یک روش داده کاوی برای مفهوم سازی محصول در یک معماری مبتنی بر وب

Rapid advancing information technology (IT) has improved the efficiency and effectiveness of product conceptualization and increased the importance of its role in new product development (NPD). However, there are two major omissions in existing work: firstly, a unified framework in the process of product conceptualization has not been well addressed; and secondly, it is imperative to attain an effective data-mining approach to support the product conceptualization process. Based on this understanding, the proposed approach aims at postulating an axiomatic product conceptualization system (APCS) to meet the demand of product concept development. The proposed APCS comprises three cohesively interacting modules, namely, knowledge elicitation module using laddering technique; knowledge representation module using design knowledge hierarchy (DKH); and knowledge synthesis module using restricted Coulomb energy (RCE) neural network. Accordingly, this system offers a method of making design decisions via a web-based data-mining product conceptualization approach. A case study on wood golf club design has been used for system illustration.

Few companies, especially small- and medium-sized enterprises, now possess sufficient expertise or proficiency to develop a complete product [1]. Nevertheless, companies can gain more control in their competitive arena by cooperating with other companies. Furthermore, enterprises are recognizing that they must devote more effort to product conceptualization rather than later stages of the new product development (NPD) life cycle, because of its disproportionate impact on the final product. Accordingly, it is crucial to improve design consistency yet manage design conflict amongst design participants. To this end, Pahng et al. [2] integrated designer-specified mathematical models for multi-disciplinary and multi-objective design problems. Alternatively, Lu et al. [3] analyzed the relationship between design process and design conflict, and thereafter developed a framework in terms of technical and social factors. Rapid advancing information technology (IT) has increased the possibilities for product conceptualization and the importance of its role in NPD. This is further enhanced if the companies can use ITs to form an alliance for the purposes of in-depth technical and business process integration [4]. Technologies for product design have been frequently explored and include: a standard for the exchange of product model data (STEP) translation [5]; database management systems (DBMS) (e.g. [6]); real-time 3D CAD systems (e.g. [7]); and virtual reality modelling language (VRML) displays [8]. On the other hand, to enhance the ability of product conceptualization, rather than individual capability alone, research work has focused on communication and coordination amongst distributed resources, e.g., knowledge-based system (KBS) [9], design management system (DMS) [10], and conceptual design tool [11]. Thus, all these methodologies have emphasized embodiment design, rather than product conceptualization, so that exploitation of early design creativity and efficiency has not been fully explored. Accordingly, there still exist a number of critical issues in product conceptualization. As such, product concept development must perform a number of complex functions with respect to design methodology, concurrency, teamwork, knowledge management and design representation [12]. In so doing, the IT realization of conceptualization systems is likely to be a major problem. In this regard, the data-mining technology presents a logical alternative. In recent years, data mining has been increasingly advocated in academia and industries. Its applications are widespread in such disciplines as marketing [13], engineering [14], biology [15], and web analysis (i.e., web mining) [16]. Specifically for product development, a number of research efforts were attempted in product data management (PDM), the scope of which has evolved from the internal efficiency of a company into the incorporation of both internal and external issues [17]. In the past few years, the fundamental paradigm shift in data mining for product development has emphasized on improving outward-facing activities in an organization, such as electronics data interchange (EDI) [18], customer relationship management (CRM) [19], enterprise resource planning (ERP) [20], virtual enterprise (VE) [21], supply chain planning (SCP) [22], and Internet-based commerce (IBC) [23]. However, some issues have not been well addressed in the previous work, such as lacking of quantitative analysis methods, low knowledge transparency, extensibility and predictability, and scarcity of effective customer management. To deal with these problems, some researchers recognized the importance of knowledge-based data-mining approaches, such as feature space theory [24], knowledge refinement [25] and rule-based classification [26]. Furthermore, in NPD, the product development team should incorporate customer concerns into product concepts. This may bring a significant benefit to the company because of higher customer satisfaction to the product, for example, CRM-based methodology [13] and web-mining model [27]. Nevertheless, there are two major omissions in existing work: first, a unified framework in the process of product conceptualization, which integrates customer requirements with design knowledge management in the early stages of product development, has not been well addressed; and second, it is imperative to attain an effective data-mining approach to support the product conceptualizing process. Based on this understanding, an axiomatic product conceptualization system (APCS) has been developed to meet the demand of product concept development. The proposed APCS comprises three cohesively interacting modules: namely, knowledge elicitation module using laddering technique; knowledge representation module using design knowledge hierarchy (DKH); and knowledge synthesis module using restricted Coulomb energy (RCE) neural network. Accordingly, this system offers a method of making design decisions via a web-based data-mining product conceptualization approach. A case study on wood golf club design has been used to illustrate and validate the system. The details of the validation are discussed.

This approach has revealed the potential of improving conventional axiomatic design theory in terms of effective product concept development. For this purpose, a prototype axiomatic product conceptualization system (APCS) has been established. Compared with previous axiomatic-design-related approaches, it possesses the following strengths: • The customer’s and designer’s knowledge, which is used as the inputs to CAs/FRs mapping, can be genuinely elicited using a psychology-originated technique, i.e., laddering. The laddering technique can systematically acquire design knowledge from such knowledge carriers as customers and designers. • A so-called design knowledge hierarchy (DKH) has been developed as a logical and novel knowledge representation scheme associated with laddering technique. Based on the DKH, both the customer attributes hierarchy (CAH) and functional requirements hierarchy (FRH) were established for representing CAs and FRs, respectively. • A novel classification strategy based on the RCE network has been proposed to analyze multicultural customer factors (e.g., gender and age), i.e., identification of output patterns with respect to diverse multicultural customer groups, and evaluate the relationship between CAs and FRs. • The product concepts are specifically generated according to diverse multicultural customer groups. In other words, a specific product concept can be obtained from the combination of targeted alternative values, which are dependent on classification results from the RCE network. A case study on wood golf club design was used to illustrate the performance of the proposed approach. From the case study, a web-based data-mining approach has demonstrated its effectiveness in CAs/FRs acquisition, representation and organization at the early stage of NPD. It is envisaged that with the genuineness of design knowledge elicited and the effectiveness of multicultural customer factors identified, more reasonable product concepts can be gleaned. As a result, organizations can gain a competitive edge in NPD.