THE SOLUTION OF _b－EQUATION OF （P，Q）－FORMS AND IT＇S L~P＆HOLDER ESTIMATES ON A STEIN MANIFOLD

ＴＨＥＳＯＬＵＴＩＯＮＯＦ_ｂ－ＥＱＵＡＴＩＯＮＯＦ（Ｐ，Ｑ）－ＦＯＲＭＳＡＮＤＩＴ＇ＳＬ￣Ｐ＆ＨＯＬＤＥＲＥＳＴＩＭＡＴＥＳＯＮＡＳＴＥＩＮＭＡＮＩＦＯＬＤ￥ＷｕＸｉａｏｑｉｎ（ＤｅｐｔｏｆＭａｔｈ，ＪｉｍｅｉＴｅａｃｈｅｒｓＣｏｌｌｅｇｅＸｉａ?..     

A STABILITY THEOREM FOR A CERTAIN FOURH-ORDER VECTOR DIFFERENTIAL FQUATION

ＡＳＴＡＢＩＬＩＴＹＴＨＥＯＲＥＭＦＯＲＡＣＥＲＴＡＩＮＦＯＵＲＨ－ＯＲＤＥＲＶＥＣＴＯＲＤＩＦＦＥＲＥＮＴＩＡＬＦＱＵＡＴＩＯＮ￥Ａ．Ｍ．Ａ．Ａｂｏｕ－Ｅｌ－Ｅｌａ＆Ａ．Ｉ．Ｓａｄｅｋ（ＦａｃｕｌｔｙｏｆＳｃｉｅｎｃｅ，ＡｓｓｉｕｔＵｎｉｖｅｒｓｉ...     

一阶线性和拟线性双曲型方程的格点模型

一阶线性和拟线性双曲型方程的格点模型李元香（武汉大学软件工程国家重点实验室）黄樟灿（武汉工学院）ＬＡＴＴＩＣＥＭＯＤＥＬＳＦＯＲＦＩＲＳＴＯＲＤＥＲＬＩＮＥＡＲＡＮＤＱＵＡＳＩ－ＬＩＮＥＡＲＨＹＰＥＢＯＬＩＣＥＱＵＡＴＩＯＮＳ￥ＬｉＹｕａｎ－ｘｉａｎ...     

一类特殊微分代数方程组的性质及应用

一类特殊微分代数方程组的性质及应用顾金生，胡显承（清华大学应用数学系）ＴＨＥＰＲＯＰＥＲＴＩＥＳＯＦＡＫＩＮＤＯＦＤＩＦＦＥＲＥＮＴＩＡＬ／ＡＬＧＥＢＲＡＩＣＥＱＵＡＴＩＯＮＳＡＮＤＴＨＥＩＲＡＰＰＬＩＣＡＴＩＯＮＳ￥ＧｕＪｉｎ－ｓｈｅｎｇ；ＨｕＸｉ...     

BOUNDEDNESS OF THE SOLUTIONS OF CERTAIN FOURTH-ORDER VECTOR DIFFERENTIAL EQUATIONS

ＢＯＵＮＤＥＤＮＥＳＳＯＦＴＨＥＳＯＬＵＴＩＯＮＳＯＦＣＥＲＴＡＩＮＦＯＵＲＴＨ－ＯＲＤＥＲＶＥＣＴＯＲＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳＢＯＵＮＤＥＤＮＥＳＳＯＦＴＨＥＳＯＬＵＴＩＯＮＳＯＦＣＥＲＴＡＩＮＦＯＵＲＴＨ－ＯＲＤＥＲＶＥＣＴＯＲ...     

THE NON－EXISTENCE OF PERIODIC SOLUTIONS OF A CERTAIN CLASS OF N－TH ORDER DIFFERENTIAL EQUATIONS

ＴＨＥ　ＮＯＮ－ＥＸＩＳＴＥＮＣＥ　ＯＦ　ＰＥＲＩＯＤＩＣ　ＳＯＬＵＴＩＯＮＳ　ＯＦ　Ａ　ＣＥＲＴＡＩＮ　ＣＬＡＳＳ　ＯＦ　Ｎ－ＴＨ　ＯＲＤＥＲ　ＤＩＦＦＥＲＥＮＴＩＡＬ　ＥＱＵＡＴＩＯＮＳＴＨＥＮＯＮ－ＥＸＩＳＴＥＮＣＥＯＦＰＥＲＩＯＤＩＣＳＯＬＵ...     

没有附加随机有界条件的B值随机元列的有界重对数律

没有附加随机有界条件的Ｂ值随机元列的有界重对数律刘立新，杨小云（保定师范专科学校，保定０７１０５１）（吉林大学数学系，长春１３００２３）ＢＯＵＮＤＥＤＬＡＷＯＦＴＨＥＩＴＥＲＡＴＥＤＬＯＧＡＲＩＴＨＭＦＯＲＡＳＥＱＵＥＮＣＥＯＦＢ－ＶＡＬＵＥＤＲＡＮ...     

SINGULARITY AND QUADRATURE REGULARITY OF（0，1，．．．，m－2，m）─INTERPOLATION ON THE ZEROS OF（1－x）P_（n－1）~（αβ）（x）

ＳＩＮＧＵＬＡＲＩＴＹＡＮＤＱＵＡＤＲＡＴＵＲＥＲＥＧＵＬＡＲＩＴＹＯＦ（０，１，．．．，ｍ－２，ｍ）─ＩＮＴＥＲＰＯＬＡＴＩＯＮＯＮＴＨＥＺＥＲＯＳＯＦ（１－ｘ）Ｐ_（ｎ－１）~（αβ）（ｘ）ＳｈｉＹｉｎｇｇｕａｎｇ（史应光）（ＣｏｍｐｕｔｉｎｇＣｅ...     

MIXED BOUNDARY VALUE PROBLEM FOR SECOND－ORDER SYSTEM OF DIFFERENTIAL EQUATIONS OF THE ELLIPTIC TYPE

（陈庆祥）ＭＩＸＥＤＢＯＵＮＤＡＲＹＶＡＬＵＥＰＲＯＢＬＥＭＦＯＲＳＥＣＯＮＤ－ＯＲＤＥＲＳＹＳＴＥＭＯＦＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳＯＦＴＨＥＥＬＬＩＰＴＩＣＴＹＰＥ￥ＣｈｅｎＱｉｎｇｘｉａｎｇ（Ｄｅｐｔ．ｏｆＭａｔｈ．，Ｚｈｏｎｇｓ...     

OSCILLATIONS OF ODD ORDER NEUTRAL DIFFERENTIAL EQUATIONS

ＯＳＣＩＬＬＡＴＩＯＮＳＯＦＯＤＤＯＲＤＥＲＮＥＵＴＲＡＬＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳ朱思铭，彭世国中同大学，邮编：５１０２７５ＯＳＣＩＬＬＡＴＩＯＮＳＯＦＯＤＤＯＲＤＥＲＮＥＵＴＲＡＬＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳ￥Ｚｈｕ...     

An advanced quality function deployment model using fuzzy analytic network process

Quality function deployment (QFD) is a customer-oriented design tool used to ensure that the voice of customers is employed throughout the product planning and design stages. QFD uses the house of quality (HOQ), which is a matrix that provides a conceptual map for inter-functional planning and communication. In this paper, an advanced QFD model, based on fuzzy analytic network process (ANP) approach, is proposed to systematically take into account the interrelationship between and within the QFD components. The proposed method is aimed at expanding the current research scope from the product planning phase to the part deployment phase to provide product developers with more valuable information (ex. the importance and bottleneck level of part characteristics). Both customer requirements and the company’s production demands will be used as the inputs for the QFD process to enhance the completeness and accuracy of the QFD analysis results. A case study is presented to illustrate the application of the proposed method.     

The implementation of simultaneous engineering in the stage of product concept development: A process orientated improvement of quality function deployment

Quality Function Deployment (QFD) has been introduced as a method of implementing Simultaneous Engineering. In spite of its achievements so far, QFD does not sufficiently link engineering to marketing and marketing science. The QFD procedure takes neither the development of market orientated or constructional product concepts, nor the coordination of both into account, although they play an important role in product definition. In order to overcome this and other deficiencies of the traditional QFD method, the author develops the process model of ‘Integrated Concept Development’ (ICoDe). It is proposed to fill the gap between marketing science and engineering by consequently relating market orientated concept development and testing to the House of Quality concept of QFD. The ICoDe process is described by refering to a ‘simulated’ application example of a wind turbines concept development.     

Quality function deployment: A literature review

This paper presents a literature review of quality function deployment (QFD) based on a reference bank of about 650 QFD publications established through searching various sources. The origination and historical development of QFD, especially in Japan and the US, are briefly accounted first, followed by a partial list of QFD organizations, softwares, and online resources. Then a categorical analysis is conducted about QFD’s functional fields, applied industries and methodological development. Ten informative QFD publications are also suggested, particularly for those who are not yet familiar with QFD. It is hoped that the paper can serve the needs of researchers and practitioners for easy references of QFD studies and applications, and hence promote QFD’s future development.     

Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator

Quality function deployment (QFD) is a planning and problem-solving tool that is gaining acceptance for translating customer requirements into the technical attributes of a product. Deriving the rating order of technical attributes from input variables is a crucial step in applying QFD. When the relative weights of customer requirements and the relationship measures between customer requirements and technical attributes are expressed as fuzzy numbers, calculating the importance of each technical attribute falls into the category of fuzzy weighted average, in which the derived membership function of the fuzzy importance of each technical attribute is not explicitly known. Thus, most ranking methods are not suitable under these circumstances. A method is proposed in this paper using fuzzy weighted average method in the fuzzy expected value operator in order to rank technical attributes in fuzzy QFD. An example of a flexible manufacturing system design is cited to demonstrate the application of the proposed approach.     

Fuzzy linear programming models for new product design using QFD with FMEA

Quality function deployment (QFD) is a customer-driven approach in processing new product developments in order to maximize customer satisfaction. Determining the fulfillment levels of design requirements (DRs) and parts characteristics (PCs) is an important decision problem during QFD activity processes for new product development. Unlike the existing literature, which mainly focuses on the determination of DRs, this paper proposes fuzzy linear programming models to determine the fulfillment levels of PCs under the requirement to achieve the determined contribution levels of DRs for customer satisfaction. In addition, considering the design risk, this paper incorporates failure modes and effect analysis (FMEA) into QFD processes, which is treated as the constraint in the models. To cope with the vague nature of product development processes, fuzzy approaches are used for both FMEA and QFD. The illustration of the proposed models is performed with a numerical example to demonstrate the applicability in practice.     

Capturing and prioritizing students’ requirements for course design by embedding Fuzzy-AHP and linear programming in QFD

Customer requirements play a vital and important role in the design of products and services. Quality Function Deployment (QFD) is a popular, widely used method that helps translate customer requirements into design specifications. Thus, the foundation for a successful QFD implementation lies in the accurate capturing and prioritization of these requirements. This paper proposes and tests the use of an alternative framework for prioritizing students’ requirements within QFD. More specifically, Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the linear programming method (LP-GW-AHP) based on Data Envelopment Analysis (DEA) are embedded into QFD (QFD-LP-GW-Fuzzy AHP) in order to account for inherent subjectivity of human judgements. The effectiveness of the proposed framework is assessed in capturing and prioritizing students’ requirements regarding courses’ learning outcomes within the process of an academic course design. Sensitivity analysis evaluates the robustness of the prioritization solution and implications for course design specifications are discussed.     

A combined approach for fuzzy multi-objective multiple knapsack problems for defence project selection

In this study, a model representing military requirements as scenarios and capabilities is offered. Pair-wise comparisons of scenarios are made according to occurrence probabilities by using the Analytical Hierarchy Process (AHP). The weights calculated from AHP are used as the starting weights in a Quality Function Deployment (QFD) matrix. QFD is used to transfer war fighter requirements into the benefit values of projects. Two levels of QFD matrices are used to evaluate new capability areas versus capabilities and capabilities versus projects. The benefit values of the projects are used in a multi-objective problem (multi-objective multiple knapsack problem) that considers the project benefit, implementation risks and environmental impact as multiple objectives. Implementation risk and environmental impact values are also calculated using the same combined AHP and QFD methodology. Finally, the results of the fuzzy multi-objective goal programming suggest a list of projects that offers optimal benefit when carried out within multiple budgets.     

Fuzzy linear programming models for NPD using a four-phase QFD activity process based on the means-end chain concept

Quality function deployment (QFD) is a customer-driven approach in processing new product development (NPD) to maximize customer satisfaction. Determining the fulfillment levels of the “hows”, including design requirements (DRs), part characteristics (PCs), process parameters (PPs) and production requirements (PRs), is an important decision problem during the four-phase QFD activity process for new product development. Unlike previous studies, which have only focused on determining DRs, this paper considers the close link between the four phases using the means-end chain (MEC) concept to build up a set of fuzzy linear programming models to determine the contribution levels of each “how” for customer satisfaction. In addition, to tackle the risk problem in NPD processes, this paper incorporates risk analysis, which is treated as the constraint in the models, into the QFD process. To deal with the vague nature of product development processes, fuzzy approaches are used for both QFD and risk analysis. A numerical example is used to demonstrate the applicability of the proposed model.     

Product design and selection using fuzzy QFD and fuzzy MCDM approaches

Quality function deployment (QFD) is a useful analyzing tool in product design and development. To solve the uncertainty or imprecision in QFD, numerous researchers have applied the fuzzy set theory to QFD and developed various fuzzy QFD models. Three issues are investigated by examining their models. First, the extant studies focused on identifying important engineering characteristics and seldom explored the subsequent prototype product selection issue. Secondly, the previous studies usually use fuzzy number algebraic operations to calculate the fuzzy sets in QFD. This approach may cause a great deviation in the result from the correct value. Thirdly, few studies have paid attention to the competitive analysis in QFD. However, it can provide product developers with a large amount of valuable information. Aimed at these three issues, this study integrates fuzzy QFD and the prototype product selection model to develop a product design and selection (PDS) approach. In fuzzy QFD, the α-cut operation is adopted to calculate the fuzzy set of each component. Competitive analysis and the correlations among engineering characteristics are also considered. In prototype product selection, engineering characteristics and the factors involved in product development are considered. A fuzzy multi-criteria decision making (MCDM) approach is proposed to select the best prototype product. A case study is given to illustrate the research steps for the proposed PDS method. The proposed method provides product developers with more useful information and precise analysis results. Thus, the PDS method can serve as a helpful decision-aid tool in product design.     

Quality function deployment for the good of soccer

This article presents a model for prioritizing and designing rule changes for the game of soccer in order to make it more attractive to soccer enthusiasts. The model, which is loosely based on quality function deployment (QFD), incorporates market segments, sports enthusiast interests, soccer activities, and rules of the game as rows and columns of interconnected QFD matrices. In addition, analytic hierarchy process (AHP) is used to determine the intensity of the relationship between the row and column variables of each matrix, while analytic network process (ANP) is used to determine the intensity of synergy effects among column variables. Finally, a trend extrapolation forecasting technique is used to suggest rule change specifications. The model fine-tunes and adds precision to the otherwise ad hoc process concerning the improvement of the game of soccer, and can provide insight about improvements in other professional sports.