An integrated framework for product line design for modular products: product attribute and functionality-driven perspective

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.     

A framework for affective customer needs in product design

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.     

Integrating Kansei engineering with conjoint analysis to fulfil market segmentation and product customisation for digital cameras

Diverse customer desires coupled with technological advances have forced companies to manufacture products with ultimate performance, low cost, high quality and much shorter time-to-market. Recently, the popularity of smart phones has given rise to seriously declined product sales of digital cameras. In this paper, a two-phase framework is presented to offer decision supports on developing next-generation cameras. In the phase of market segmentation, Kansei engineering is employed to capture customer perceptions of affective features. Then, rough set theory is conducted to generate decision rules for partitioning the whole market into the consumer segment and the professional segment, respectively. In the phase of product customisation, conjoint analysis is applied to extract customer preferences for functional features. Furthermore, Grey relational analysis is conducted to select the top three varieties with regard to two distinct segments. In particular, this paper is capable to help brand companies or camera manufacturers better capture customer perceptions and preferences for digital cameras, effectively perform market segmentation (based on affective features) and efficiently conduct product customisation (based on functional features).     

A multi-objective fuzzy graph approach for modular formulation considering end-of-life issues

Increased awareness of the negative environmental impact caused by electronic waste has driven electronics manufacturers to re-engineer their product design process and include product end-of-life considerations into their design criteria. Design for the Environment (DfE), as a possible solution, lacks an implementation framework. To address this problem, a fuzzy graph based modular product design methodology is developed to implement DfE strategies in product modular formulation considering multiple product life cycle objectives guided by DfE. A fuzzy connected graph approach is used to present the product structure, whereby fuzzy relationship values are determined by applying Analytic Hierarchy Process (AHP) to life cycle environmental objectives along with other functional and production concerns. Based on the fuzzy connected graph, an optimal modular formulation is searched using the graph-based clustering algorithm to identify the best module configuration. An example is provided to illustrate the methodology and the algorithm presented in this paper.     

客户参与下的服务型制造系统模型

客户参与的产品服务系统是服务型制造的一个显著特征。针对客户参与度对实施服务型制造的企业产品服务系统绩效难以度量的难题,以客户参与度为变量,构建了客户参与度与客户满意度、市场需求和企业利润的模型。通过分析表明：客户参与产品服务系统能在一定条件下提升客户满意度,实现市场需求和企业利润的增长;并可用平衡积分卡理论诠释四者之间相互支撑的逻辑关系,最后算例验证了上述模型和理论分析的科学与有效性。     

提高定制产品物料需求预测的准确性

提高定制产品物料需求预测准确性是提高企业竞争能力的必由之路。通过某公司提高定制产品物料需求预测准确性的具体项目实践，介绍了关于提高物料需求预测准确性的具体措施。通过建立一种能为各部门所共同接受的产品语言来加强各部门的信息交流，并减少从客户的实际需求到物料预测之间的中间环节来提高整个物料预测的准确性，并以实例验证其有效性。     

Optimisation of product configuration in consideration of customer satisfaction and low carbon

Product configuration is one of the key technologies in the environment of mass customisation, and it has been emphasised and concerned by much research. However, previous studies mostly focus on the cost or the customer utility, but ignore the environmental concern which becomes an important design criterion due to the rising awareness of environmental protection. Moreover, various preferences of customers are also not considered. In this paper, we develop a new bi-objective optimisation model with simultaneous consideration of customer satisfaction and the environmental impact in product configuration. Two objectives of our model are the customer satisfaction index (CSI) and greenhouse gas (GHG) emissions of products. The CSI is presented for the evaluation of customer satisfaction and the GHG emission model is developed to assess the environmental impact of the product. Essential constraints, such as selection, cost and compatibility, are also considered in the model. In addition, a two-phase approach is proposed to solve the optimisation model. Finally, the effectiveness of the proposed method is demonstrated through a case study.     

Understanding big consumer opinion data for market-driven product design

Big consumer data provide new opportunities for business administrators to explore the value to fulfil customer requirements (CRs). Generally, they are presented as purchase records, online behaviour, etc. However, distinctive characteristics of big data, Volume, Variety, Velocity and Value or ‘4Vs’, lead to many conventional methods for customer understanding potentially fail to handle such data. A visible research gap with practical significance is to develop a framework to deal with big consumer data for CRs understanding. Accordingly, a research study is conducted to exploit the value of these data in the perspective of product designers. It starts with the identification of product features and sentiment polarities from big consumer opinion data. A Kalman filter method is then employed to forecast the trends of CRs and a Bayesian method is proposed to compare products. The objective is to help designers to understand the changes of CRs and their competitive advantages. Finally, using opinion data in Amazon.com, a case study is presented to illustrate how the proposed techniques are applied. This research is argued to incorporate an interdisciplinary collaboration between computer science and engineering design. It aims to facilitate designers by exploiting valuable information from big consumer data for market-driven product design.     

基于顾客满意度及模糊计算推理的产品创新体系

在当前买方市场的经济条件下,产品设计必须满足顾客需求,产品的创新必须使顾客满意,因此,对基于顾客满意度的产品创新体系进行探讨是产品设计中的首要任务。在顾客满意度调查的基础上,提出最小顾客满意度法、基于模糊模拟的遗传算法以及利用Bayes估计顾客满意度指数的聚类方法这3种方法,从不同侧面挖掘产品创新点,再利用模糊计算推理对提出的3种产品创新点挖掘方法进行综合。在挖掘出产品创新点后,需要根据专业知识对产品进行进一步的改进设计,并给出一个产品创新点挖掘方法的计算实例。建立了基于顾客满意的产品创新体系,使产品的创新设计能面向顾客的需求。     

Strategies for evaluating performance of flexibility in product recovery system

In view of the increasing business opportunities with changing customer attitudes and stricter legislations, the handling of returns has become a daunting challenge. The need for decision models for evaluating return performance has been observed in the academia and the corporate world. To improve return system performance, integrated flexible reverse enterprise systems have attracted attention from researchers as well as practitioners. This paper addresses these critical issues and proposes a novel integrated and Flexible recovery system decision model. The proposed model aims to facilitate enterprises in assessing their product recovery system capability, and in improving overall performance. The proposed model is a natural extension of several well-grounded policies for conventional reverse supply chains and can be verified on a simulation platform.     

名牌产品顾客满意度测评体系研究

本文在研究国内外典型顾客满意度测评模型的基础上,分析了名牌产品满意度测评与行业、企业满意度测评的不同,提出了面向名牌产品的顾客满意度测评模型和体系。数据分析表明,该测评体系能够反映顾客的意愿。本文提出的名牌产品顾客满意度测评体系对企业提高满意度和增强竞争力具有参考价值。     

A mathematical formulation for interface-based modular product design with geometric and weight constraints

Since customer preferences change rapidly, there is a need for design processes with shorter product development cycles. Modularization plays a key role in achieving mass customization, which is crucial in today's competitive global market environments. Standardized interfaces among modularized parts have facilitated computational product design. To incorporate product size and weight constraints during computational design procedures, a mixed integer programming formulation is presented in this article. Product size and weight are two of the most important design parameters, as evidenced by recent smart-phone products. This article focuses on the integration of geometric, weight and interface constraints into the proposed mathematical formulation. The formulation generates the optimal selection of components for a target product, which satisfies geometric, weight and interface constraints. The formulation is verified through a case study and experiments are performed to demonstrate the performance of the formulation.     

Evaluation of multicultural factors from elicited customer requirements for new product development

Globalisation has been characterised as one of the recent trends in new product development (NPD), in which multicultural factors, in particular, dominate the initial step of product development. Moreover, the voice of customers has been widely accepted as an important source of input to subsequently obtain design metrics and specifications in the early stage of product concept design. For this purpose, customer requirements elicitation and management will determine the success level of an organisation's NPD and benchmarking. Hence, multicultural factors are the most difficult issues for organisations to address, even with the assistance of today's advanced computer systems. It has, accordingly, been one of the future directions in NPD. However, in practice, there are few successful or effective techniques available for the evaluation of multicultural factors in customer requirements. This paper aims at realising a prototype system that combines the strengths of the laddering technique and the radial basis function (RBF) neural network for customer requirements acquisition and multicultural factors evaluation. The performance of the prototype system was illustrated using a case study on mobile hand phone design. The results are discussed in detail.     

A profit maximising product line optimisation model under monopolistic competition

Existing research on product line optimisation have focused mainly on designing a product line based on the trade-offs between sellers’ and buyers’ utility, without any explicit consideration of the underlying market structure. A few studies can be found that consider the monopolists’ optimal product line offering. In this study, we examine the optimal product line decision of an entrant firm under monopolistic competitive markets. Specifically, we develop a mathematical programming formulation of an entrant firm’s problem of deciding on the market segments to enter and the corresponding product designs to offer, to maximise its profit. A heuristic has been presented for solving the resulting mixed integer non-linear programming problem. The specifications of the problem increase exponentially with the size of the problem and as such, commercial solvers are not useful for solving a generalised instance. A small example has been presented and solved using both the heuristic and the ILOG CPLEX 10.2. Both result in identical solutions. We attempt an explanation on why the heuristic gives an optimal solution.     

建筑施工企业顾客满意度模型实证分析

根据建筑施工项目的特征提出一个简化的建筑施工企业顾客满意度理论模型.在收集建筑施工企业顾客样本数据的基础上,利用结构方程模型软件对理论模型作了检验.研究结果表明:顾客感知质量对顾客满意度、顾客感知价值对顾客忠诚度、顾客满意度对顾客抱怨具有显著性的影响;顾客期望对顾客抱怨、顾客满意度对顾客忠诚度有正面影响;顾客抱怨对顾客忠诚度有负面影响.研究结论具有较高的精度,模型对该建筑施工企业顾客满意度有较好的解释力.     

An advanced CMII-based engineering change management framework: the integration of PLM and ERP perspectives

Previous studies of engineering change management (ECM) presented valuable results from the design domain of the product lifecycle management (PLM) perspective. However, few of these studies proposed a framework under the configuration management II (CMII) standards and its industrial implementation based on the design and manufacturing domains of PLM and enterprise resources planning. This study proposes an advanced CMII-based ECM framework. This framework has been successfully implemented in a large Taiwanese motorcycle manufacturer resulting in significant performance improvement. Major contributions of this study include: (1) presenting an advanced CMII-based ECM framework, (2) depicting information exchange and integration between the design and manufacturing activities based on five major ECM phases and their associated processes and (3) providing a basis for best practice from the motorcycle industry for reference in other manufacturing industries.     

商业性矿产勘查的理论与实践

商业性矿产勘查是一种按照经济属性划分的地质工作,是企业的生产经营活动。商业性矿产勘查的经营成果是具有经济开采价值的地质储量,要通过转出矿业权或转入矿产品生产实现勘查投资的回收和盈利。其运行方式与传统计划管理体制下的矿产勘查有多种差异。云南地矿资源股份有限公司商业性矿产勘查的运行给了有益的启示。     

Attribute selection for product configurator design based on Gini index

Customer needs play a critical role in product design. Matching diversified customer needs with a company’s product offerings has been a challenge for academia and industry. To this end, product configurator systems have been accepted as important tools to elicit customer needs to meet the challenge. However for complex products with many product possibilities and intricate inter-product relationships, current product configuration systems may become tedious and time consuming for customers’ choice navigation process. They cannot adapt to each individual customer’s preferences by leveraging on the attribute specification information captured in previous configuration steps. This paper presents a Gini index-based attribute selection approach for configurator design. Product configuring is modelled as a sequential query–answer process. In each configuring step, the Gini index is deployed to quantify the clarity of the designer’s beliefs about the customer’s needs. The attribute which contributes most to the clarity will be selected for the customer to configure. A product recommendation module is also integrated with the configurator to further improve the efficiency. As a result, designers obtain clarification on the customer’s needs and preferences in an accelerated manner. An example is presented to test the viability of the method.     

Modularity analysis and commonality design: a framework for the top-down platform and product family design

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.