Access the full text.
Sign up today, get DeepDyve free for 14 days.
Frédéric Demoly, Xiu-Tian Yan, B. Eynard, S. Gomes, D. Kiritsis (2012)
Integrated product relationships management: a model to enable concurrent product design and assembly sequence planningJournal of Engineering Design, 23
N. Mortensen, L. Hvam, Anders Haug (2010)
Modelling Product Families for Product Configuration Systems with Product Variant Master
Linda Zhang (2007)
Process platform-based production configuration for mass customization
Marcel Michaelis, H. Johannesson, H. Elmaraghy (2015)
Function and process modeling for integrated product and manufacturing system platformsJournal of Manufacturing Systems, 36
E. Järvenpää, N. Siltala, Otto Hylli, Minna Lanz (2018)
The development of an ontology for describing the capabilities of manufacturing resourcesJournal of Intelligent Manufacturing, 30
J. Ladiges, A. Fay, W. Lamersdorf (2016)
Automated Determining of Manufacturing Properties and Their Evolutionary Changes from Event TracesIntelligent Industrial Systems, 2
T. Brunø, Ann-Louise Andersen, Daniel Sørensen, Kjeld Nielsen, Mads Bejlegaard (2020)
Integrated product-process modelling for platform-based co-developmentInternational Journal of Production Research, 58
H. Wiendahl, H. Elmaraghy, P. Nyhuis, M. Zäh, Hans-Hermann Wiendahl, N. Duffie, M. Brieke (2007)
Changeable Manufacturing - Classification, Design and OperationCirp Annals-manufacturing Technology, 56
P. Johannesson, E. Perjons (2014)
A Method Framework for Design Science Research
H. Kagermann, J. Helbig, A. Hellinger, W. Wahlster (2013)
Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group
M. Hansson, E. Järvenpää, N. Siltala, O. Madsen (2017)
Modelling Capabilities for Functional Configuration of Part Feeding EquipmentProcedia Manufacturing, 11
S. Bagchi, Jighyasu Gaur (2017)
Optimization of postponement process for a two stage modular manufacturer, 11
O. Madsen, Charles Møller (2017)
The AAU Smart Production Laboratory for Teaching and Research in Emerging Digital Manufacturing TechnologiesProcedia Manufacturing, 9
R. Heinrich, Sandro Koch, Suhyun Cha, Kiana Busch, Ralf Reussner, B. Vogel‐Heuser (2018)
Architecture-based change impact analysis in cross-disciplinary automated production systemsJ. Syst. Softw., 146
R. Drath, A. Horch (2014)
Industrie 4.0: Hit or Hype? [Industry Forum]IEEE Industrial Electronics Magazine, 8
Christoffer Levandowski, J. Jiao, H. Johannesson (2015)
A two-stage model of adaptable product platform for engineering-to-order configuration designJournal of Engineering Design, 26
Marcel Michaelis, H. Johannesson (2012)
From Dedicated to Platform-Based Co-Development of Products and Manufacturing Systems
J. Backhaus, G. Reinhart (2017)
Digital description of products, processes and resources for task-oriented programming of assembly systemsJournal of Intelligent Manufacturing, 28
R. Singh, Pravin Kumar (2019)
Measuring the flexibility index for a supply chain using graph theory matrix approachJournal of Global Operations and Strategic Sourcing
Senthil Chandrasegaran, K. Ramani, Ram Sriram, I. Horváth, A. Bernard, R. Harik, Wei Gao (2013)
The evolution, challenges, and future of knowledge representation in product design systemsComput. Aided Des., 45
M. Aldanondo, É. Vareilles (2008)
Configuration for mass customization: how to extend product configuration towards requirements and process configurationJournal of Intelligent Manufacturing, 19
P. Pitiot, M. Aldanondo, É. Vareilles (2014)
Concurrent product configuration and process planning: Some optimization experimental resultsComput. Ind., 65
Junkai He, F. Chu, Feifeng Zheng, Ming Liu, C. Chu (2019)
A multi-objective distribution-free model and method for stochastic disassembly line balancing problemInternational Journal of Production Research, 58
H. Elmaraghy, H. Wiendahl (2009)
Changeability – An Introduction
H. Elmaraghy, G. Schuh, W. ElMaraghy, F. Piller, P. Schönsleben, M. Tseng, A. Bernard (1998)
Product Variety ManagementCirp Annals-manufacturing Technology, 62
S. Hu, Jeonghan Ko, L. Weyand, H. Elmaraghy, T. Lien, Y. Koren, H. Bley, G. Chryssolouris, N. Nasr, M. Shpitalni (2011)
Assembly system design and operations for product varietyCIRP Annals, 60
S. Mortensen, O. Madsen (2018)
A Virtual Commissioning Learning PlatformProcedia Manufacturing, 23
Elise Gruhier, Frédéric Demoly, Olivier Dutartre, S. Abboudi, S. Gomes (2015)
A formal ontology-based spatiotemporal mereotopology for integrated product design and assembly sequence planningAdv. Eng. Informatics, 29
Yang Lu (2017)
Industry 4.0: A survey on technologies, applications and open research issuesJ. Ind. Inf. Integr., 6
H. Lasi, P. Fettke, H.-G. Kemper, T. Feld, M. Hoffmann (2014)
Industry 4.0Business & Information Systems Engineering, 6
(2017)
About the unified modeling language specification version 2.5.1
The purpose of this paper is to investigate how necessary changes in a manufacturing system can be determined based on a new product specification. It proposes a formal modelling approach, enhancing the utilization of changeability of a manufacturing system given a set of changes in a product.Design/methodology/approachTo develop the proposed modelling approach, a design science research method is used to iteratively frame an issue, develop a solution and evaluate it in a relevant environment. Evaluation is carried out through a case study.FindingsA stepwise method is introduced, facilitating the creation of a model describing the relations between product characteristics within a product family and the changeability of a manufacturing system. Limitations of each manufacturing system module are evaluated to determine permittable changes in the product domain. This establishes clear relations between product attributes and manufacturing capabilities. Through this, users receive feedback on which parts of the manufacturing system must change, depending on changes in product attributes.Research limitations/implicationsTesting has been carried out in an academic learning factory setting. Products and processes are thus less complicated than an industrial setting. The system used for validation is highly modular by design.Practical implicationsThe proposed approach could be used during product development, when determining characteristics and variety of new products, evaluating the consequences of changing the solution space. This implies a shorter time-to-market and lower product costs.Social implicationsFaster product development and shorter time-to-market would give manufacturers increased agility to track market needs, and ultimately lead to greater fulfilment of customer requirements.Originality/valueThe current body of literature focus on modelling either products or manufacturing systems. Little literature addresses both, but does not touch on identifying changes within parts of the manufacturing system, nor supports the high changeability proposed in this research.
Journal of Global Operations and Strategic Sourcing – Emerald Publishing
Published: Nov 30, 2021
Keywords: Qualitative; Process modelling; Industry 4.0; Product modelling; Manufacturing system; Changeability; Changeable manufacturing; Reconfigurable manufacturing
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.