A synthetical development approach for rehabilitation assistive smart product–service systems: A case study

Digital transformation (DT), the combination of information, computing, communication and connectivity technologies, which has triggered an effective upgrade of different aspects of market strategy, customer experience etc. Nowadays, rehabilitation assistive devices (RADs) are evolving to be more digital, intelligent and personalized. Digitalization and servitization have fostered to an emerging business model—the smart product–service system (Smart PSS). Therefore, DT of the RADs’ industry advocates not only the design of products and functions, the more important is the management of service processes and resource integration. With the increase in the elderly and disabled population, the requirement for RADs is becoming more urgent. However, research on Smart PSS for RAD is still limited. The rehabilitation assistive smart product–service systems (RASPSS) was introduced into the development of RADs based on the “Design and Management of DT” strategy through the service design of assistive devices and user requirements analysis. Further, an integrated design of RAD and Smart PSS has been created, a development method of RASPSS proposed, the theoretical model of the Smart PSS based on RADs built. To specify the service framework, this case study discusses the development of a home rehabilitation assistive system for femoral stem fracture patients. This paper evaluates the usability of the system, the results of which prove usability and effectiveness of the RASPSS development method. The RASPSS development model is designed to meet needs of stakeholders, improve the user rehabilitation experience, promote the service innovation of Smart PSS, bring certain market benefits of rehabilitation aids and create social value.     

A novel data-driven graph-based requirement elicitation framework in the smart product-service system context

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.     

Evolutionary design framework for Smart PSS: Service engineering approach

Digital technology is transforming industry, economy, and society. Under this digitalization trend, a new concept of product and service offerings, Smart PSS has been introduced. While the Smart PSS concept aiming at data-driven innovation attracts more attentions, there are two major challenges in designing Smart PSS. First, available data from digital technologies are actually limited by technical, financial, and social reasons. Second, the context of applying Smart PSS dynamically changes, which makes designed Smart PSS unfit to the target situation. To overcome these challenges, we propose an evolutionary design framework for Smart PSS. Our approach is based on the service engineering research, which has been contributing to the design and development of PSS. The proposed framework consists of three conceptual spaces and three cycles. The main features of the framework were two design cycles; in-system and ex-system design cycle. In-system design cycle is a process of creating and applying human knowledge for making the most use of data collected by digital technologies. Ex-system design cycle is to adapt to dynamic changes in contexts of the applied Smart PSS. We examine how the proposed framework works for designing a Smart PSS, with a case study about the digitalization of a restaurant business.     

A structural service innovation approach for designing smart product service systems: Case study of smart beauty service

Smart Product-service systems (PSS) are the emerging type of PSS that offer market value and dynamic intelligence combining products and services as solutions to consumers based on digital technology. To design a smart PSS with an effective way, a structural design approach is required. Nevertheless, only a few existing researchers discussed this topic. Aiming to bridge this gap, an integrated way is proposed for smart PSS design. This study refines a generic approach for structural service innovation approach which integrates the advantage of PSS engineering and service engineering for designing smart product service systems. The structural design approach is based on the Theory of Inventive Problem Solving (TRIZ) incorporating with service blueprint named PRR method. Three design phases are demonstrated as verification of the PRR method by an elaborated case study of the smart beauty service. Based on PRR, three key design phases are integrated, i.e., (1) problem definition, (2) resolution generation, and (3) resolution design. Empirical results and implications are collected and discussed to obtain valuable insights for value creation.     

A TRIZ-inspired knowledge-driven approach for user-centric smart product-service system: A case study on intelligent test tube rack design

With the advancement of information and communication technologies, smart product-service system (PSS) has attracted increasing research attention to integrate diverse providers/stakeholders and deliver value-added services. Many studies have thusly been conducted to design and develop the smart PSS, while i) how to identify multi-source requirements through reviewing the entire service interaction cycle, ii) how to define and deduce the innovative smart connected products (SCPs) features under contradictory interests, and iii) how to specify the functional and data service configuration solutions are still unclear. To tackle these problems, a knowledge-driven approach was introduced to better organize the multi-source design knowledge and deduce service recommendations for personalized user demands. Specifically, a user journey map-based method was proposed for knowledge elicitation of the specific user demands. To organize the user knowledge for better understanding, hierarchical personalized user requirements (PURs) analytics were proposed to quantitively transfer PURs into proper design engineering parameters. To inspire the problem-solving logic for design solution generation, TRIZ inventive principles were retrieved and referred to. With the generated design concept, the service logic diagrams were structured to define the personalized service content of SCPs. Having the service logic and SCPs, the overall service network of the user-centric smart PSS can be outlined. The proposed approach was demonstrated and validated in the digital health area via a case study on smart test tube rack (STTR) design, and it was validated from an economic feasibility perspective. It showed that the STTR was promising to reduce manual work, improve the nurses' performance, and enhance patients’ medical experience. Furthermore, it was suggested that the proposed approach can effectively guide the innovative SCPs creation in a straightforward and instructive manner, and is promising to process the service solution deduction and improve the efficiency of service creation in real practice.     

Smart experience-oriented customer requirement analysis for smart product service system: A novel hesitant fuzzy linguistic cloud DEMATEL method

Smart product service system (PSS) has become an essential strategy to transform towards digital servitization for manufacturing companies. By leveraging smart capabilities, smart PSS aims to create superior user experience in a smart context. To develop a successful smart PSS, customer requirement management from smart experience perspective is necessary. However, it is a challenging task to identify and evaluate diverse, implicit and interrelated smart experience-oriented customer requirement (SEO-CR) in smart PSS context. Hence, this paper proposes an effective methodology to elicit and analyze SEO-CRs. At first, a generic, two-dimensional SEO-CR system is presented as a basis to derive the tailored SEO-CRs for various smart PSS applications. Second, a novel HFLC-DEMATEL (hesitant fuzzy linguistic cloud-based Decision-making and trial evaluation laboratory) method is proposed to accurately evaluate the priority and complicated interaction of SEO-CRs, considering the hesitancy, fuzziness and randomness under uncertain decision environment. Some new operations (e.g., cloud total-relation matrix and weight determination method) and a cloud influence relation map are developed to fully take advantage of cloud model in DEMATEL implementation. Finally, a real case of smart vehicle service system (SVSS) is presented. The 18 SEO-CRs of the SVSS are derived based on the generalized SEO-CRs. By using HFLC-DEMATEL, some important SEO-CRs in context of SVSS are identified, such as autonomous and convenience. The finding of results can help designers make proper decisions in design and development of SVSS with a superior smart experience. The effectiveness and reliability of the proposed method are validated by conducting some comparative analyses.     

Smart product-service systems in interoperable logistics: Design and implementation prospects

To deal with the increasing complexity of customer demands, supply chain (SC) and logistics organisation and management have been constantly moving towards collaboration, intelligence, and service-orientation. The importance of service-oriented design for SC and logistics systems has been stressed, especially with regards to interoperability and sustainability. In this context, the recent intelligent interoperable logistics paradigm has been increasingly studied and the Smart Product-Service System (PSS) concept seems interesting for the paradigm. Smart PSS are characterised by their ability to collect and process information autonomously and subsequently make decisions and self-act/evolve. Interested in the potential for tackling complex logistics systems, this paper investigates how smart PSS could be considered and designed for service-oriented, intelligent interoperable logistics. A recent breakthrough logistics paradigm called the Physical Internet (PI) is taken as a practical example in this research. We present and discuss key design issues and innovative business models associated with smart PSS in PI. The results clearly indicate the promising potential of smart PSS in PI and the need for further research. Consequently, new research avenues leading to a new era of intelligent interoperable logistics are outlined. This paper intends to contribute to two main areas of research: the design and implementation of smart PSS in PI, and functional and conceptual research on PI and intelligent interoperable logistics.     

An integrated framework of user experience-oriented smart service requirement analysis for smart product service system development

The rapid deployment of digital technologies drives the conventional product service system (PSS) to shift into a new paradigm known as smart PSS. Empowered with smart capabilities, smart PSS has great potential in creating positive user experience (UX). The requirements analysis is an essential task for successful development of smart PSS with strong UX. Nevertheless, there is still a lack of research on the requirement analysis of smart PSS by incorporating smart-enabled UX perspective. Hence, this paper proposes a framework of user experience-oriented smart service requirement (UXO-SSR) analysis for smart PSS development. At first, the relevant factors (e.g., user personas and activity journey) are integrated to conceptualize the UX in smart PSS context. Second, a four-phase model is proposed for identifying UXO-SSR, which can provide an effective tool for acquiring UX requirements of smart PSS from holistic perspective. Third, a novel asymmetric trapezium cloud-based uncertain linguistic BWM approach is developed to evaluate the priority of the identified UXO-SSRs. The approach can appropriately handle the hybrid uncertainties (i.e., hesitancy, fuzziness and randomness) of linguistic evaluation information, thereby improving the accuracy of evaluation results. Finally, a case study of smart sleep service system is presented to demonstrate the feasibility and reliability of the proposed framework.     

Edge-cloud orchestration driven industrial smart product-service systems solution design based on CPS and IIoT

The rapid booming of advanced information and communication technologies (ICT) has promoted an encouraging smart, connected product (SCP) market that further triggers the development of manufacturing towards the servitization proposition, viz. smart product-service systems (PSS). Smart PSS aims to provide a solution (product-service) with high satisfaction and less environmental influence by leveraging SCP as the media tool. Its solution design should not just focus on the physical world nor only be enabled by the cloud side, while the cyber world and the edge side must be included in the Industry 4.0. However, only few current researches investigate about the smart PSS, let alone an overall cyber-physical and edge-cloud discussion to support its solution design. In order to fill this gap, this work proposes an edge-cloud orchestration driven solution design based on the cyber-physical systems (CPS) and industrial Internet of Things (IIoT). To make our ideas concrete, a real-life milling process was conducted as an illustrative example. It is hoped that this study can furnish industrial enterprises with meaningful sights in the process of servitization and value co-creation.     

A digital smart product service system and a case study of the mining industry: MSPSS

Mining equipment products and services no longer meet the needs of future development in the mining industry due to high safety and operational risk. The deep integration of the product-service system (PSS) and digitization is required in the mining industry to promote industry transformation and safe and efficient production without changing the traditional operation mode. This paper proposes a smart product-service system for the mining industry (MSPSS) consisting of a smart product subsystem, stakeholders, smart service subsystem, and smart decision-making subsystem. The analytic hierarchy process (AHP) and virtual reality (VR) are used for decision-making, product selection, operation, and maintenance. The smart product subsystem outputs reliable digital products using three stages: digital design, virtual simulation and planning, and virtual debugging. The smart service subsystem is driven by data and digital technology and provides fault diagnosis and online maintenance services for complex mining products. A case study indicates that all stakeholders can participate seamlessly in the design process. The smart product subsystem uses iterative optimization (more than 100 iterations) to obtain the design results interactively. The smart service subsystem provides digitalized services throughout the entire process. Thus, a stable, reliable, and comprehensive product and service solution is provided for complex mining conditions. The output is used to guide the design, debugging, and operation of physical equipment. The MSPSS has higher design quality and efficiency, a shorter design time, and lower design cost (key performance indicator (KPI)) than the traditional design method.     

Towards an automatic engineering change management in smart product-service systems – A DSM-based learning approach

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.     

How sustainable is smart PSS? An integrated evaluation approach based on rough BWM and TODIM

Smart Product-Service Systems (PSS) integrates smart products and e-services into a total solution with Information and Communication Technology (ICT). It is necessary to assess the Smart PSS from the perspective of sustainability in the early design phase to reduce potential failure to meet the environmental and social requirements in delivery stage. However, the existing PSS evaluation frameworks consider less about characteristics of digitalization and smartness. Moreover, the previous criteria weighting methods for PSS evaluation becomes time consuming and frustrating when comparing too many criteria to determine the weights for criteria. In addition, the existing PSS evaluation methods often omit decision makers’ bounded rationality and vagueness of judgements. To solve these problems, a novel method is proposed by integrating the merit of Best Worst Method (BWM) in reducing the decision makers’ burden of pairwise comparisons of criteria importance, the strengths of TODIM (an acronym in Portuguese of Interactive and Multi-Criteria Decision Making) in dealing with decision makers’ bounded rationality and the flexibility of Rough Set Theory (RST) in handling vagueness without prior information. Finally, a case study of sustainability evaluation for smart air-conditioner PSS is used to validate the effectiveness and efficiency of the proposed method.     

A design method for an intelligent manufacturing and service system for rehabilitation assistive devices and special groups

The maturity of Industrial 4.0 technologies (smart wearable sensors, Internet of things [IoT], cloud computing, etc.) has facilitated the iteration and digitization of rehabilitation assistive devices (RADs) and the innovative development of intelligent manufacturing systems of RADs, expanding the value-added component of smart healthcare services. The intelligent manufacturing service mode, based on the concept of the product life cycle, completes the multi-source data production process analysis and the optimization of manufacturing, operation, and maintenance through intelligent industrial Internet of things and other means and improves the product life cycle management and operation mechanism. The smart product-service system (PSS) realizes the value-added of products by providing users with personalized products and value-added services, service efficiency, and sustainable development and gradually forms an Internet-product-service ecosystem. However, research on the PSS of RADs for special populations is relatively limited. Thus, this paper provides an overview of an IoT-based production model for RADs and a smart PSS-based development method of multimodal healthcare value-added services for special people. Taking the hand rehabilitation training devices for autistic children as a case, this paper verifies the effectiveness and availability of the proposed method. Compared with the traditional framework, the method used in this paper primarily helps evaluate rehabilitation efficacy, personalizes schemes for patients, provides auxiliary intelligent manufacturing service data and digital rehabilitation data for RAD manufacturers, and optimizes the product iteration development procedures by combining user-centered product interaction, multimodal evaluation, and value-added design. This study incorporates the iterative design of RADs into the process of smart PSS to provide some guidance to the RADs design manufacturers.     

Configuration optimization of service solution for smart product service system under hybrid uncertain environments

Configuration of service solution is recognized as a crucial task for smart product service system (PSS) development, which provides an effective way to meet dynamic customer requirements. New smart attributes, broader stakeholder value and hybrid uncertainty occur inherently in the service solution configuration for smart PSS. These emerging characteristics lead to urgent updating need of the existing approaches to service solution configuration optimization. Therefore, the current study proposes a systematic approach to optimization of smart product service (SPS) solution configuration, aiming to achieve the best smart capability and value symbiosis among stakeholders of the configured SPS schemes. In the proposed approach, a new attributes system is proposed to describe the smart service module instances, and then employed as criteria to determine the configuration parameters. A novel rough-fuzzy data envelopment analysis (DEA) method is proposed to obtain the configuration parameters of each service module, with objective of effectively handling the hybrid uncertainties involved in the configuration environments. In addition, a bi-objective optimization model for SPS solution configuration considering smart capability efficiency and value symbiosis efficiency is proposed, and it is solved by an adaptive non-dominated sorting genetic algorithm II (ANSGA-II) to acquire a Pareto set of optimized configuration solutions. Finally, an application of this systematic approach to smart vehicle service demonstrates the feasibility and effectiveness of the proposed approach.     

Integrating crowd-/service-sourcing into digital twin for advanced manufacturing service innovation

In order to support advanced collaborations among smart products, services, users and service providers in a smart product and service ecosystem (S-PSS), this paper proposed a service-oriented hybrid digital twin (DT) and digital thread platform-based approach with embedded crowd-/service-sourcing mechanism for enabling advanced manufacturing services. This approach is well supported by the ecosystem interaction intelligence of digitally connected products, services, users, and service providers via Internet of Beings (IoB) (Things, Users and Service providers). First, driven by industrial application needs in heating industry, a conceptual model of the service-oriented hybrid platform integrated with crowdsourcing mechanism is developed, which supports the concepts of product DT, service DT and human user DT. Second, the key system realization techniques are developed to integrate service crowdsourcing and service recommendation for realizing smart services. Finally, a case study is carried out for evaluating and confirming its feasibility.     

A survey of smart product-service systems: Key aspects,challenges and future perspectives

The rapid development of information and communication technologies (ICT) has enabled the prevailing digital transformation (i.e. digitalization), where physical products can be readily digitized in the virtual space and seamlessly interconnected. Meanwhile, industries are ever increasingly adopting service business models (i.e. servitization), so as to offer not only physical products but also services as a solution bundle to meet individual customer needs. Such convergence of both digitalization and servitization (i.e. digital servitization) has triggered an emerging IT-driven business paradigm, smart product-service systems (Smart PSS). As a novel paradigm coined in 2014, to the authors’ knowledge, only 2 conference papers have provided some literature review to date, and many issues remain uncovered or not comprehensively investigated. Aiming to fill this gap, this paper has conducted a systematic review of Smart PSS or related papers published ever since its first brought up to date (30/06/2019), and selected 97 representative items together with other 37 supplementary works to summarize the tendency towards Smart PSS, its business and technical aspects, current challenges, and future perspectives. From the survey, it is found that several hybrid concerns are the key challenges faced, and self-adaptiveness with sustainability, advanced IT infrastructure, human-centric perspectives, and circular lifecycle management are the core future perspectives to explore. It is hoped that this work can attract more open discussions and provide useful insights to both academics and industries in their exploration and implementation of Smart PSS.     

A methodological framework with rough-entropy-ELECTRE TRI to classify failure modes for co-implementation of smart PSS

Smart PSS (product-service system) has been transcending the scope of traditional PSS through ICTs (information and communication technologies). The co-implementation is a specific way of co-creation to generate value for customer and supplier in smart PSS. Meanwhile, the service failures in co-implementation can bring about service paradox. As such, three key research questions, including the construction of co-implementation of smart PSS, the extension of risk factors in FMECA and the category of identified failure modes, are put forward and conquered by a proposed methodological framework. First, in order to construct the co-implementation of smart PSS involving customer and supplier, the PCN (process-chain-network) diagram with direct interaction, surrogate interaction and independent handling is employed to reflect the nature of interaction. Second, since that the highly complexity of co-implementation of smart PSS can lead to more huge risk, an extended-FMECA (failure mode effect and criticality analysis) sheet is formulated by considering the adaptation of autonomy. Third, to handle the uncertainty of expert judgments more reasonably and determine the weights of risk factors without additional information, a hybrid approach integrating rough-entropy-ELECTRE TRI is proposed to classify failure modes into ordinal classes, so that decision-makers can swiftly access them. This proposed methodological framework also is illustrated by the co-implementation of smart fridge-service system, in which the feasibility and superiority are verified by analysing comparative results.     

A hybrid intelligence approach for sustainable service innovation of smart and connected product: A case study

Nowadays, smart and connected product (SCP) is gradually replacing the traditional functional products, which has attracted widespread attention from the industry and academia. Service innovation, as a crucial part of SCP iterative improvement, is a multi-criteria decision-making (DM) process facilitated by intelligent automation (IA) and cognitive technologies. However, product user’s intelligence (e.g. physiological feeling) that can intuitively reflect and evaluate the product service satisfaction is rarely considered in the process of service innovation. Hence, it is difficult to measure the product users’ preferences with precise numerical terms to make a strategic decision. In order to fill this gap, a hybrid intelligence approach is proposed to perform the service innovation for SCP. The product-user data (e.g. subjective data and physiological data) and product-sensor data are collected and used for the process of service innovation. A smart group spinning bicycle system is presented as an elaborated case study to illustrate the proposed architecture and approach. The service innovation of real-time and dynamic monitoring, user participation improvement and smart feedback manners are achieved. In addition, an ergonomic experiment is conducted to validate the effectiveness of the proposed approach in implementing the service innovation for SCP.     

A smart conflict resolution model using multi-layer knowledge graph for conceptual design

Reducing the impact of conflicts on requirement-function-structure mapping in the early stage of product design is an important measure to achieve conceptual innovation, which relies on accurate reasoning of multi-domain knowledge. As product requirements become more personalized and diverse, traditional discrete knowledge organization and reasoning methods are difficult to adapt to the challenges of continuity and precision in conceptual solution. Knowledge graphs with complex networks have obvious advantages in association detection, knowledge visualization, and explainable reasoning of implicit knowledge, which offer innovative opportunities for conflict resolution in conceptual design. Therefore, a smart conflict resolution model using a multi-layer Knowledge Graph for Conceptual Design(mKGCD) is proposed in this study. A knowledge expression form of FBS-oriented design patent vocabulary is proposed, which is used for knowledge entity recognition and relation extraction based on natural language processing. A label mapping method based on inventive principles is used for patent classification and a four-layer semantic network for conflict resolution is constructed. Through semantic distance calculation, the designer's requirements for function/behavior/structure are smart deployed to obtain appropriate knowledge. A case study of the conceptual design of a collapsible installation and handling equipment demonstrates the feasibility of the proposed approach. The proposed method can not only meet the functional solution and innovation in the context of different design requirements, but also effectively improve the design efficiency in the iterative design process by means of multiple meanings of one graph.