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.     

Conceptual design of a user-centric smart product-service system using self-organizing map

As an emerging IT-driven business paradigm, smart product-service system (Smart PSS), which offers not only the smart, connected product (SCP) but also its generated service as a solution bundle, has become a vital research topic. Many research efforts have been devoted to constructing the conceptual design framework by considering SCPs and services simultaneously. However, the following critical issues in Smart PSS conceptual design have not been well addressed: how to improve the solution of Smart PSS in the conceptual design stage to meet user emotional requirements. Aiming to fill the gap, this work proposes a conceptual design method for Smart PSS from the perspective of analyzing user-generated emotions/feelings. Specifically, the relevant traditional products are identified, and their public review data is used to analyze user emotions/feelings in user-product interaction. Interactive emotion board as a new design tool is presented to organize the user-generated emotions/feelings, associated design elements, and the potential design points of the initial solution. And the analytic hierarchy process (AHP) is utilized to evaluate the improved solution. To ensure the efficiency of the analysis process, the self-organizing map (SOM) algorithm is utilized in the process of clustering product samples and Kansei words. A case study of smart electric bicycle service system (SEBSS) design is used to demonstrate the performance of the proposed method. Based on the case study, the proposed approach appears effective in helping with Smart PSS conceptual design.     

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 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.     

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.     

Requirement management for product-service systems: Status review and future trends

Many manufacturers today are striving to offer high value-added product-service systems (PSS) to their customers. Since the success of the PSS largely depends on the understanding and satisfying of different requirements, requirements management (RM) has become a critical factor in PSS development. However, PSS are mixed product-service offerings with features of heterogeneity, interaction, stakeholder participation and customization, which makes the PSS requirement difficult to be captured, analyzed, concretized and forecasted. Thus, this research analyzes the state of the art of requirements management for PSS by reviewing extensive literature of requirement identification, analysis, specification, and forecast. Based on the review, key challenges and future research directions are identified, and they are requirement elicitation considering interactions, hybrid PSS conflict detection and resolution, dynamic requirement forecasting with big data, smart requirement management and proactive response. This literature review lays the foundation for future research of PSS development.     

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 framework to design a human-centred adaptive manufacturing system for aging workers

The so-called smart manufacturing systems (SMS) combine smart manufacturing technologies, cyber-physical infrastructures, and data control to realize predictive and adaptive behaviours. In this context, industrial research focused mainly on improving the manufacturing system performance, almost neglecting human factors (HF) and their relation to the production systems. However, in order to create an effective smart factory context, human performance should be included to drive smart system adaptation in efficient and effective way, also by exploiting the linkages between tangible and intangible entities offered by Industry 4.0. Furthermore, modern companies are facing another interesting trend: aging workers. The age of workers is generally growing up and, consequently, the percentage of working 45–64 years old population with different needs, capabilities, and reactions, is increasing. This research focuses on the design of human-centred adaptive manufacturing systems (AMS) for the modern companies, where aging workers are more and more common. In particular, it defines a methodology to design AMS able to adapt to the aging workers’ needs considering their reduced workability, due to both physical and cognitive functional decrease, with the final aim to improve the human-machine interaction and the workers’ wellbeing. The paper finally presents an industrial case study focusing on the woodworking sector, where an existing machine has been re-designed to define a new human-centred AMS. The new machine has been engineered and prototyped by adopting cyber-physical systems (CPS) and pervasive technologies to smartly adapt the machine behaviour to the working conditions and the specific workers’ skills, tasks, and cognitive-physical abilities, with the final aim to support aging workers. The achieved benefits were expressed in terms of system usability, focusing on human-interaction quality.     

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.     

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.     

Data-driven cyber-physical system framework for connected resistance spot welding weldability certification

A cyber-physical system is one of the integral parts of the development endeavor of the smart manufacturing domain and the Industry 4.0 wave. With the advances in data analytics, smart manufacturing is gradually transforming the global manufacturing landscape. In the Resistance Spot Welding (RSW) domain, the focus has been more on the physical systems, compared to the virtual systems. The cyber-physical system facilitates the integrated analysis of the design and manufacturing processes by converging the physical and virtual stages to improve product quality in real-time. However, a cyber-physical system integrated RSW weldability certification is still an unmet need. This research is to realize a real-time data-driven cyber-physical system framework with integrated analytics and parameter optimization capabilities for connected RSW weldability certification. The framework is based on the conceptualization of the layers of the cyber-physical system and can incorporate the design and machine changes. It integrates data from the analytics lifecycle phases, starting from the data collection operation, to the predictive analytics operation, and to the visualization of the design. This integrated framework aims to support decision-makers to understand product design and its manufacturing implications. In addition to data analytics, the proposed framework implements a closed-loop machine parameter optimization considering the target product design. The framework visualizes the target product assembly with predicted response parameters along with displaying the process parameters and material design parameters simultaneously. This layer should help the designers in their decision-making process and the engineers to gain knowledge about the manufacturing processes. A case study on the basis of a real industrial case and data is presented in detail to illustrate the application of the envisioned cyber-physical systems framework.     

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.     

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.     

工业控制系统的信息物理因果流模型

工业控制系统向智能控制的发展随着人工智能的因果革命也应该进行因果建模的思考。通过提出工业过程控制系统的单、多层信息物理结构,引入信息、物理因果流,建立过程控制系统的信息物理因果流模型,为依据因果关系设计工业控制系统、分析控制运行机制、实施系统故障预测和监控等提供理论基础和描述框架。     

从工业4.0到能源5.0:智能能源系统的概念、内涵及体系框架

分析推动工业进程和能源进程交互发展的因素和趋势, 结合能源互联网的发展要求, 提出了建立能源5.0的迫切性和必要性. 着重讨论了在网络化之后, 能源系统呈现的社会性问题, 认为在传统方式之外, 必须引入人类社会学、管理学等软科学进行分析建模; 指出了虚拟人工系统根本不同于传统仿真系统等理念, 只有利用虚拟人工模型, 采用平行系统, 才能建立能源5.0. 阐述了能源5.0的理论、框架和技术, 明确了能源5.0、基于社会物理信息系统(Cyber-physical-social system, CPSS) 的平行能源是等价的概念. 指出能源5.0核心是构建与实际能源系统同构的虚拟人工能源系统, 通过虚拟人工能源系统的计算实验, 确定优化控制策略, 引导实际能源系统运行, 并使虚拟人工系统和实际系统平行执行、共同演化, 形成智能能源系统. 最后以华电集团已经完成的分布式能源5.0示范项目和正在实施的火力发电5.0项目及智能家居能源系统, 探讨了能源5.0的研究内容、技术途径及应用前景.     

Advanced mobile and wearable systems

The recent spectacular progress in the microelectronic, information, communication, material and sensor technologies created a big stimulus towards development of smart communicating cyber-physical systems (CPS) and Internet of Things (IoT). CPS and IoT are undergoing an explosive growth to a large degree related to advanced mobile systems like smart automotive and avionic systems, mobile robots and wearable devices. The huge and rapidly developing markets of sophisticated mobile cyber-physical systems represent great opportunities, but these opportunities come with a price of unusual system complexity, as well as, stringent and difficult to satisfy requirements of many modern applications. Specifically, smart cars and various wearable systems to a growing degree involve big instant data from multiple complex sensors or other systems, and are required to provide continuous autonomous service in a long time. In consequence, they demand a guaranteed (ultra-)high performance and/or (ultra-)low energy consumption, while requiring a high reliability, safety and security. To adequately address these demands, sophisticated embedded computing and embedded design technologies are needed. After an introduction to modern mobile systems, this paper discusses the huge heterogeneous area of these systems, and considers serious issues and challenges in their design. Subsequently, it discusses the embedded computing and design technologies needed to adequately address the issues and overcome the challenges in order to satisfy the stringent requirements of the modern mobile systems.     

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.     

Digital twin-based smart assembly process design and application framework for complex products and its case study

With rapid advances in new generation information technologies, digital twin (DT), and cyber-physical system, smart assembly has become a core focus for intelligent manufacturing in the fourth industrial evolution. Deep integration between information and physical worlds is a key phase to develop smart assembly process design that bridge the gap between product assembly design and manufacturing. This paper presents a digital twin reference model for smart assembly process design, and proposes an application framework for DT-based smart assembly with three layers. Product assembly station components are detailed in the physical space layer; two main modules, communication connection and data processing, are introduced in the interaction layer; and we discuss working mechanisms of assembly process planning, simulation, predication, and control management in the virtual space layer in detail. A case study shows the proposed approach application for an experimental simplified satellite assembly case using the DT-based assembly application system (DT-AAS) to verify the proposed application framework and method effectiveness.