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Data Mining through Early Experience Prototyping: A step towards Data Driven Product Service System Design
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)
Volvo Construction Equipment, SWE. (Product Development Research Lab)
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)ORCID iD: 0000-0003-4875-391X
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)ORCID iD: 0000-0002-9662-4576
2018 (English)In: IFAC PAPERSONLINE, Elsevier, 2018, Vol. 51, no 11, p. 1095-1100, article id 11Conference paper, Published paper (Refereed)
Abstract [en]

The construction industry is ripe for disruption through innovative solutions that provide added productivity. Equipment manufacturers are attempting to disrupt their industry with investments in autonomy, electrification and product-service system business models. Designing solutions that will operate in completely new systems or modify an existing complex system require new approaches to address the uncertainty of system impacts. An iterative approach can help tackle ambiguity through cyclical validation of design decisions. Data mining in each cycle adds a quantitative dimension to the rationale of decision making, but data is sparse and difficult to collect in parallel with design of theoretical product-service systems operating in future scenarios. This can be combated using experiential prototyping techniques to design flexible infrastructure that supports contextualized data gathering in a variety of focused design sprints using Design, Build and Test approach. The intricacy of designing innovative solutions to increase productivity in the construction industry can be untangled by framing aspects of the problem in small sprints and testing them in a contextualized setting built to generate functional data to drive design.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 51, no 11, p. 1095-1100, article id 11
Series
IFAC PAPERSONLINE, ISSN 2405-8963 ; 51
Keywords [en]
​Product Service System, Data Mining, Experience Prototyping, New Machine Development
National Category
Other Mechanical Engineering
Identifiers
URN: urn:nbn:se:bth-16395DOI: 10.1016/j.ifacol.2018.08.458ISI: 000445651000183OAI: oai:DiVA.org:bth-16395DiVA, id: diva2:1216332
Conference
16th IFAC Symposium on Information Control Problems in Manufacturing, Bergamo
Projects
Model Driven Development and Decision Support
Funder
Knowledge Foundation, 20120278Available from: 2018-06-11 Created: 2018-06-11 Last updated: 2018-10-30Bibliographically approved

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Ruvald, RyanJohansson, ChristianLarsson, Tobias

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