مدلسازی و بهینه سازی طراحی محصول و رابط مدیریت پرتفولیو
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|21967||2011||11 صفحه PDF||سفارش دهید||7929 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers & Chemical Engineering, Volume 35, Issue 11, 15 November 2011, Pages 2579–2589
The paper presents modeling and analysis of product design and product portfolio management (PD–PM) domains interaction using an integrated simulation–optimization model. To represent the interactions, the product design phase is modeled as a discrete-scenario static system. The goal of this work is to develop a decision support framework that relies on product design–product portfolio management integration in order to aid product design planning and design execution. We utilize dependency matrix approach to illustrate domain relation between the product design and product portfolio management domains, and to facilitate their integration. Hence, the process integration model utilizes iterative effects, and their attendant processing duration and costs, to pattern domain interaction. An industrial case study is used to illustrate the application and utility of the proposed approach.
The product development process can be characterized by related sets of technological and business decisions that are made in situ. The linking of these two sets of decisions facilitates complete and accurate project (product) valuation by ensuring consideration of both commercial and technical requirements (Georgiopoulos et al., 2005 and Michalek et al., 2005). Furthermore, product developers have come to acknowledge that greater coordination and integration of specialized capabilities yield measurable improvement in product development cycle time and development cost (Bode et al., 2007, Krishnan, 1998 and Sogomonian and C.S., 1993). However, while acknowledging the need for technological and business integration, researchers have also admitted that there is a real challenge in formalizing the relationship between the disciplines (Georgiopoulos et al., 2005 and Michalek et al., 2005) and quantifying its impact. According to Michalek et al. (2005) the reasons for this absence of a coordinated framework can be traced to historical developments and perceptions of disciplinary boundaries. Nevertheless, a number of models have been proposed in the academic literature that seeks to quantify the interdependence of investment decisions and engineering performance decisions via analytical evaluation (Georgiopoulos, 2003, Georgiopoulos et al., 2002, Georgiopoulos et al., 2005 and Michalek et al., 2005). Such models, in forging the linkage of the two disciplines may lead to improved portfolio decisions; however it may not address issues associated with inefficient coordination, therefore yielding less than optimal portfolio decisions. Recently Ng (2004) offered a hierarchical framework that relied on distinctions in decisions length and time scales within a chemical enterprise. Such layered distinction provides the basis for linking business decision making to product and process design; wherein regions of overlap indicate the presence of interaction between levels of decision making. Moreover, the number of iterations between the various levels is minimized when decisions are made in the order of decreasing length and time scales. In recognizing the influence of dynamic market conditions and unpredictable changes in business conditions, this novel approach ignores the random nature of decision making in response to these uncertain conditions. In this study we assess interaction between technical and business domains based on recognized dependence relationship, while accounting for uncertainties that influence interactions. With a growing intensity in global market competition, firms within the chemical and related industries are forced to develop products at a rapid pace, while minimizing development costs and ensuring product quality (Smith & Ierapepritou, 2009). Faced with such stark reality, firms must optimize their development process by eliminating inefficient practices such as wasteful iterations and ineffective communication during the product development process (Cho and Eppinger, 2005, Clark and Fujimoto, 1991, Meier et al., 2007, Ulrich and Eppinger, 2000 and Wang and Lin, 2009). Such industry imperative warrants the application of a wide range of streamlining strategies; including efficient coordination across disciplinary boundaries. Other practices aimed at reducing product development cycle time include activity crashing, overlapping of activities and concurrent exploration of design alternatives (Graves, 1989). A search of the literature revealed a disproportionate focus on product design activities as targets for streamlining the product development process (Langerak and Hultink, 2008, Langerak et al., 2008, Millson et al., 1992 and Steward, 1981). Steward (1981) introduced the problem of managing product design activities by analyzing the flow of information embedded in the design of a given product. In subsequent studies, Novak and Eppinger (2001) introduced the design structure matrices (DSM) to enhance the capability for evaluating product design activities. According to Roemer and Ahmadi (2004), the management of the development process may require coordination between design activities with complex information dependencies. However, such coordination must extend beyond the product design domain in order to realize maximum efficiency accompanying product development execution. Hence, in this study we have expanded the field for product design coordination beyond intra-design activities and explore opportunities for product development performance improvement by modeling the integration of product design domain and the project selection aspect of the product portfolio management domain, as shown in Fig. 1.Given the decision dependence relationship between the two domains, the principal question now becomes how to obtain optimal interaction in an effort to avoid unnecessary project delays and cost while ensuring realistic resource allocations. Our goal in this study is to minimize the number of iterations between the domains by applying relevant streamlining policies and determining the optimal scenario for domains integration for a given set of projects that constitutes the design phase product portfolio. The paper is organized as follows: in the next section we review the approach for product design–product portfolio management integration. Section 3 outlines the domain dependencies that formed the basis of our integrative approach and has contributed to the development of the proposed computational framework. The problem description and model formulation is presented in Section 4, followed by an industrial case study to illustrate the proposed framework in Section 5, and concluding remarks in Section 6.
نتیجه گیری انگلیسی
In this work we offer a formalized approach to modeling and quantifying the interaction between the product design domain and the product portfolio management domain, with the aim to provide decision support to the product design community. The application of the proposed procedure secures a priori alignment of product portfolio management level considerations to product design activities, and subsequently makes allowance for iterative effects that may accompany such interactions. The combined implementation of product design streamlining policies and processed iterations provides meaningful support to the technical design community by enabling intelligent trade-off decisions making while limiting iterations during design execution. Furthermore, the proposed procedure provides greater control over budget and people resource allocation by establishing early priorities through the alignment of product design decision making to portfolio management level considerations.