2012 Service Design National Conference Korea
kSDN2012-xxx
A Case-based Recommender System for Product-service system Design Yu Wu*, Sunjoong Kim*, Xiaofang Yuan* and Ji-Hyun Lee*† * KAIST, Graduate School of Culture Technology, Korea
Abstract Product-service system (PSS) is a complex combination of product and service, which is more competitive to meet customer needs. To design a PSS, the designers should deal with complex issues, like stakeholders, activity, function, and product/service elements. Our motivation is to build a casebased recommender system for PSS design. In case-based recommender system, the comparison between different PSSs and their design process is very important for of case retrieval, adaption, and reuse. However, very few researches address PSS design process representation and the comparison between them. In this paper, we try to propose the overall framework of case-based recommender system and specify the way to represent PSS design process. Our research can be useful for a recommender system in which CBR is used to retrieve information and knowledge from prior cases and as inference mechanism.
Contact: Ji-Hyun Lee, Phone: +82-42-350-2919, Email:
[email protected], URL: http://ct.kaist.ac.kr
Yu Wu is a PhD student at Graduate School of Culture Technology, KAIST. Email:
[email protected] Sunjoong Kim is a PhD student at Graduate School of Culture Technology, KAIST. Email:
[email protected] Xiaofang Yuan is a PhD student at Graduate School of Culture Technology, KAIST. Email:
[email protected] Ji-Hyun Lee Ji-Hyun Lee is an Associate Professor of the Graduate School of Culture Technology at KAIST. She also received a joint appointment as a professor of Knowledge Service Engineering and KI for Entertainment Engineering. She received her Ph.D. from the School of Architecture (Computational Design) at Carnegie Mellon University in 2002. Her research interests are the Quantification for User Experience (UX), Computational creativity and Cultural identity + morphological analysis. Email:
[email protected]
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1.
Introduction
Sustainable production and consumption is becoming an important issue of current public concern. An increasingly common idea is to switch from a productbased economy to a serviced-based economy and by the way to move towards a new economic model[1]. To initiate this switch, many concepts have been raised in the last decades, such as product-service system (PSS), extended products, total care products and service engineering. PSS can be defined as “a marketable set of products and services capable of jointly fulfilling a user’s need. The product/service ratio in this set can vary, either in terms of function fulfillment or economic value”[2]. The adoption of PSS needs companies change their old paradigm that focuses on producing and selling products. Some companies added minor services to physical product, for example, extended warranty and trade new good for old. This kind of PSS is based on an existing product, which only makes incremental change to product. The role of designers during PSS design is different from that in the product design. In the development of PSS, designer’s activities should focus on systematic solutions, rather than on physical artifacts. Designers should consider about six dimensions in the PSS development, such as context specification, positioning and importance of stakeholders, design stage, development cycle, life-cycle consideration and representation[3]. Therefore, designers need new methods and tools to deal with the problem they might face in the PSS development. CBR is the process of creating new design solution by combining and/or adapting previous design solution(s)[4]. CBR-based design system can help designers solve the problem by past experience and improve designs by enhancing creativity. This raises the motivation to build a CBR-based recommender system to help designers for PSS development.
2.
Product-service system
2.1 Definition of PSS A PSS is an integrated product and service offering that delivers value in use. The first definition of a PSS was given by Goedkoop in a report for Report for Dutch Ministries of Environment (VROM) and Economics Affairs (EZ). Since then, most researchers have adopted this definition, and generally interpreted a PSS as a ‘product and service combined in a system to deliver
required user functionality in a way that reduces the impact on the environment’ (see Table 1). Table 1. Definitions of a Product-Service System Author (date) Goedkoop et al.(1999)
Mont(2001)
Manzini(2003)
Aurich et al(2006)
Maussang et al(2009)
Definition of product-service system ‘A product service-system is a system of products, services, networks of “players” and supporting infrastructure that continuously strives to be competitive, satisfy customer needs and have a lower environmental impact than traditional business models’[2]. ‘A system of products, services, supporting networks and infrastructure that is designed to be: competitive, satisfy customer needs and have a lower environmental impact then traditional business models’[5]. ‘An innovation strategy, shifting the business focus from designing (and selling) physical products only, to designing (and selling) a system of products and services which are jointly capable of fulfilling specific client demands’[6]. ‘PSS consists of mutually interrelated physical and non-physical components. ’[7]. ‘PSS is composed of physical objects and service units that relate to each other’[1].
2.2 PSS design methodologies A successful PSS needs to be designed at the systemic level. Shimomura et al. proposed a unified representation scheme of human and physical processes for designing service activity and products concurrently and collaboratively during the early phase of product design. In their method, physical processes are included in service blueprint to design service activities, and to connect with view models representing service content[8]. Morelli suggested IDEF0 (Integration definition for function modeling) can support a systemic approach to the design of PSS. He think service components in PSS will introduce new variables such as time dimension, the dimension of the interaction between people, and other hidden dimensions related to cultural mind frames and social habits. He also argued that dimensional, aesthetical technological and mechanical characteristics of the product should be considered in the development of physical features of a [9]. Kim et al. proposed a systematic design process for PSS development. In the design process, function layer is added in to service blueprint to generate PSS concept by considering functions, stakeholders, activities and product/service elements as a whole. Moreover, design support systems, such as activity modeling system for designing stakeholders’ activities and function modeling system for decomposing overall PSS function are also provided. [10]. - 2 -
3.
Case-based recommender system for PSS
3.1 Case-based reasoning (CBR) Case-based reasoning is a problem solving methodology that addresses a new problem by retrieving solved similar case and reusing that case for solving problem. CBR has four main steps: retrieve, reuse, adaptation and retain[11]. In a typical CBR system, all the cases are stored in the case base, and system will search the most similar cases in the case base and reuse an adapted version of the retrieved solution to solve the problem. We proposed a framework for case-based recommender system for PSS design. (see Fig.1) The fundamental issues in our framework are case indexing and retrieval. To achieve these, firstly we should model cases, which should account for both the problem and solution components. A case models a past experience, storing both problem description and the solution in certain context. Secondly, we should select relevant attributes that compose a case and define the indexes to measure case similarity.
based and case-based. 3.3 Case-based recommender system for PSS Case-based reasoning has played a key role in the development of an important recommender system known as case-based recommender system (CBR-RS). Lorenzi and Ricci [15] proposed a general framework for CBR-RSs, which including the classical five steps of the CBR problem solving cycle plus an additional’ iterate’ step. Some CBR-RSs are analyzed using the framework to find the common features and the points were they take different solutions. Moreover, the proposed framework can helps to describe to what extent a recommender system exploits the CBR cycle. In CBR-RSs, item descriptions are vital to generate a set of recommendations for user by retrieving items whose descriptions match the user’s query. In most CBRRSs, the case base models the items to be recommended and the set of suggested items is retrieved by searching for items similar to that partially described by the user[16]. In these approaches a case and an item are considered as identical, and the main components of the case are represented by item features. In this research, we try to represent PSS design process for case retrieval in CBR based recommender system. We proposed a framework to represent PSS design process, in which design activity, design process and function requirements are considered. (see Fig.2) Based on the context-based activity modeling [], we assumed that design activity can be represented by action actor (designer), object (product and service), tools (methodology and software) and context (goal, physical context, psychological context). We will convert these attributes to similarity metric for similarity measurement between cases.
Fig.1. Framework for case based recommender system
3.2 Recommender systems Recommender systems were originally defined as ones in which ‘people provide recommendations as inputs, which the system then aggregates and directs to appropriate recipients’ [12]. Now recommender system has a broader connotation, any system that produces individualized recommendations or has the effect of guiding the user in a personalized way to interesting or useful objects in a large space of possible options [13]. Recommender systems combine ideas from information retrieval and filtering, user modeling, machine learning, and human-computer interaction[14]. Recommendation techniques are very important for recommender system and the most commonly known recommendation techniques are collaborative, demographic, knowledge-
Fig.2. Case representation of PSS design process
We can gather the function requirements information in the function modeling phase in Kim’s PSS design process. By utilizing function dictionary, the function requirements can be revert to standardized function requirements. Then we use Van der Weken Method to
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calculate the similarity between different design processes. For the object (product and service), we try to find a standard criteria to categorize them. The United Nations Standard Products and Services Code (UNSPSC) provides an open, global multi-sector standard for efficient, accurate classification of products and services. In the UNSPSC, every product and service can be represented by an eight-digit number, for example, 44101501 represent photocopiers. The first two-digit is the code for the segment that the product/service is in. Up to date, UNSPSC has fifty-five segments that are arranged in a logical sequence that reflects how value is progressively added to products. (see Fig.3)
Fig.3. Fifty-five segments for UPSPSC
For the ordinary products, we can easily get their UNSPSC code by searching through its database. There are some examples in table2. Table 2. UNSPSC code for products and services UNSPSC code
Fig.4. Categorization of product and service
We assumed that design process can be compared through time spent, transit behavior, information gathering and alternative solutions. We developed multiple measures to describe the PSS design process.(See table 3) Firstly, we calculate time and percentage of time spend on six stages and fifteen steps in Kim’s PSS design process. Secondly, we account the transition behaviors among six stages and fifteen steps; for the reason that we assumed that the more transition will lead more creativity in final results. Thirdly, we account the outcome for each design stage, such as function, activity, affordance, product elements and service elements. Finally, we measure the quality of PSS design concept to get a quality score for each case.
Product and service
25101702
Police vehicles
25111502
Fishing boats
43191501
Mobile phone
42192210
Wheelchairs
56101703
Desks
43211507
Desktop computers
43211503
Notebook computers
40101701
Air conditioners
52141501
Domestic refrigerators
70142011
Cooling or refrigeration services
85101706
Traditional healthcare services
90111501
Hotels
Table 3. Information for design process comparison Design process measures
According to the UNSPSC codes we got, product and service can be categorized as follow (see Fig.4)
Time spent in design process
Case Absolute time(sec)
Relative time (%)
Total time TAP (Target Product) LCS (Life-Cycle Step) STH (Stakeholders) REQ (Requirements) E3V (E3 Values) CBAM(Context-based Activity Model) SCN (Scenarios) SBL (Service Blueprint) PSSF (PSS Function) FAM(Function-Activity Mapping) AFF (Affordance) SEM (Service Elements) PRT (Product Elements) PSSC (PSS Concept) INFR (Informal Remarks) Transition behavior
No. of
Step transitions Stage transitions Stage outcome Function
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No. of
Activity Affordance Product element Service element Information gathering
No. of
Information request Information categories Design quality measures
Avg. score
Number of constraints met Quality score
4.
Discussion
Our future research will be conducted in three stages. Firstly, we analyze PSS design process to extract more influential factors, such as tools and context in design activity elements. Then, we convert these influential factors to case indices. At this stage, we will examine how to calculate the similarity between factors and the weights of different case indices. With these results, finally we can gain a more detailed understanding of how to represent PSS design process.
Acknowledgement This research has been conducted with support from the Product-Service System Design project sponsored by Korean Ministry of Knowledge Economy.
Production, 2003. 11(8): p. 851-857. 7. Aurich, J.C., C. Fuchs, and C. Wagenknecht, Life cycle oriented design of technical Product-Service Systems. Journal of Cleaner Production, 2006. 14(17): p. 1480-1494. 8. Shimomura, Y., T. Hara, and T. Arai, A unified representation scheme for effective PSS development. CIRP Annals - Manufacturing Technology, 2009. 58(1): p. 379-382. 9. Morelli, N., Developing new product service systems (PSS): methodologies and operational tools. Journal of Cleaner Production, 2006. 14(17): p. 1495-1501. 10. Kim, Y.S., et al., Product-Service Systems (PSS) Design Process and Design Support Systems J. Hesselbach and C. Herrmann, Editors. 2011, Springer Berlin Heidelberg. p. 129-134. 11. Kolodner, J.L., Case-based reasoning1993: Morgan Kaufmann Publishers. 12. Resnick, P. and H.R. Varian, Recommender systems. Commun. ACM, 1997. 40(3): p. 56-58. 13. Burke, R., Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction, 2002. 12(4): p. 331-370. 14. Bridge, D., et al., Case-based recommender systems. Knowl. Eng. Rev., 2006. 20(3): p. 315-320. 15. Lorenzi, F. and F. Ricci, Case-based recommender systems: a unifying view, in Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization2005, Springer-Verlag: Acapulco, Mexico. p. 89-113. 16. Burke, R., Knowledge-Based Recommender Systems, in Encyclopedia of Library and Information Science, A. Kent, Editor 2000, Marcel Dekker: New York.
References 1. Maussang, N., P. Zwolinski, and D. Brissaud, Product-service system design methodology: from the PSS architecture design to the products specifications. Journal of Engineering Design, 2009. 20(4): p. 349-366. 2. Goedkoop, M.J., et al., Product Service-Systems, ecological and economic basics, in Report for Dutch Ministries of Environment(VROM) and Economics Affairs(EZ)1999. 3. Vasantha, G.V.A., et al., A review of product–service systems design methodologies. Journal of Engineering Design, 2011: p. 1-25. 4. Watson, I. and S. Perera, Case-based design: A review and analysis of building design applications. Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing, 1997. 11(1): p. 59-87. 5. Mont, O., Introducing and developing a ProductService System (PSS) concept in Sweden 2001. 6. Manzini, E. and C. Vezzoli, A strategic design approach to develop sustainable product service systems: examples taken from the ‘environmentally friendly innovation’ Italian prize. Journal of Cleaner
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