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Modeling resale value of road compaction equipment: a data mining approach
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)ORCID iD: 0000-0002-5076-3300
2018 (English)In: IFAC PAPERSONLINE, Elsevier, 2018, Vol. 51, no 11, p. 1101-1106, article id no.11Conference paper, Published paper (Refereed)
Abstract [en]

Resale value is an important aspect to be addressed when companies aim to shift from one-sale models to Product Service Systems (PSS). In the initial stages of the PSS design process, it is beneficial to predict how the mechanical features of the PSS hardware will impact resale value, so to orient business strategy decisions accordingly. The objective of this work is to propose a methodology to model the resale value of road compaction equipment using data mining techniques. By scrapping and merging data sets from the machine manufacturer and from dealers of second-hand machines, the work discusses how the derived correlations may be used to populate value models for early stage decision making.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 51, no 11, p. 1101-1106, article id no.11
Series
IFAC PAPERSONLINE, ISSN 2405-8963 ; 51
Keywords [en]
Data-driven decision making, product service system, new product development, decision support systems, data mining.
National Category
Other Mechanical Engineering
Identifiers
URN: urn:nbn:se:bth-16393DOI: 10.1016/j.ifacol.2018.08.457ISI: 000445651000184OAI: oai:DiVA.org:bth-16393DiVA, id: diva2:1216300
Conference
16th IFAC Symposium on Information Control Problems in Manufacturing
Projects
Model Driven Development and Decision Support
Funder
Knowledge FoundationAvailable from: 2018-06-11 Created: 2018-06-11 Last updated: 2020-02-05Bibliographically approved
In thesis
1. A data-driven approach for Product-Service Systems design: Using data and simulation to understand the value of a new design concept
Open this publication in new window or tab >>A data-driven approach for Product-Service Systems design: Using data and simulation to understand the value of a new design concept
2020 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Global challenges such as increasingly competitive markets, low-cost competition, shorter lead time demands, and high quality/value output are transforming the business model of the company to focus beyond the performance requirements. In order to meet these challenges, companies are highly concerned with the customer perceived value, which is to connect the product with the customer in a better way and become more proactive to fulfil the customer needs, via function-oriented business models and Product-Service Systems.

In literature, the conceptual phase is distinguished as the most critical phase of the product development process. Many authors have recognized the improvement of design in the conceptual phase as the mean to deliver a successful product in the market. At the decision gate, where concepts are selected for further development, the design team needs knowledge/data about the long-term consequences of their early decision, to see how changes in design propagate to the entire lifecycle of the product.

The main goal of the thesis is to describe how the design of Product-Service Systems in the conceptual phase can be improved through the use of a data-driven approach. The latter provides an opportunity to enhance decision making and to provide better support at the early development phase. The study highlights how data are managed and used in current industrial setting and indicates the room for improvement with current practices. The thesis further provides guidelines to efficiently use data into the modelling and simulation activities to increase design knowledge. As a result of this study, a data-driven approach emerged to support the early design decision.

 The thesis presents initial descriptive study findings from the empirical investigations, showing a model-based approach that creates awareness about the value of a new design concept, thus acting as a key enabler to use data in design. This will create a link between the product engineering characteristic to the high-level attributes of customer satisfaction and provider’s long-term profitability. The preliminary results indicate that the application of simulation models to frontload the early design stage creates awareness about how performance can lead to value creation, helping multidisciplinary teams to perform quick trade-off and what-if analysis on design configurations. The proposed framework shows how data from various sources are used through a chain of simulations to understand the entire product lifecycle. The proposed approach holds a potential to improve the key performance indicators for Product-Service Systems development: lead time, design quality, cost and most importantly deliver a value-added product to the customer.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2020.: Blekinge Tekniska Högskola, 2020
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 1
Keywords
Engineering design, data-driven design, conceptual phase, Value-Driven Design, Product-Service Systems, Ingenjörsdesign, datadriven design, konceptuell fas, värdedriven design, data mining
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:bth-19036 (URN)978-91-7295-397-0 (ISBN)
Presentation
2020-02-28, 1650, Campus Gräsvik, Karlskrona, 10:00 (English)
Opponent
Supervisors
Projects
Model Driven Development and Decision Support
Funder
Knowledge Foundation
Available from: 2019-12-18 Created: 2019-12-18 Last updated: 2020-02-26Bibliographically approved

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fulltext(530 kB)140 downloads
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Chowdhery, Syed AzadBertoni, Marco

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