Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89051
Title: Towards an automatic engineering change management in smart product-service systems – A DSM-based learning approach
Authors: Zheng, Pai
Shang, Suiyue
Chen, Chun-Hsien
Keywords: Design Structure Matrix
Product Service Systems
DRNTU::Engineering::Mechanical engineering
Issue Date: 2019
Source: Zheng, P., Chen, C.- H., & Shang, S. (2019). Towards an automatic engineering change management in smart product-service systems - A DSM-based learning approach. Advanced Engineering Informatics, 39203-213. doi:10.1016/j.aei.2019.01.002
Journal: Advanced Engineering Informatics
Abstract: The rapid development and implementation of smart, connected products (SCPs) in the engineering field has triggered a promising manufacturing paradigm of servitization, i.e. smart product-service systems (Smart PSS). As a complex solution bundle in both system and product level, its engineering change management differs from the existing ones mainly in two aspects. Firstly, massive in-context stakeholder-generated/product-sensed data during usage stage can be leveraged to enable its success in a data-driven manner. Secondly, the digitalized services, consisting of both hardware and software solutions, can also be changed in a more flexible way other than the physical components alone. Nevertheless, scarcely any work reports on how to conduct engineering change in such context, let alone a systematic approach to support the automatic generation of its change prediction or recommendation. Aiming to fill these gaps, this work proposes an occurrence-based design structure matrix (DSM) approach together with a three-way based cost-sensitive learning approach for automatic engineering change management in the Smart PSS environment. This informatics-based research, as an explorative study, overcomes the subjectivity and tedious assessment of the experts in the conventional approaches, and can offer useful guidelines to the manufacturing companies for managing their engineering changes for product-service innovation process.
URI: https://hdl.handle.net/10356/89051
http://hdl.handle.net/10220/47676
ISSN: 1474-0346
DOI: 209549
10.1016/j.aei.2019.01.002
209549
Schools: School of Electrical and Electronic Engineering 
School of Mechanical and Aerospace Engineering 
Rights: © 2019 Elsevier. All rights reserved. This paper was published in Advanced Engineering Informatics and is made available with permission of Elsevier.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles
MAE Journal Articles

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