@misc{ColliBergerBockholtetal., author = {Colli, Michele and Berger, Ulrich and Bockholt, Markus and Madsen, Ole and M{\o}ller, Charles and Vejrum W{\ae}hrens, Brian}, title = {A maturity assessment approach for conceiving context-specific roadmaps in the Industry 4.0 era}, series = {Annual Reviews in Control}, volume = {Vol. 48}, journal = {Annual Reviews in Control}, issn = {1367-5788}, doi = {10.1016/j.arcontrol.2019.06.001}, pages = {165 -- 177}, abstract = {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.}, language = {en} } @incollection{MollerMadsenBergeretal., author = {M{\o}ller, Charles and Madsen, Ole and Berger, Ulrich and Shou, Casper and Heidemann Lassen, Astrid and Vejrum W{\ae}hrens, Brian}, title = {The Smart Production Vision}, series = {The Future of Smart Production for SMEs: A Methodological and Practical Approach Towards Digitalization in SMEs}, booktitle = {The Future of Smart Production for SMEs: A Methodological and Practical Approach Towards Digitalization in SMEs}, publisher = {Springer International Publishing}, address = {Cham}, isbn = {978-3-031-15428-7}, pages = {13 -- 28}, abstract = {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.}, language = {en} } @misc{ColliMadsenBergeretal., author = {Colli, Michele and Madsen, Ole and Berger, Ulrich and M{\o}ller, Charles and Vejrum W{\ae}hrens, Brian and Bockholt, Markus}, title = {Contextualizing the outcome of a maturity assessment for Industry 4.0}, series = {16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 : Bergamo, Italy, 11-13 June 2018}, volume = {51}, journal = {16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018 : Bergamo, Italy, 11-13 June 2018}, number = {11}, issn = {1474-6670}, doi = {10.1016/j.ifacol.2018.08.343}, pages = {1347 -- 1352}, abstract = {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.}, language = {en} } @misc{SchouColliBergeretal., author = {Schou, Casper and Colli, Michele and Berger, Ulrich and Heidemann Lassen, Astrid and Madsen, Ole and M{\o}ller, Charles and Vejrum W{\ae}hrens, Brian}, title = {Deconstructing Industry 4.0: Defining the Smart Factory}, series = {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}, journal = {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}, editor = {Andersen, Ann-Louise and Andersen, Rasmus and Brunoe, Thomas Ditlev and Stoettrup Schioenning Larsen, Maria and Nielsen, Kjeld and Napoleone, Alessia and Kjeldgaard, Stefan}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-90699-3}, doi = {10.1007/978-3-030-90700-6_40}, pages = {356 -- 363}, abstract = {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.}, language = {en} }