نوع مقاله : پژوهشی
نویسندگان
دانشکدهی مدیریت، دانشگاه تربیت مدرس
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Today, universal competition has greatly increased, due to the rapid change in technical progress and the variety of production. This makes the role of Performance improvemen as a computational and strategic requirement
in many organization worldwide. The function of production is in the area of engineering characteristics, and, for this design, correct understanding of customer requirements and recognition of design requirements are important. Quality function deployment is a strong instrument for improving the quality and design of a product and for making a system customer oriented. In this research, we have combined a frame of QFD and GP for showing the fulfillment level of DR(s). Wasermans has been used in the frame for normalizing houses of quality.
This framework can include multi goals, like increasing customer satisfaction, and decreasing costs and technical difficulty. Suppose that customer satisfaction and cost expenditure are considered more important than technical
difficulty (two such priority levels are recommended in the QFD process). Based on the three fuzzy goals and their preemptive priority structure, the overall model can be formulated.
Determining goal values precisely is difficult for the design team. Since customer satisfaction, cost, and technical difficulty are not easy to measure exactly, these goals usually conflict with each other. For dealing with this,
the design team first determines aspiration levels for each goal, and then finds a set of solutions to achieve the maximum satisfaction degree of all goals in total.
The important variable in this model is $x_{j}. x_{j}$ is the fulfillment level of engineering
design requirement, j =1,2,...
n. if $x_{j}$ = 100%, it denotes complete
fulfillment of the objective targets for the jth DR.
For solving this problem, the model transforms with fuzzy coefficients to a family of conventional crisp mathematical programming models by applying the $alpha-cut$ approach and Zadehs extension principle. Obviously, if a designer requires more information to decide the fulfillment level of DRs, more
$alpha-cut$ are needed.
Different $alpha$ values lead to different ranges of degree satisfaction of the goals and also those of the fulfillment levels of DRs. The membership function for fuzzy goals and fuzzy fulfillment levels are constructed by piecewise linear segments based on different $alpha$ values Finally, this research has been used in the Cement Company of Larestan, Iran, producing Portland II cement.
کلیدواژهها [English]
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