A New Classification Analysis of Customer Requirement Information Based on Quantitative Standardization for Product Configuration

Abstract

Traditional methods used for the classification of customer requirement information are typically based on specific indicators, hierarchical structures, and data formats and involve a qualitative analysis in terms of stationary patterns. Because these methods neither consider the scalability of classification results nor do they regard subsequent application to product configuration, their classification becomes an isolated operation. However, the transformation of customer requirement information into quantifiable values would lead to a dynamic classification according to specific conditions and would enable an association with product configuration in an enterprise. This paper introduces a classification analysis based on quantitative standardization, which focuses on (i) expressing customer requirement information mathematically and (ii) classifying customer requirement information for product configuration purposes. Our classification analysis treated customer requirement information as follows: first, it was transformed into standardized values using mathematics, subsequent to which it was classified through calculating the dissimilarity with general customer requirement information related to the product family. Finally, a case study was used to demonstrate and validate the feasibility and effectiveness of the classification analysis.