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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. [ABSTRACT FROM AUTHOR]

Abstract Recent development and implementation of advanced information and communication technologies (ICT) (e.g. Internet-of-Things (IoT), Cyber-Physical System (CPS)) has triggered a promising market of smart, connected product (SCP), and hence, enabled the prevailing tendency of manufacturing value proposition towards a service-oriented manner, viz. Smart product-service systems (PSS). Smart PSS, as a unique type of PSS, aims to achieve individual customer satisfaction with less environment impact by utilizing SCP as the media and tool, to generate various e-services as a bundle. Its service innovation is enabled by a platform-based approach and generated in a data-driven manner. Moreover, the digitalization of users, things, manufacturers and service providers in the cloud-based environment also provides potential service innovation opportunities. Nevertheless, only few existing works discuss about the Smart PSS, let alone an effective manner with valid cases to support its service innovation. Aiming to fill this gap, this research provides a novel definition of Smart PSS, and proposes a systematic design framework for its service innovation with an elaborated case study of a personalized smart wearable. Meanwhile, other potential industrial applications are discussed as well to offer valuable insights to manufacturers in their servitization for value creation. Graphical abstract Image 1 Highlights • Two criteria-based evaluation for product-service systems classification. • Extended scope of digital twin implementation scenarios. • Platform-based, data-driven and digital twin enabled service innovation. • Four-stage based design approach for service innovation of smart product-service systems. • Smart wearable service innovation and other industrial potentials. [ABSTRACT FROM AUTHOR]

Data-driven design (D 3), a new design paradigm benefited from advanced data analytics and computational intelligence, has gradually promoted the research of data-driven product design (DDPD) ever since 2000 s. In today's Intelligence Age, some theoretical and practical studies have tried to achieve the advanced intelligence capabilities in DDPD. However, to the authors' best knowledge, there is still a lack of a holistic summary of DDPD with chronological concern in the intelligence age. To bridge the gap, this research undertakes a literature review of DDPD publications from 2000 to date (19/09/2022), of which 172 relevant papers are discussed via bibliometric analysis and state-of-the-art analysis. The results shown that DDPD has vitality in the Intelligence Age by combining the cutting-edge digital technologies, such as AI, additive manufacturing, digital twin, and so on. Moreover, current DDPD studies could outperform the classical design methods on the well-defined tasks, but it still cannot master the creative/innovative design tasks which require the cognitive capability. This survey further highlights several future research potentials including cognitive intelligence-enabled design, end-to-end design integration, advanced design knowledge support, design for additive manufacturing, and sustainable smart product-service systems. It is hoped that this work can be regarded as a reference to understand the roadmap of DDPD and offer insights for the design practitioners to complete relevant tasks in today's intelligence age. [ABSTRACT FROM AUTHOR]

Nowadays, industrial companies are facing ever-increasing challenges to generate new value-in-use and maintain their high competitiveness in the market. With the rapid development of Information and Communication Technology (ICT), IT is embedded in the products themselves, i.e. smart, connected products (SCPs) to generate values. Hence, an emerging value proposition paradigm, smart product-service system (Smart PSS) was introduced, by leveraging both SCPs and its generated services as a solution bundle to meet individual customer needs. Unlike other types of PSS, in Smart PSS, massive user-generated data and product-sensed data are collected during the usage phase, where potential requirements can be elicited readily in a value co-creation manner with context-awareness. Nevertheless, only few scholars discuss any systematic manner to support requirement elicitation in such context. To fill the gaps, this research proposes a novel data-driven graph-based requirement elicitation framework in the Smart PSS, so as to assist engineering/designers make better design improvement or new design concept generation in a closed-loop manner. It underlines the informatics-based approach by integrating heterogeneous data sources into a holistic consideration. Moreover, by leveraging graph-based approach, context-product-service information can be linked by the edges and nodes in-between them to derive reliable requirements. To validate its feasibility and advantages, an illustrative example of smart bicycle design improvement is further adopted. As an explorative study, it is hoped that this work provides useful insights for the requirement elicitation process in today's smart connected environment. [ABSTRACT FROM AUTHOR]