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A knowledge-enabled approach for user experience-driven product improvement at the conceptual design stage

Published online by Cambridge University Press:  17 August 2023

Jun Li
School of Mechanical Engineering, Sichuan University, Chengdu 610065, China Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, China
Xin Guo
School of Mechanical Engineering, Sichuan University, Chengdu 610065, China Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, China
Kai Zhang
School of Mechanical Engineering, Sichuan University, Chengdu 610065, China Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, China
Wu Zhao*
School of Mechanical Engineering, Sichuan University, Chengdu 610065, China Yibin Institute of Industrial Technology, Sichuan University Yibin Park, Yibin, China
Corresponding author: Wu Zhao; Email:


Improving existing products plays a vital role in enhancing customer satisfaction and coping with changes in the market. Analyzing user experience (UX) to find the deficiencies of existing products and establishing improved schemes is the key to UX-driven product improvement, especially at the conceptual design stage. Although some tools used in conceptual design, such as requirements analysis and knowledge reasoning, have advanced recently, they lack targeted goals and sufficient efficiency in identifying insufficient product attributes and improving existing functions and structures. The challenge lies in considering the influence imposed on design activities by the original product features (including attributes, functions, and structure). In this study, a knowledge-enabled approach and framework that integrates the conceptual design process, online reviews for UX, and knowledge is proposed to support product improvement. Specifically, a decision-making algorithm based on UX analysis is proposed to identify to-be-improved product attributes. Then, through optimizing the previous knowledge application model from knowledge requirement transformation, knowledge modeling, and knowledge reasoning, a smart knowledge reasoning model is established to push knowledge for functional solving of the to-be-improved attributes. A knowledge configuration method is used to modify product features to generate an improved scheme. To demonstrate the feasibility of the proposed approach, a case study of improving an agricultural sprayer is conducted. Through discussion, this study can help to regulate design activities for product improvement, enhance data and knowledge application, and promote divergent thinking during scheme modification.

Research Article
Copyright © The Author(s), 2023. Published by Cambridge University Press

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Bandini, S and Sartori, F (2010) From handicraft prototypes to limited serial productions: exploiting knowledge artifacts to support the industrial design of high quality products. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24, 1734.CrossRefGoogle Scholar
Berni, A and Borgianni, Y (2021) From the definition of user experience to a framework to classify its applications in design. Proceedings of the Design Society 1, 16271636.CrossRefGoogle Scholar
Borg, JC, Yan, X and Juster, NP (1999) Guiding component form design using decision consequence knowledge support. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 13, 387403.CrossRefGoogle Scholar
Chen, Y, Liu, Z and Xie, Y (2012) A knowledge-based framework for creative conceptual design of multi-disciplinary systems. Computer-Aided Design 44, 146153.CrossRefGoogle Scholar
Chen, JW, Zhang, JS and Yang, HJ (2013) Knowledge modeling and solving strategy for product innovation design. Applied Mechanics and Materials 339, 378383.CrossRefGoogle Scholar
Chen, B, Hu, J and Chen, W (2019 a) DRE-based semi-automation of the axiomatic design transformation: from the functional requirement to the design parameter. Journal of Engineering Design 30, 255287.CrossRefGoogle Scholar
Chen, J, Ota, K, Wang, L and He, J (2019 b) Big data and smart computing in network systems. Peer-to-Peer Networking and Applications 12, 13081310.CrossRefGoogle Scholar
Chris, F, Anindya, G and Batia, W (2008) Examining the relationship between reviews and sales: the role of reviewer identity disclosure in electronic markets. Information Systems Research 19, 291313.Google Scholar
Dou, R, Zhang, Y and Nan, G (2016) Customer-oriented product collaborative customization based on design iteration for tablet personal computer configuration. Computers & Industrial Engineering 99, 474486.CrossRefGoogle Scholar
Guo, Q, Xue, C, Yu, M and Shen, Z (2018) A new user implicit requirements process method oriented to product design. Journal of Computing and Information Science in Engineering 19, 011010.CrossRefGoogle Scholar
Guo, X, Liu, Y, Zhao, W, Wang, J and Chen, L (2021 a) Supporting resilient conceptual design using functional decomposition and conflict resolution. Advanced Engineering Informatics 48, 101262.CrossRefGoogle Scholar
Guo, X, Zhao, W, Hu, H, Li, L, Liu, Y, Wang, J and Zhang, K (2021 b) A smart knowledge deployment method for the conceptual design of low-carbon products. Journal of Cleaner Production 321, 128994.CrossRefGoogle Scholar
He, B and Feng, P (2013) Guiding conceptual design through functional space exploration. The International Journal of Advanced Manufacturing Technology 66, 19992011.CrossRefGoogle Scholar
Hu, M and Liu, B (2004) Mining and summarizing customer reviews. Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168−177.CrossRefGoogle Scholar
Hu, J, Ma, J, Feng, J and Peng, Y (2017) Research on new creative conceptual design system using adapted case-based reasoning technique. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 31, 1629.CrossRefGoogle Scholar
Huang, Y, Jiang, Z, He, C, Liu, J, Song, B and Liu, L (2015) A semantic-based visualised wiki system (SVWkS) for lesson-learned knowledge reuse situated in product design. International Journal of Production Research 53, 25242541.CrossRefGoogle Scholar
Hye-Sun, K, Ho-Bin, S and Jong-Suk, L (2016) A study on big data new technology trends and market prospects. Advanced Science Letters 22, 35633566.CrossRefGoogle Scholar
Iyer, G and Soberman, D (2000) Markets for product modification information. Marketing Science 19, 203225.CrossRefGoogle Scholar
Jeong, B, Yoon, J and Lee, J (2019) Social media mining for product planning: a product opportunity mining approach based on topic modeling and sentiment analysis. International Journal of Information Management 48, 280290.CrossRefGoogle Scholar
Jiang, H, Kwong, CK, Okudan Kremer, GE and Park, WY (2019) Dynamic modelling of customer preferences for product design using DENFIS and opinion mining. Advanced Engineering Informatics 42, 100969.CrossRefGoogle Scholar
Jiao, RJ, Zhou, F and Chu, C (2017) Decision theoretic modeling of affective and cognitive needs for product experience engineering: key issues and a conceptual framework. Journal of Intelligent Manufacturing 28, 17551767.CrossRefGoogle Scholar
Jin, J, Ji, P and Gu, R (2016) Identifying comparative customer requirements from product online reviews for competitor analysis. Engineering Applications of Artificial Intelligence 49, 6173.CrossRefGoogle Scholar
Jin, J, Liu, Y, Ji, P and Kwong, CK (2019) Review on recent advances in information mining from big consumer opinion data for product design. Journal of Computing and Information Science in Engineering 19, 010801.CrossRefGoogle Scholar
Jing, R, Yu, Y and Lin, Z (2015) How service-related factors affect the survival of B2T providers: a sentiment analysis approach. Journal of Organizational Computing and Electronic Commerce 25, 316336.CrossRefGoogle Scholar
Jing, L, Yao, J, Gao, F, Li, J, Peng, X and Jiang, S (2021) A rough set-based interval-valued intuitionistic fuzzy conceptual design decision approach with considering diverse customer preference distribution. Advanced Engineering Informatics 48, 101284.CrossRefGoogle Scholar
Kiessling, TS, Richey, RG, Meng, J and Dabic, M (2009) Exploring knowledge management to organizational performance outcomes in a transitional economy. Journal of World Business 44, 421433.CrossRefGoogle Scholar
Kosmadoudi, Z, Lim, T, Ritchie, J, Louchart, S, Liu, Y and Sung, R (2013) Engineering design using game-enhanced CAD: the potential to augment the user experience with game elements. Computer-Aided Design 45, 777795.CrossRefGoogle Scholar
Lamb, CW, Hair, JF and McDaniel, C (2012) Marketing: Cengage Learning.Google Scholar
Law, EL, van Schaik, P and Roto, V (2014) Attitudes towards user experience (UX) measurement. International Journal of Human-Computer Studies 72, 526541.CrossRefGoogle Scholar
Li, S, Hu, J and Peng, Y (2010 a) Representation of functional micro-knowledge cell (FMKC) for conceptual design. Engineering Applications of Artificial Intelligence 23, 569585.CrossRefGoogle Scholar
Li, W, Li, Y, Wang, J and Liu, X (2010 b) The process model to aid innovation of products conceptual design. Expert Systems with Applications 37, 35743587.CrossRefGoogle Scholar
Li, JH, Liu, GS and Lin, X (2017) Survey on sentiment orientation analysis and its applications. Journal of Cyber Security 2, 4862.Google Scholar
Li, S, Li, Y, Li, W and Chen, C (2019) An extended case-based reasoning method and corresponding product design process. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, 66736688.Google Scholar
Li, S, Zhang, Y, Li, Y and Yu, Z (2021) The user preference identification for product improvement based on online comment patch. Electronic Commerce Research 21, 423444.CrossRefGoogle Scholar
Lin, CJ and Cheng, L (2017) Product attributes and user experience design: how to convey product information through user-centered service. Journal of Intelligent Manufacturing 28, 17431754.CrossRefGoogle Scholar
Liu, Y, Jin, J, Ji, P, Harding, JA and Fung, RYK (2013) Identifying helpful online reviews: a product designer's perspective. Computer-Aided Design 45, 180194.CrossRefGoogle Scholar
Luo, J, Sarica, S and Wood, KL (2021) Guiding data-driven design ideation by knowledge distance. Knowledge-Based Systems 218, 106873.CrossRefGoogle Scholar
Ma, H, Chu, X, Lyu, G and Xue, D (2017) An integrated approach for design improvement based on analysis of time-dependent product usage data. Journal of Mechanical Design 139, 111401.CrossRefGoogle Scholar
Mykowiecka, A and Górecki, P (2016) Bootstrapping algorithms for gene duplication and speciation events. International Conference on Algorithms for Computational Biology. Springer, pp. 106–118.CrossRefGoogle Scholar
Park, J, Han, SH, Kim, HK, Oh, S and Moon, H (2013) Modeling user experience: a case study on a mobile device. International Journal of Industrial Ergonomics 43, 187196.CrossRefGoogle Scholar
Peng, J, Li, W, Wang, M, Song, Y and Qin, X (2020) Knowledge configuration model for fast derivation design of electronic equipment and its implementation. Knowledge-Based Systems 206, 106360.CrossRefGoogle Scholar
Pournarakis, DE, Sotiropoulos, DN and Giaglis, GM (2017) A computational model for mining consumer perceptions in social media. Decision Support Systems 93, 98110.CrossRefGoogle Scholar
Qi, J, Zhang, Z, Jeon, S and Zhou, Y (2016) Mining customer requirements from online reviews: a product improvement perspective. Information & Management 53, 951963.CrossRefGoogle Scholar
Rai, R (2012) Identifying key product attributes and their importance levels from online customer reviews. ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference.CrossRefGoogle Scholar
Rehman, F and Yan, X (2003) Product design elements as means to realise functions in mechanical conceptual design. Proceedings of 14th International Conference on Engineering Design ICED 03, Stockholm, Sweden.Google Scholar
Rehman, FU and Yan, XT (2011) Application of context knowledge in supporting conceptual design decision-making. International Journal of Product Development 13, 4766.CrossRefGoogle Scholar
Relich, M, Gola, A and Jasiulewicz-Kaczmarek, M (2022) Identifying improvement opportunities in product design for reducing energy consumption. Energies 15, 119.CrossRefGoogle Scholar
Rodda, J, Ranscombe, C and Kuys, B (2022) A method to explore strategies to communicate user experience through storyboards: an automotive design case study. AI EDAM - Artificial Intelligence for Engineering Design Analysis and Manufacturing 36, e16.Google Scholar
Romero Bejarano, JC, Coudert, T, Vareilles, E, Geneste, L, Aldanondo, M and Abeille, J (2014) Case-based reasoning and system design: an integrated approach based on ontology and preference modeling. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 28, 4969.CrossRefGoogle Scholar
Salehan, M and Kim, DJ (2016) Predicting the performance of online consumer reviews: a sentiment mining approach to big data analytics. Decision Support Systems 81, 3040.CrossRefGoogle Scholar
Sheng, ML and Teo, TSH (2012) Product attributes and brand equity in the mobile domain: the mediating role of customer experience. International Journal of Information Management 32, 139146.CrossRefGoogle Scholar
Sivakumar, K and Feng, C (2019) Patterns of product improvements and customer response. Journal of Business Research 104, 2743.CrossRefGoogle Scholar
Smith, RP and Eppinger, SD (1997) Identifying controlling features of engineering design iteration. Management Science 43, 276293.CrossRefGoogle Scholar
Smith, S, Smith, G and Shen, Y (2012) Redesign for product innovation. Design Studies 33, 160184.CrossRefGoogle Scholar
Sobolewski, M (2017) Amorphous transdisciplinary service systems. International Journal of Agile Systems and Management 10, 93.CrossRefGoogle Scholar
Sun, H, Guo, W, Shao, H and Rong, B (2020) Dynamical mining of ever-changing user requirements: a product design and improvement perspective. Advanced Engineering Informatics 46, 101174.CrossRefGoogle Scholar
Van Kleef, E, Van Trijp, HC and Luning, P (2005) Consumer research in the early stages of new product development: a critical review of methods and techniques. Food Quality and Preference 16, 181201.CrossRefGoogle Scholar
Voet, H, Altenhof, M, Ellerich, M, Schmitt, RH and Linke, B (2019) A framework for the capture and analysis of product usage data for continuous product improvement. Journal of Manufacturing Science and Engineering 141, 021010.CrossRefGoogle Scholar
Wang, X, Yu, C and Wei, Y (2012) Social media peer communication and impacts on purchase intentions: a consumer socialization framework. Journal of Interactive Marketing 26, 198208.CrossRefGoogle Scholar
Wang, Z, Tian, L, Wu, Y and Liu, B (2016) Personalized knowledge push system based on design intent and user interest. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 230, 17571772.Google Scholar
Wang, A, Zhang, Q, Zhao, S, Lu, X and Peng, Z (2020) A review-driven customer preference measurement model for product improvement: sentiment-based importance–performance analysis. Information Systems and E-Business Management 18, 6188.CrossRefGoogle Scholar
Xu, J, Houssin, R, Bernard, A and Caillaud, E (2013) Systemic modeling of knowledge for innovation in design. CIRP Journal of Manufacturing Science and Technology 6, 112.CrossRefGoogle Scholar
Yang, B, Liu, Y, Liang, Y and Tang, M (2019) Exploiting user experience from online customer reviews for product design. International Journal of Information Management 46, 173186.CrossRefGoogle Scholar
Yang, C, Wu, L, Tan, K, Yu, C, Zhou, Y, Tao, Y and Song, Y (2021) Online user review analysis for product evaluation and improvement. Journal of Theoretical and Applied Electronic Commerce Research 16, 15981611.CrossRefGoogle Scholar
Yang, J, Quan, H and Zeng, Y (2022) Knowledge: the good, the bad, and the ways for designer creativity. Journal of Engineering Design 33, 945968.CrossRefGoogle Scholar
Yu, H, Zhao, W and Zhao, Q (2022) Distributed representation learning and intelligent retrieval of knowledge concepts for conceptual design. Advanced Engineering Informatics 53, 101649.CrossRefGoogle Scholar
Yuan, L, Liu, Y, Sun, Z, Cao, Y and Qamar, A (2016) A hybrid approach for the automation of functional decomposition in conceptual design. Journal of Engineering Design 27, 333360.CrossRefGoogle Scholar
Zhang, C, Zhou, G, Lu, Q and Chang, F (2017) Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development. International Journal of Production Research 55, 71877203.CrossRefGoogle Scholar
Zhang, K, Zhao, W, Wang, J, Chen, L and Guo, X (2018) Knowledge push technology based on quality function knowledge deployment. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, 11191138.Google Scholar
Zhang, L, Chu, X and Xue, D (2019) Identification of the to-be-improved product features based on online reviews for product redesign. International Journal of Production Research 57, 24642479.CrossRefGoogle Scholar
Zhan-Shan, LI, Kou, FH, Cheng, XC and Wang, T (2006) Model-based product redesign. International Journal of Computer Science & Network Security 6, 99103.Google Scholar
Zheng, H, Feng, Y, Tan, J and Zhang, Z (2015) Research on intelligent product conceptual design based on cognitive process. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 230, 20602072.Google Scholar
Zhou, F, Xu, Q and Jiao, RJ (2011) Fundamentals of product ecosystem design for user experience. Research in Engineering Design 22, 4361.CrossRefGoogle Scholar
Zhou, F, Ji, Y and Jiao, RJ (2014) Prospect-theoretic modeling of customer affective-cognitive decisions under uncertainty for user experience design. IEEE Transactions on Human-Machine Systems 44, 468483.CrossRefGoogle Scholar
Zhou, F, Jianxin Jiao, R and Linsey, JS (2015) Latent customer needs elicitation by use case analogical reasoning from sentiment analysis of online product reviews. Journal of Mechanical Design 137, 071401.CrossRefGoogle Scholar
Zhou, F, Jiao, JR, Yang, XJ and Lei, B (2017) Augmenting feature model through customer preference mining by hybrid sentiment analysis. Expert Systems with Applications 89, 306317.CrossRefGoogle Scholar
Zhu, F and Zhang, X (2010) Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. Journal of Marketing 74, 133148.CrossRefGoogle Scholar
Zhu, S, Wu, J, Xiong, H and Xia, G (2011) Scaling up top-k cosine similarity search. Data & Knowledge Engineering 70, 6083.CrossRefGoogle Scholar
Zhu, S, Qi, J, Hu, J and Huang, H (2021) Intelligent product redesign strategy with ontology-based fine-grained sentiment analysis. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 35, 295315.CrossRefGoogle Scholar