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Study On Customer-Enterprise Interacting Mechanism For The Quality-Improvement Oriented By Complex Nonlinear System

Posted on:2006-08-04Degree:DoctorType:Dissertation
Country:ChinaCandidate:W Q WuFull Text:PDF
GTID:1119360182975522Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
With the market competition getting more and more severe, meeting customerrequirements and satisfying customers through quality-improvement are the basis ofan enterprise's development. However, the quality-improvement of enterprises in ourcountry still remains at the passive level of customer-oriented. To raise the effectiveand efficiency of the quality-improvement, a new concept is put forward in this thesis.That is Customer-Enterprise Interacting Mechanism for the Quality-Improvementoriented to the customer loyalty. The main idea of this concept is that thequality-improvement should not only be based on customer-oriented theory but alsotry to tap and guide the customer requirements, including the hidden requirements andthe latent requirements. This Interactive Mechanism emphasizes making customersmore satisfied and loyal and the enterprise more active in the market competitionthrough the customer-focus interact, whole-organization interact, whole-processinteract, active interact, mutually beneficial interact and continual interact.To guide the enterprises to build and accomplish this Interactive Mechanism, themathematical model oriented by the simple linear system has been built with thematrix alternation and fuzzy-set theory according to the definition and intension ofthis mechanism. This model being made up of alternation sub-model,quality-improvement sub-model and feedback sub-model reveals the internalinteractive relationship between the quality-improvement and customer-requirement,customer-satisfaction.On the basis of this model, the research about the complexity and thenonlinearity of this Mechanism has been done from the angle of the system theory,and the new idea of the Interactive Mechanism oriented by the complex nonlinearsystem composed by forecasting input sub-system, optimizing and controlsub-system ,decision-making output sub-system has been posed in this paper.To provide the mathematical tool of the establishment of this Mechanism, in thisdissertation, the algorithm of Neural Network has been modified, and the GA-WNNoptimization method that combining Genetic Algorithm (GA) with Wavelet NeuralNetwork (WNN) has been proposed. Then, the forecasting input sub-system based oncombining Neural Network with chaotic theory, the optimizing and controlsub-system based on combining Genetic Algorithm with Wavelet Neural Network andthe decision-making output sub-system based on combining Artificial Neural Network(ANN) with Expert System (ES) have been presented and established.Finally, the Interactive Mechanism oriented by the complex nonlinear systembased on Artificial Neural Network and other nonlinear methods has been built, andthe framework chart and the mathematical model of this Mechanism have beenbrought forward. According to the practice in manufacturing enterprises, thepracticality of this Mechanism's establishment and the concrete process has beenstudied. And, to solve the internal 'black box' problem of this Mechanism, a methodbased on Quality-Function-Deployment (QFD) is posed and the concept of InteractHouse of Quality is advanced. For the application of this Mechanism in enterprises,the Five-Combination principle has been proposed, which emphasizes thecombination of the Interactive Mechanism with 6σ Quality Program to put forwardthe enterprises' Continuous-Quality-Improvement (CQI).It is proved by facts that the establishment of the Interactive Mechanism canraise the effective and efficiency of the quality-improvement, make customers moresatisfied and loyal, realize the win-win situation between enterprises and customers,has significance to guide the enterprises' quality-improvement.
Keywords/Search Tags:Quality-Improvement, Customer Relationship Management, Interactive Mechanism, Complex Nonlinear System, Nonlinear Methods, GA-WNN Method
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