Data-driven smart product design, smart service design, and smart product-service system design – A comprehensive review

The increasing complexity of smart products in the era of Artificial Intelligence (AI) presents new challenges for designing smart products, services, and product service systems. This paper aims to summarize the latest progress in the design of smart products and services, focusing on the concepts, design methods, and data types used in the design process of smart products and services. It also aims to explore how a data-driven approach can enhance product performance, improve user experience, and drive service innovation. A systematic literature search was conducted for studies published between 2004 and 2024 in the Web of Science (WoS) database. Keywords such as “smart product-service system (SPSS)”, “smart product design (SPD)”, “smart service design (SSD)”, “intelligent product service system design”, “intelligent product design”, and “intelligent service design” are used to retrieve relevant literature. A total of 803 research articles were searched and screened for relevance and eligibility based on predefined inclusion criteria, focusing on journals, papers, and conference proceedings. Ultimately, 694 valid articles were identified. Text analysis includes Term Frequency-Inverse Document Frequency (TF-IDF), Keywords cluster and knowledge graph, combined with research categories, data type, case study, and publication years to find core concepts and trends. The review identifies key applications of data in SPD, SSD, and SPSS, including requirements analysis, product optimization, fault diagnosis, and enhancing user experience. The findings highlight the importance of interdisciplinary integration and continuous innovation for developing SPD, SSD, and SPSS.

Authors

Publication Details

Journal
Advanced Engineering Informatics
Published
2026-03-03
DOI
https://doi.org/10.1016/j.aei.2026.104534
Primary Topic
Service and Product Innovation
Type
article
Field-Weighted Citation Impact
0.00
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article

Data-driven smart product design, smart service design, and smart product-service system design – A comprehensive review

Adelaide Marzano, Wenguang Lin, Keng Goh, Gokula Vasantha et al.
Advanced Engineering Informatics
Service and Product Innovation
article

Data-driven smart product design, smart service design, and smart product-service system design – A comprehensive review

Adelaide Marzano, Wenguang Lin, Keng Goh, Gokula Vasantha, Xiaodong Liu
article en

Abstract

The increasing complexity of smart products in the era of Artificial Intelligence (AI) presents new challenges for designing smart products, services, and product service systems. This paper aims to summarize the latest progress in the design of smart products and services, focusing on the concepts, design methods, and data types used in the design process of smart products and services. It also aims to explore how a data-driven approach can enhance product performance, improve user experience, and drive service innovation. A systematic literature search was conducted for studies published between 2004 and 2024 in the Web of Science (WoS) database. Keywords such as “smart product-service system (SPSS)”, “smart product design (SPD)”, “smart service design (SSD)”, “intelligent product service system design”, “intelligent product design”, and “intelligent service design” are used to retrieve relevant literature. A total of 803 research articles were searched and screened for relevance and eligibility based on predefined inclusion criteria, focusing on journals, papers, and conference proceedings. Ultimately, 694 valid articles were identified. Text analysis includes Term Frequency-Inverse Document Frequency (TF-IDF), Keywords cluster and knowledge graph, combined with research categories, data type, case study, and publication years to find core concepts and trends. The review identifies key applications of data in SPD, SSD, and SPSS, including requirements analysis, product optimization, fault diagnosis, and enhancing user experience. The findings highlight the importance of interdisciplinary integration and continuous innovation for developing SPD, SSD, and SPSS.

Advanced Engineering InformaticsVol. 73
Openalex Percentile: Top 44%
Service and Product Innovation
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