Data Mining through Early Experience Prototyping -A step towards Data Driven Product Service System Design. Issue 11 (2018)

• Record Type: Journal Article
• Authors: Ruvald, Ryan; Frank, Martin; Johansson, Christian; Larsson, Tobias
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 11(2018)
• Page Start: 1095
• Page End: 1100
• Publication Date: 2018
• Subjects: Product Service System -- Data Mining -- Experience Prototyping -- New Machine Development; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.08.458
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: 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.