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Technological innovation and satisfaction of customer needs are the keys to survival and success for firms, especially in global competitive high-tech industries. Since new products are usually a source of new sales and profits, the success of new product development (NPD) is essential to maintain a competitive edge and to make a decent profit in a longer term. Therefore, how to develop products that deliver the quality and functionality customers demand while generating the desired profits becomes an important task for the manufacturers. In this paper, a framework with two phases is constructed for facilitating the selection of engineering characteristics (ECs) for product design. In the first phase, quality function deployment (QFD) is incorporated with the supermatrix approach of analytic network process (ANP) and the fuzzy set theory to calculate the priorities of ECs with the consideration of the interrelationship among factors and the impreciseness and vagueness in human judgments and information. In the second phase, multi-choice goal programming model is constructed by considering the outcome from the first phase and other additional goals, such as NPD cost and manufacturability, in the attempt to select the most suitable ECs. A case study of the product design process of backlight unit (BLU) in thin film transistor liquid crystal display (TFT-LCD) industry in Taiwan is carried out to verify the practicality of the proposed framework. 相似文献
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基于结合分析的产品意象造型设计研究 总被引:2,自引:0,他引:2
为设计出符合消费者感性需求的产品,提出基于结合分析的产品意象造型设计方法。首先采用多元尺度法和聚类分析法选择典型样本,进而应用形态分析法确定产品的属性和各属性的水平。其次,利用因子分析法确定产品的感性意象,并用造型吸引力对其进行整合。在此基础上,使用对应分析法对感性意象和产品属性的关系进行探讨。最后,利用结合分析建立二者之间的数学模型。该文结合办公座椅进行研究,结果表明该方法是正确可行的。 相似文献
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客户需求信息的准确获取与表达是产品族规划的首要环节,针对客户需求模型构建过程中需求信息具有抽象性、模糊性等特点,基于公理设计构建描述客户需求的模型,运用联合分析法对客户需求进行量化,将模糊的客户需求转换为具体的产品设计指标和参数.通过对指标和参数的相关性分析,建立产品设计关联矩阵.采用模糊最大树聚类算法对设计关联矩阵进行聚类分析,以聚类有效性指标为依据,得到最佳聚类阈值,从而获得最优聚类结果.在此基础上,利用最优聚类结果对设计关联矩阵进行解耦,最终得到解耦设计关联矩阵,为参数化产品族规划提供理论依据.最后,以圆柱齿轮减速器产品族规划为实例,验证了该方法的有效性和可行性. 相似文献
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The purpose of this research is to facilitate original equipment manufacturers operating in a single market segment to frame their product line design strategy that pertains to offering right product attributes with right attribute level in the right product profile within a market segment. Through this research, we attempt to establish a link between functional level design of product attributes with commercial objectives of the enterprise. Initially, by deriving the functional importance of product attribute levels of individual product attributes within a product profile, demand and functional importance data are generated. Utilising the function-based cost estimating framework and multi-linear regression methodology, we determine the cost and product development time coefficients for respective product attributes. Finally, a mixed integer quadratic programming-based mathematical formulation is developed that includes maximisation of product premium and minimisation of various costs as major objectives under the assumption that manufacturer seeks to offer optimal number of product profiles within the market segment. Employing the commercial solver LINGO, the integrated framework is solved. The entire framework is illustrated using the operator cabin of heavy construction machinery. 相似文献
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A systematic framework is proposed to conceptualize customer needs in product design. Customer needs were derived for current and future electronic devices in automobiles. Subjects rated their preferences for 15 product attributes on 10-point semantic differential scales. Using factor analysis, three generic factors were extracted, namely holistic attributes, styling and functional design. Depending upon the familiarity of the device, there were clear differences among potential customers. Unknown devices such as a navigation map were assessed first hand by using holistic attributes. Familiar designs such as car radio and cell phone were assessed using styling and functionality attributes. Customer reactions and preferences may be caused by product design parameters that operate either through their perceptual attributes or from the experience they acquire in using the artifacts or interfaces. There are both functional and affective needs. Functional (or cognitive) customer needs can be derived top-down, using product design features. Affective customer needs are difficult to derive top-down—typically they are evaluated by looking at several design propositions. 相似文献
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Combinatorial optimization problems are often too complex to be solved within reasonable time limits by exact methods, in spite of the theoretical guarantee that such methods will ultimately obtain an optimal solution. Instead, heuristic methods, which do not offer a convergence guarantee, but which have greater flexibility to take advantage of special properties of the search space, are commonly a preferred alternative. The standard procedure is to craft a heuristic method to suit the particular characteristics of the problem at hand, exploiting to the extent possible the structure available. Such tailored methods, however, typically have limited usefulness in other problems domains.An alternative to this problem specific solution approach is a more general methodology that recasts a given problem into a common modeling format, permitting solutions to be derived by a common, rather than tailor-made, heuristic method. Because such general purpose heuristic approaches forego the opportunity to capitalize on domain-specific knowledge, they are characteristically unable to provide the effectiveness or efficiency of special purpose approaches. Indeed, they are typically regarded to have little value except for dealing with small or simple problems.This paper reports on recent work that calls this commonly held view into question. We describe how a particular unified modeling framework, coupled with latest advances in heuristic search methods, makes it possible to solve problems from a wide range of important model classes.Correspondence to: Gary A. Kochenberger.This research was supported in part by ONR grants N000140010598 and N000140310621. 相似文献
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In order to develop the profit-maximising, market share-maximising or cost-minimising bundle of product engineering specifications with proper performance levels, an optimisation model driven by operating data is proposed. The operating data are input as the sources to conduct the optimisation and a data-based customer satisfaction function can be formed. Then, a customer choice model developed from the customer satisfaction is constructed to estimate the customer choice probability. The expected market share (EMS) then can be derived from the choice probability. After all, a multi-objective model is constructed to maximise the EMS and minimise the total engineering cost. The candidate Pareto-optimal solutions can be obtained by solving the optimisation model. Then a membership function is defined to select the optimal solution from the Pareto-optimal solutions. A case study for optimising the smartphone’s specifications is conducted to demonstrate the effectiveness of the newly developed approach. Compared with the commonly used Conjoint Analysis (CA) method in determining the most desired levels for product specifications, the proposed data-driven method can avoid the situation where the user’s preferences are irrational, making the proposed method be more practical in measuring customer preferences than the utility-based model. 相似文献
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With a highly fragmented market and increased competition, platform-based product family design is recognised as an effective method for constructing a product line that satisfies diverse customer demand while keeping design and production cost- and time-effective. Recognising the need for modularity and commonality in platform development, this paper presents a systematic framework to assist in implementing top-down platform and product family design, which aims to achieve system-level modularity for variety generation, and rationalise the commonality configuration for module instantiation. In the first phase of platform development, a robust and flexible product family architecture is constructed to accommodate variations by analysing the external varieties of the generic product architecture, and provide a modularity design space, wherein the design tasks are further decomposed into module instantiation. The second phase of detailed platform development aims to enhance commonality in terms of engineering efficiency by coordinating with the back-end product realisation stage. A tractable optimisation method is used to capture and resolve the trade-off between commonality configuration and individual product performance. A family of power tool designs is used to demonstrate the potential and feasibility of the proposed framework at the system level and detailed design stages. 相似文献
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The primary objective of the design for supply chain (DFSC) is the selection of an appropriate product family. Moreover, it deals with the selection of the optimal combination among the different conflicting criteria while making a trade-off between the supply chain cost, sales profit and the product design complexities. In this research, to address the DFSC issues a product platform approach has been proposed which amalgamates the component modularity as well as the function modularity in the product design. The optimisation model proposed in this paper for the product development and the supply chain design is based on a generic bill of materials (GBOM) representation. The complete framework includes vital decision-making needed for designing a robust supply chain such as locating plants to alleviate the likely dominance of production cost and market mediation cost on product variety and imparting process flexibility of the located plants. The optimisation model proposed in this paper, models the supply chain cost, sales profit and product design complexity as three criteria that altogether determine the robustness of the supply chain and the underlying product development approach. Certain parameters like process flexibility, flow types and drivers of the product variety dominance have been controlled in the design framework. To resolve the complexity of the proposed model a genetic algorithm (GA) technique has been proposed. The proposed GA adopts an arithmetic crossover, a dynamic mutation and a variable penalty strategy to produce optimal results in a very short computational time. To validate the proposed model, a simulated case study of the wiring harness supplier of an AGV manufacturer has been studied. 相似文献
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We consider the slab storage problem (SSP) in slab yard operations. A set of slabs enter a slab yard in a specific order. A proper stack needs to be selected for each inbound slab, so that the number of relocations in the subsequent retrieval stage is minimised. We present a 0-1 integer programming model of the SSP that minimises the lower bound of the number of relocations. Four solving strategies are derived from several interesting properties of the mathematical model to speed up the solving process of the model. Making use of randomly generated instances and practical instances, we testify the effectiveness of the solving strategies and study the influence of problem parameters on the computational time of the model. Computational results show that the solving strategies can effectively reduce the computational time of the model and is applicable in medium-sized practical instances. 相似文献
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Xufeng Yao 《国际生产研究杂志》2019,57(7):2226-2246
The nature of competitive markets continuously pushes manufacturers to develop new products to meet the increasingly diversified customer demands. Manufacturers thus have to handle the complexities generated during the total life cycles of various product types, from product design to procurement, production, marketing and recycling. Though some management practices in mass customisation help to improve the performance of manufacturing systems, there are still some fundamental problems not covered. Joint decision-making of product and supply chain design, for example, is one of them. The existing industrial practice tends to treat these two problems separately. Decoupling these two problems decrease the design complexity but may lead to suboptimal decision outcome. To enhance understanding of the interconnected decisions for supply chain management and product design, this review collects related literature on this topic and focuses on the analysis of existing papers from an operation research perspective. 相似文献
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《工程优选》2012,44(1):139-164
ABSTRACTWith continued growth in air traffic, airports worldwide are expanding their runway infrastructure. This leads to the problem of determining an appropriate location and height for an Air Traffic Control (ATC) tower that can provide the right vantage point for coordinating runway and taxiway movements. The challenge involves finding the right location and optimal height that can satisfy the visibility and obstruction constraints for a complex airport-airside environment with multiple runways and civil infrastructure under different weather conditions. This article formulates the ATC tower location and height problem as a Mixed-Integer-Programming (MIP) model while considering the visibility and obstruction constraints. Singapore Changi Airport's proposed third runway extension is used as a case study to determine the set of location and height of ATC Tower using the proposed approach. A visual analytic test is conducted in an ATC tower simulator for different tower locations and heights under varying visibility conditions. 相似文献
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Chang Muk Kang 《国际生产研究杂志》2013,51(19):5271-5295
Mass customisation is a common trend in many industries, and the platform-based product family strategy is a widely used method for this purpose. While the platform strategy can reduce the cost of variety by sharing common assets such as components and production processes, it has the risk of losing market share owing to its limitation on diversity. A balance between commonality and variety needs to be achieved when designing platforms that are both efficient and effective. In this paper, we focus on developing a platform that is versatile for highly effective differentiation to increase market share, incorporating the preferences of customers for different kinds of diversity. By distinguishing preferred and non-preferred diversity and ignoring the unnecessary need for differentiation, a platform designer can increase commonality without loss of market share. Under the assumption that a versatile platform is composed of versatile components, we estimate the versatility of components to identify the versatile ones. The estimation method consists of two phases: the market analysis phase, for identifying which specifications are preferred to be differentiated, and the product analysis phase, for assessing how much impact the differentiation may have on the component. A high versatility score indicates that the corresponding component is suitable for being platformed since it is not likely to be changed to increase market share. At the same time, a low versatility score provides a clue for improving the product architecture. The proposed method was applied to computer mouse design and yielded a reasonable platform plan. 相似文献
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Affective design is an important aspect of new product development, especially for consumer products, to achieve a competitive edge in the marketplace. It can help companies to develop new products that can better satisfy the emotional needs of customers. However, product designers usually encounter difficulties in determining the optimal settings of the design attributes for affective design. In this article, a novel guided search genetic algorithm (GA) approach is proposed to determine the optimal design attribute settings for affective design. The optimization model formulated based on the proposed approach applied constraints and guided search operators, which were formulated based on mined rules, to guide the GA search and to achieve desirable solutions. A case study on the affective design of mobile phones was conducted to illustrate the proposed approach and validate its effectiveness. Validation tests were conducted, and the results show that the guided search GA approach outperforms the GA approach without the guided search strategy in terms of GA convergence and computational time. In addition, the guided search optimization model is capable of improving GA to generate good solutions for affective design. 相似文献
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The spread of drug resistance represents a significant challenge to many disease control efforts. The evolution of resistance is a complex process influenced by transmission dynamics between hosts as well as infection dynamics within these hosts. This study aims to investigate how these two processes combine to impact the evolution of resistance in malaria parasites. We introduce a stochastic modelling framework combining an epidemiological model of Plasmodium transmission and an explicit within-human infection model for two competing strains. Immunity, treatment and resistance costs are included in the within-host model. We show that the spread of resistance is generally less likely in areas of intense transmission, and therefore of increased competition between strains, an effect exacerbated when costs of resistance are higher. We also illustrate how treatment influences the spread of resistance, with a trade-off between slowing resistance and curbing disease incidence. We show that treatment coverage has a stronger impact on disease prevalence, whereas treatment efficacy primarily affects resistance spread, suggesting that coverage should constitute the primary focus of control efforts. Finally, we illustrate the importance of feedbacks between modelling scales. Overall, our results underline the importance of concomitantly modelling the evolution of resistance within and between hosts. 相似文献
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T. William Chien Chinho Lin Georghios Sphicas 《Quality and Reliability Engineering International》1997,13(4):225-233
We propose a systematic approach to determine the optimal maintenance policy for an automated manufacturing system which includes a flexible manufacturing cell (FMC) and several automated machine shops. The systematic approach combines simulation, fractional factorial design, noise or outer array of Taguchi design, regression metamodelling, and classical queueing analysis. A useful expression of the fractional utilization of the manufacturing system is derived and incorporated into formulating and solving the corresponding decision problem. The systematic approach provides an effective implementation procedure to handle practical maintenance problems found in a complex manufacturing environment. © 1997 John Wiley & Sons, Ltd. 相似文献