Abstract: Customer requirement analysis is the premise of product design. The traditional methods for requirement analysis include market research methods and online comment analysis. These methods are subjective and difficult to quantify the description of the requirements. Therefore, a method based on operating data is proposed to identify the customer performance requirements. Firstly, the distribution fitting method is used to fit the performance distribution. Based on this, the user required performance interval is determined, and the customer satisfaction function is constructed with the approximation of Sigmoid-like function of the cumulative probability distribution. Based on the function, for a given certain satisfaction degree, the customer required performance can be obtained and also used for comparison with user’s perception. At the end of this paper, two experiments are conducted for analyzing the volunteers’ performance requirement on their mobile battery module through the data collected by the Smart Monitor system we developed, including daily cumulative power consumption, residual capacity, number of charge cycles. The errors between two experimental results are less than 5.00%, which verifies the theoretical method we proposed.

Key words: performance requirement analysis, perception analysis, operating data, data driven, customer satisfaction function