Development of Data Mining Driven Software Tool to Forecast the Customer Requirement for Quality Function Deployment

Shivani K. Purohit and Ashish K. Sharma
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Shivani K. Purohit: Manoharbhai Patel Institute of Engineering and Technology (MIET), Gondia, India
Ashish K. Sharma: Manoharbhai Patel Institute of Engineering and Technology (MIET), Gondia, India

International Journal of Business Analytics (IJBAN), 2017, vol. 4, issue 1, 56-86

Abstract: Quality Function Deployment (QFD) is widely used customer driven process for product development. Thus, Customer Requirements (CRs) play a key role in QFD process. However, the diversification in marketplace makes these CRs more dynamic and changing, giving rise the need to forecast CRs to improve competitiveness and increase customer satisfaction. The purpose can be served by using Data Mining techniques of forecasting. With the pool of forecasting techniques available, it is important to evaluate a suitable one for more effective results. To this end, the paper presents a novel software tool to efficiently forecast CRs in QFD. The tool allows for forecasting using various data mining based time series analysis techniques that strongly assists in doing comparative analysis and evaluating out the most apt technique for forecasting of CRs. The tool is developed using VB.Net and MS-Access. Finally, an example is presented to demonstrate the practicability of proposed software tool.

Date: 2017
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