and transform industry, predominantly by a substantial improvement of the entire value chain. However, its implementation process remains slow, in particular for small and medium-sized enterprises (SMEs), as they tend to have misconceptions about the complexity and expense of digitalization. The purpose of this research is to analyze factors that affect Brandenburg-State, DEU SMEs in their decision making process for an effective implementation of digital technologies in their daily business routine. The results of this study are based on a survey that was conducted in cooperation with fifty SMEs, which currently face problems in the areas of enterprise resource planning (ERP), CAD/CAM, automation, logistics and production/factory planning. Ten of these SMEs have decided to invest in digitalization measures and started the implementation process. Three of them were chosen for the case study to evaluate potential benefits, trade-offs and barriers hampering the implementation of digitalization technologies. These three companies are considered representative items, since their needs and measures investigated were identical to most of the companies of this survey. It was found that the overwhelming majority of the companies regard ERP implementation as their highest priority when investing in the most cost-effective technology. Y1 - 2019 U6 - https://doi.org/10.1016/j.ifacol.2019.11.522 SN - 2405-8963 VL - 52 IS - 13 SP - 2145 ER - TY - RPRT A1 - Schmitt, Randolf A1 - Borck, Christian A1 - Hentschel, Christian A1 - Berger, Ulrich T1 - Lightweight digital shadow concept for batch size one products and modular shopfloors N2 - The Digital Twin is seen as the step towards digitalization in many areas, including the area of manufacturing which is the focus of this paper. However, the frequently application-oriented development of concepts and initial implementations make it difficult to adapt them to other applications. Especially when production deviates from the usual highly automated processes and requires high flexibility, e.g. to allow batch size one. In such a case, the Digital Twin must support modular shopfloors with flexible areas in which different production times and various tools and machines are used. It should also be possible to react promptly to problems in production. Design errors that only become apparent during production must be reported directly. In order to deal with this problem, the paper presents a concept for an abstract representation of a Digital Shadow (DS). The DS combines the disciplines of production planning and control, product lifecycle and layout planning which creates new links and enables further application scenarios. Based on this Digital Shadow, different applications can be realized that provide user-related solutions. For this purpose, a tree structure is used that links information about the product and the production environment which in this case is variable. KW - Digital Shadow KW - Digital Twin KW - Flexible Manufacturing KW - Industry 4.0 KW - SME Y1 - 2020 U6 - https://doi.org/10.26127/BTUOpen-5220 ER - TY - GEN A1 - Borck, Christian A1 - Schmitt, Randolf A1 - Berger, Ulrich A1 - Hentschel, Christian 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 - Development of a IIoT Platform for Industrial Imaging Sensors 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 - In the industry, connecting machines and tools - also known as the industrial Internet of things (IIoT) - is an essential part of the digital transformation of a company. The aim is to increase the efficiency and predictability of complex processes. In manual and semi-automatic processes, imaging sensors can help to monitor conditions, gives automated feedbacks to a central system, and e.g. provide current information for a digital twin. However, when imaging sensors are integrated into established IIoT platforms, they quickly reach their system limits due to the multidimensionality and high update and data rates. This paper presents a software platform that enables decoupled automated image processing through the abstraction and contextualization of the sensor technology and its data as well as a plugin architecture. Analogous to edge computing, partial processing can already be performed close to the sensor node to condensate data and reduce network loads and latencies. Thereby, all these approaches increase the longevity, flexibility and scalability of multi-sensor systems and associated processing algorithms. Based on the generic structure of the sensor network, the user is provided with an intuitive user interface that is based on IIoT platforms and enables the integration of their processing pipelines even for non-experts, despite the high complexity of the data. Y1 - 2021 SN - 978-3-030-90699-3 SN - 978-3-030-90702-0 U6 - https://doi.org/10.1007/978-3-030-90700-6_37 SP - 330 EP - 338 PB - Springer CY - Cham ER - TY - CHAP A1 - Bilous, Vadym A1 - Städter, Philipp A1 - Gebauer, Marc A1 - Berger, Ulrich ED - Schüppstuhl, Thorsten ED - Tracht, Kirsten ED - Raatz, Annika T1 - Usage of Augmented Reality for Improved Human-Machine Interaction and Real-Time Error Correction of Laboratory Units T2 - Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021 KW - Augmented reality KW - Error correction KW - Human-machine interaction KW - Industry 4.0 KW - Technical assistance systems KW - Data transfer Y1 - 2022 SN - 978-3-030-74031-3 U6 - https://doi.org/10.1007/978-3-030-74032-0_22 SP - 263 EP - 274 PB - Springer CY - Cham ER - TY - GEN A1 - Berger, Ulrich A1 - Lehmann, Marlon Antonin A1 - Porsch, Ronny T1 - Selbstlernende Assistenzsysteme für Industrieroboter T2 - Industrie 4.0 Management N2 - Intelligente Assistenzsysteme unterstützen die Mitarbeiter in der Produktion und erhöhen die Effizienz durch das Einblenden von situationsbasierten Aufgabeninformationen. Im Projekt Advanced Robot Assistance Solution (ARAS) im Rahmen des Kuka Innovation Awards 2021 wurde eine Assistenztechnologie entwickelt, um automatisiert Roboterprogramme für Montageabläufe zu generieren. Durch innovative Mensch-Maschine-Schnittstellen werden Montageschritte per maschinellem Lernen erkannt und in ausführbare Programme für Industrieroboter übersetzt. Dadurch können roboterbasierte Montageprozesse innerhalb von Minuten auf neue Produkte angepasst werden, ohne dass die Mitarbeiter über Kenntnisse des Programmierens oder der Robotik verfügen müssen. Ein Mitarbeiter muss den Montageprozess nur einmal vormachen. Das ARAS-System ermöglicht die kosten- und zeiteffiziente Integration und Adaption von Industrierobotern in der Montage für große und mittelständische Unternehmen. Y1 - 2021 SN - 2364-9208 VL - 37 IS - 6 SP - 23 EP - 26 ER - 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 -