A graph-based methodology for context-aware smart product-service system concept development
With the trend of sertivization and digitalization, manufacturing companies are upgrading their business paradigms as Smart product-service systems (Smart PSS) by offering customized and integrated product-service bundles (PSBs) via digital technologies (e.g., smart-connected products (SCPs)) and in...
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2021
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Engineering::Industrial engineering::Engineering management Wang, Zuoxu A graph-based methodology for context-aware smart product-service system concept development |
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With the trend of sertivization and digitalization, manufacturing companies are upgrading their business paradigms as Smart product-service systems (Smart PSS) by offering customized and integrated product-service bundles (PSBs) via digital technologies (e.g., smart-connected products (SCPs)) and informatics-based approaches (e.g., big data analytic tools and artificial intelligence (AI) technologies). Smart PSS, especially Smart PSS concept development, distinguishes from conventional ones in the following aspects.
First, major studies discussed Smart PSS development without considering the closed-loop and ever-evolving characteristics. Second, massive unstructured user-generated data embrace abundant latent user knowledge, and hence, can assist user-centric design in Smart PSS. Third, the end-users expect unique rather than generalized functionalities, which is highly dependent on the usage scenarios. Last, facing at fierce market, Smart PSS service providers are expected to comprehensively evaluate their product-service bundles even after launching to the market.
Motivated by the above issues, this study explores a framework for engineers
to make proper decisions while upgrading the product-service bundles. Furthermore, this study investigates the approaches to effectively extracting implicit requirements and generating solutions for Smart PSS development. The scientific contributions are briefly summarized as follows.
First, considering the multipartite information in Smart PSS, a systematic framework is built for Smart PSS concept development to organize the information and the decision-making tasks. Two critical Smart PSS design tasks, i.e., requirement elicitation and solution selection, are modelled as multipartite graphs (also referred to complex networks), which are analogous to the multipartite information in the real world. The overall Smart PSS design framework transforms conventional human-intensive design methods into a data-driven design method (Chapter 3). Second, this study provides a new approach to explore implicit requirements considering usage scenarios. The proposed approach enriches the constructed requirement graph by exploring semantic relations. The extracted results can serve as references for engineers to understand the implicit relations between the contexts, product components, and service modules (Chapter 4).
Third, an unbiased hypergraph-based approach is proposed to deal with the
mismatched solutions caused by the uncertain technical attributes during the Smart PSS configuration process. The proposed approach allows users to offer their preferred usage scenarios as auxiliary information, hence relieving the uncertain technical attributes’ effects (Chapter 5).
Finally, a context-aware concept evaluation approach is proposed to comprehensively evaluate the product-service bundles from the perspectives of user behavior and user perception based on information axiom and natural language processing (NLP) techniques (Chapter 6).
The research contributions were validated via an example of a three-dimensional (3D) printer company that offers remote 3D printing service bundles. It is a typical result-oriented PSS since the users pay for the 3D printers’ functions but do not own one. The example’s smartness is reflected in the processes of implicit requirement elicitation, personalized concept selection, and automatic concept evaluation.
Despite the concrete case study of 3D printing services, the proposed systematic Smart PSS conceptual design framework and corresponding design approaches can also be transformed onto other Smart PSS projects when the project has multi-sourced data, heterogeneous entities, and complex relations among entities.
Most of the research work in this thesis has been reported in three journal papers and two conference papers. It is hoped that the research outcomes could offer useful design guidance for the product designers/industrial companies for digital servitization upgrades in a user-centric way. |
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Chen Chun-Hsien |
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Chen Chun-Hsien Wang, Zuoxu |
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Wang, Zuoxu |
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Wang, Zuoxu |
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A graph-based methodology for context-aware smart product-service system concept development |
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A graph-based methodology for context-aware smart product-service system concept development |
title_full |
A graph-based methodology for context-aware smart product-service system concept development |
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A graph-based methodology for context-aware smart product-service system concept development |
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A graph-based methodology for context-aware smart product-service system concept development |
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graph-based methodology for context-aware smart product-service system concept development |
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Nanyang Technological University |
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2021 |
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sg-ntu-dr.10356-1526242023-03-11T17:35:29Z A graph-based methodology for context-aware smart product-service system concept development Wang, Zuoxu Chen Chun-Hsien School of Mechanical and Aerospace Engineering Delta-NTU Corporate Laboratory MCHchen@ntu.edu.sg Engineering::Industrial engineering::Engineering management With the trend of sertivization and digitalization, manufacturing companies are upgrading their business paradigms as Smart product-service systems (Smart PSS) by offering customized and integrated product-service bundles (PSBs) via digital technologies (e.g., smart-connected products (SCPs)) and informatics-based approaches (e.g., big data analytic tools and artificial intelligence (AI) technologies). Smart PSS, especially Smart PSS concept development, distinguishes from conventional ones in the following aspects. First, major studies discussed Smart PSS development without considering the closed-loop and ever-evolving characteristics. Second, massive unstructured user-generated data embrace abundant latent user knowledge, and hence, can assist user-centric design in Smart PSS. Third, the end-users expect unique rather than generalized functionalities, which is highly dependent on the usage scenarios. Last, facing at fierce market, Smart PSS service providers are expected to comprehensively evaluate their product-service bundles even after launching to the market. Motivated by the above issues, this study explores a framework for engineers to make proper decisions while upgrading the product-service bundles. Furthermore, this study investigates the approaches to effectively extracting implicit requirements and generating solutions for Smart PSS development. The scientific contributions are briefly summarized as follows. First, considering the multipartite information in Smart PSS, a systematic framework is built for Smart PSS concept development to organize the information and the decision-making tasks. Two critical Smart PSS design tasks, i.e., requirement elicitation and solution selection, are modelled as multipartite graphs (also referred to complex networks), which are analogous to the multipartite information in the real world. The overall Smart PSS design framework transforms conventional human-intensive design methods into a data-driven design method (Chapter 3). Second, this study provides a new approach to explore implicit requirements considering usage scenarios. The proposed approach enriches the constructed requirement graph by exploring semantic relations. The extracted results can serve as references for engineers to understand the implicit relations between the contexts, product components, and service modules (Chapter 4). Third, an unbiased hypergraph-based approach is proposed to deal with the mismatched solutions caused by the uncertain technical attributes during the Smart PSS configuration process. The proposed approach allows users to offer their preferred usage scenarios as auxiliary information, hence relieving the uncertain technical attributes’ effects (Chapter 5). Finally, a context-aware concept evaluation approach is proposed to comprehensively evaluate the product-service bundles from the perspectives of user behavior and user perception based on information axiom and natural language processing (NLP) techniques (Chapter 6). The research contributions were validated via an example of a three-dimensional (3D) printer company that offers remote 3D printing service bundles. It is a typical result-oriented PSS since the users pay for the 3D printers’ functions but do not own one. The example’s smartness is reflected in the processes of implicit requirement elicitation, personalized concept selection, and automatic concept evaluation. Despite the concrete case study of 3D printing services, the proposed systematic Smart PSS conceptual design framework and corresponding design approaches can also be transformed onto other Smart PSS projects when the project has multi-sourced data, heterogeneous entities, and complex relations among entities. Most of the research work in this thesis has been reported in three journal papers and two conference papers. It is hoped that the research outcomes could offer useful design guidance for the product designers/industrial companies for digital servitization upgrades in a user-centric way. Doctor of Philosophy 2021-09-09T02:49:19Z 2021-09-09T02:49:19Z 2021 Thesis-Doctor of Philosophy Wang, Z. (2021). A graph-based methodology for context-aware smart product-service system concept development. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/152624 https://hdl.handle.net/10356/152624 10.32657/10356/152624 en SCO-RP1; RCA-16/434 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |