Modularization of Product Service System Based on Functional Requirement

Sun, Jian; Chai, Nana; Pi, Gang; Zhang, Zaifang; Fan, Beibei

doi:10.1016/j.procir.2017.03.038

Cited by 34 publications

(24 citation statements)

References 16 publications

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“…As an imperative part of PSS design, PSS configuration is usually studied in a predefined level of module granularity [21,22]. The service modules in existing studies of PSS [23,34] are essentially whole service flows, which can be decomposed into service activities.…”

Section: Discussionmentioning

confidence: 99%

Optimization of the Product–Service System Configuration Based on a Multilayer Network

Zhang

Ostrosi

et al. 2020

Sustainability

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Product–service systems (PSS) accelerate the transition of value creation patterns for manufacturing industries, from product design and production to the delivery of overall solution integrating products and services. Existing PSS configuration solutions provide customers with preferable product modules and service modules characterized by the module granularity. Every service module is essentially a whole service flow. However, the performance of the PSS configuration solution is greatly influenced by service details. In summary, this paper studied the configuration optimization of product-oriented PSS using a fine-grained perspective. A multilayer network composed of (i) a product layer, (ii) a service layer, and (iii) a resource layer was constructed to represent the elements (product parts, service activities, resources) and relationships in PSS. Service activities selection and resource allocation were considered jointly to construct the mathematical model of PSS configuration optimization, thus enabling the calculation of optimizing objectives (time, cost, and reliability) under constraints closer to the actual implementation. The importance degree of service activity was considered to improve the performance of service activities with higher importance. Corresponding algorithms were improved and applied for obtaining the optimal solutions. The case study in the automotive industry shows the various advantages of the proposed method.

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Section: Discussionmentioning

confidence: 99%

Optimization of the Product–Service System Configuration Based on a Multilayer Network

Zhang

Ostrosi

et al. 2020

Sustainability

Self Cite

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“…Sun et al argue that modularization plays a key role in PSS development to support individual design. Here, functional requirements of PSS can be identified and then classified into different clusters using a fuzzy clustering algorithm [119].…”

Section: Development Of Product-service Systemsmentioning

confidence: 99%

Leveraging Circular Economy through a Methodology for Smart Service Systems Engineering

2019

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Product Service Systems (PSS) and Smart Services are powerful means for deploying Circular Economy (CE) goals in industrial practices, through dematerialization, extension of product lifetime and efficiency increase by digitization. Within this article, approaches from PSS design, Smart Service design and Model-based Systems Engineering (MBSE) are combined to form a Methodology for Smart Service Architecture Definition (MESSIAH). First, analyses of present system modelling procedures and systems modelling notations in terms of their suitability for Smart Service development are presented. The results indicate that current notations and tools do not entirely fit the requirements of Smart Service development, but that they can be adapted in order to do so. The developed methodology includes a modelling language system, the MESSIAH Blueprinting framework, a systematic procedure and MESSIAH CE, which is specifically designed for addressing CE strategies and practices. The methodology was validated on the example of a Smart Sustainable Street Light System for Cycling Security (SHEILA). MESSIAH proved useful to help Smart Service design teams develop service-driven and robust Smart Services. By applying MESSIAH CE, a sustainable Smart Service, which addresses CE goals, has been developed.

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“…Third, for the SPS module partition based on the obtained correlation evaluation results, the efficiency of the previous partition methods, such as fuzzy clustering algorithm (Sun et al, 2017), mapping matrix (Li et al, 2012), fuzzy graph (Song et al, 2015;Song and Sakao, 2017), transitive closure method (Geng et al, 2019;Sheng et al, 2017) and morphological matrix (Li et al, 2018), would markedly decrease and easily suffered in local optima (Sayama et al, 2013). Most of these methods cannot be capable to acquire optimal SPS module partition schemes in terms of a larger calculation scale and workload, and to provide a visualization way to directly understand the partition process.…”

Section: Introductionmentioning

confidence: 99%

Modularization of smart product service: A framework integrating smart product service blueprint and weighted complex network

Chen

Ming

Vareilles

et al. 2020

Computers in Industry

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Modularization of smart product service (SPS) emerges as a priority strategy to agilely satisfy the dynamic customization requirement and to flexibly response to the rapid market change. Compared with the traditional product service, the SPS have more complicated interactions between the service components due to the novel characteristics caused by the application of smart technologies. The SPS modularization presents great differences from the identification of service component, correlation evaluation and module partition with the traditional product service modularization. However, most the existing research mainly focuses on the context of traditional product service, while containing scant study of smart product service. Therefore, this study proposes a hybrid framework for SPS modularization. In the framework, a cyber-physical product service blueprint is firstly proposed to represent the SPS operation process and identify the SPS components. Then, a rough-fuzzy correlation matrix is presented to determine the comprehensive interdependence between all pairs of SPS components with fully considering the hybrid decision uncertainties involved in the evaluation process, i.e., intrapersonal linguistic vagueness and interpersonal preference diversity. After that, the complex network theory is used to construct the SPS network and a modified Girvan-Newman algorithm is adopted for the SPS module partition. Finally, an illustrative modularization case of smart gearbox maintenance service and some caparisons with other methods demonstrate the feasibility and validity of the proposed approach.

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Modularization of Product Service System Based on Functional Requirement

Cited by 34 publications

References 16 publications

Optimization of the Product–Service System Configuration Based on a Multilayer Network

Optimization of the Product–Service System Configuration Based on a Multilayer Network

Leveraging Circular Economy through a Methodology for Smart Service Systems Engineering

Modularization of smart product service: A framework integrating smart product service blueprint and weighted complex network

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