Abstract

The paper investigates the use of intelligent systems to identify the factors that significantly influence the duration of new product development. These factors are identified on the basis of an internal database of a production enterprise and further used to estimate the duration of phases in product development projects. In the paper, some models and methodologies of the knowledge discovery process are compared and a method of knowledge acquisition from an internal database is proposed. The presented approach is dedicated to industrial enterprises that develop modifications of previous products and are interested in obtaining more precise estimates for project planning and scheduling. The example contains four stages of the knowledge discovery process including data selection, data transformation, data mining, and interpretation of patterns. The example also presents a performance comparison of intelligent systems in the context of variable reduction and preprocessing. Among data mining techniques, artificial neural networks and the fuzzy neural system are chosen to seek relationships between the duration of project phase and other data stored in the information system of an enterprise.

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