結合灰色理論與品質機能展開建構動態趨勢預測模型

Combining Grey Theory and Quality Function Deployment to Construct a Dynamic Trend Prediction Model

王佩淳(Wang pei-chun)

指導教授 ： 廖岳祥 ； 吳信宏

亞洲大學/資訊學院/資訊工程學系碩士班/碩士(2004年)

摘要

由於商品高度成熟以及市場充分開放，使得消費型態轉變，當企業面臨市場波動超乎預期時，即需要一些預測工具的輔助，來增強企業的反應速度。有鑑於此，企業為了維持基本的競爭能力，必須以多樣化的產品來滿足顧客多變性的消費型態。品質機能展開為一顧客需求導向之分析工具，能達到有效分析顧客多變性的需求之目的，因此，我們利用其結構性展開的特性，作為顧客需求之動態分析的主體架構。另外，不穩定的市場波動方面，就面臨經常性短期變化的狀況而言，如何能夠以短期有限的資訊，獲得對企業有利的經營方針，成為企業重要的課題之一。我們可利用灰預測模型只要有四筆以上的資料即可建立預測模型的主要特色，進行未來性的趨勢分析，增進企業面臨短期變化的反應能力。
　　基於上述因素，本研究延伸基本品質機能展開之觀念，利用灰預測模型只需少數數據即可達成預測未來需求動態趨勢之特色，發展一動態趨勢預測模型；並以範例說明其模式於動態趨勢分析之應用細節，並探討展開條件變動之可行性。另外，針對預測模型之效用評估，將透過與現存之統計預測方法進行成效與效率的差異評估。動態趨勢預測模型不僅具備效率且結構化展開顧客需求及技術量度的優點，其內涵之預測模式，在分析上大量減少了數學式的推導，將大幅度簡化預測模式之複雜度並且明顯提升預測品質。
　　本模型主要運用品質機能展開作為研究主體，利用其結構化展開決策條件及反映真實需求之優點，將灰預測模型結合至品質機能展開，改善原本靜態資訊為主的品質機能展開，透過動態趨勢預測，達成顧客動態需求分析的目的。即使模型中展開條件產生動態變動，並不影響模型之可行性。

關鍵字

灰色理論 ； 品質機能展開 ； 動態趨勢分析

並列摘要

The high maturity of the merchandise and the openness of the marketplace have changed the types of consumptions. When enterprises have to face the market fluctuation more than they expect, some forecasting tools might be very useful for enterprises to strengthen their responsiveness. In light of this, enterprises have to provide a variety of products to satisfy different types of customer needs. Quality function deployment (QFD) is a customer-driven analytical tool, which can be applied to capture different types of dynamic customer needs based upon its structural deployment. Besides, with the uncertainties of the marketplace, the short-term information might be extremely useful to determine management policy for enterprises. In this case, grey prediction (GP) model can be applied with only four data sets to analyze dynamic trends in the near future as well as to strengthen the responsiveness of the enterprises.
　　Based on the above discussions, this research has extended the concept of basic QFD along with GP model with few data sets to establish a dynamic forecasting model to analyze the future trends. Moreover, an example is illustrated in detail to discuss how this proposed model works under a variety of conditions. The results generated by GP model and other statistical methods are compared. The advantages of this proposed model include the high efficiency and structured deployments in customer needs and technical measures by reducing a lot of mathematical formulations to simplify the complexity and improve the forecasting quality.
　　This proposed model has applied QFD as a research basis by integrating grey prediction model to analyze dynamic customer needs to replace the static customer information. Even when the deployment conditions have been changed, the feasibility of this proposed model is not going to be affected.

並列關鍵字

Grey theory ； Quality function deployment ； Dynamic trend analysis

參考文獻

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