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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: 2019-12-03Bibliographically approved
In thesis
1. Prototyping for Product-Service Systems innovation: Insights from the construction equipment industry
Open this publication in new window or tab >>Prototyping for Product-Service Systems innovation: Insights from the construction equipment industry
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

To radically increase the value delivered to the customers in the construction industry a concerted effort is needed to develop solutions beyond incremental adjustments. Simply providing add-on services to existing products does not effectively create solutions with enough gains in core customer values. Designing and developing a product service system (PSS) through the adjustment or reconfiguration of existing elements is a challenge on its own, and adding the design of new elements serves to confound the process even further. By realigning all components of a PSS from inception to a function provides an opportunity to escape current product limitations and explore new solutions with potentially higher value. Designing a new PSS solution from scratch comes with added ambiguity in an expanded solution space.

The aim of this thesis is to investigate early conceptual phases of PSS innovation within the domain of construction equipment manufacturing. The research included the development and testing of a prototyping method to foster customer co-creation and transdisciplinary design which are considered primary impact factors increasing the value of final PSS solutions.

The work was performed in collaboration with a construction equipment manufacturer, conducting a demonstrator project on an electric and autonomous production site. The thesis first depicts how the prototyping method can be implemented to enable stakeholder insights that were previously not accessible through current practices. This leads to the testing of the method in a broader perspective to represent tangible and intangible elements in a way that facilitates concept design decisions in multi-disciplinary settings. The thesis concludes by exploring the limitations on current practices in relation to the adoption and potential use of the method.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019. p. 50
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 19
Keywords
Product-Service System, Engineering Design, Prototyping, Boundary Objects
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:bth-18964 (URN)978-91-7295-395-6 (ISBN)
Opponent
Supervisors
Available from: 2019-11-29 Created: 2019-11-29 Last updated: 2019-12-18Bibliographically approved
2. A Step Towards the Design of Collaborative Autonomous Machines: A Study on Construction and Mining Equipment
Open this publication in new window or tab >>A Step Towards the Design of Collaborative Autonomous Machines: A Study on Construction and Mining Equipment
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Fully autonomous construction and mining machines are not science fiction anymore. For special applications, these types of machinery are well known for several years. The construction and mining industries are ripe for innovative product and service offers, including automated and fully autonomous machines at a larger scale. Nevertheless, commercially available autonomous machines for the main markets are still rare. Driven by the advancements in sensor technology, increased connectivity, and on-board computational capabilities, automation of machine functions and subsystems led to the development of advanced operator-assistant functions in certain fields like material handling, predictive maintenance, and operator guidance. Semi-automated machines, supporting the machine operator during normal operation, are well accepted by users and customers and show beneficial effects on the productivity of the machine and the overall work process. The purpose of this thesis is to generate a deeper understanding of the specific requirements needed to support the design decisions during the development of fully autonomous machines. Complementary, deeper insights into the efficient collaboration between autonomous machines and human collaborators are explored.

The thesis summarizes the research performed by the author, as an industrial Ph.D. student and Specialist for Intelligent Machines at Volvo Construction Equipment. Performed research comprises the investigation of the state-of-the-art approaches in the automation of machines and dedicated functions with special emphasis on the connectivity of the different systems and components up to the site management solution. Further, the work includes the exploration of data-mining through early experience prototyping as a step towards data-driven design of a product-service system. In additional the research covered the support of on-site collaboration between autonomous machines and humans by investigating team behavior and trust development among humans.

Conclusions from this work are that autonomous machine design requires new sets of requirements to support early decision making during the development process. Dedicated data collection based on different methods such as, data-mining, needfinding, and observations, supported by multiple physical and virtual artifacts can generate useful data to support the decision-making. Trust between humans and machines, and the preconditions of developing this trust need to be captured as specific requirements. To support further development in the area of autonomous machine design, an interaction model had been proposed to map possible interactions of an autonomous machine with objects and collaborators within the same work area. To capture the different nature of the possible interactions, several levels had been introduced to enable the distinction between cognitive, and physical, as well as intended, and unintended interactions.

 

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 17
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:bth-18944 (URN)978-91-7295-393-2 (ISBN)
Presentation
2019-12-19, J1650, Campus Gräsvik, Karlskrona, 15:00 (English)
Opponent
Supervisors
Available from: 2019-11-21 Created: 2019-11-21 Last updated: 2019-12-18Bibliographically approved

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Ruvald, RyanJohansson, ChristianLarsson, Tobias

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