Enterprise Resource Planning (ERP) systems are essential for industrial companies to automatize and monitor their business processes in order to boost their competitiveness. ERP systems are generic software designed to serve a large variety of companies with different business processes. Therefore, they have many configuration options to support various business processes used in different companies. The implementation process of an ERP system consists in assigning values to ERP parameters according to the company requirements: It determines the exact operations and processes supported by the system in the specific company. Infologic is a French company that develops and integrates their own ERP system called Copilote. It has thousands of parameters that are used to adapt it as precisely as possible to customer requirements. However, this flexibility makes the implementation of Copilote a time consuming task that requires a deep knowledge of its functionalities and parameters. Reducing the complexity of the implementation of Copilote is a critical issue for Infologic who needs to integrate efficiently new system integrators to meet the demand of new customers. In this thesis, we study the implementation process of Copilote in order to understand the main issues encountered by Infologic. We propose a new approach for extracting a catalog of configuration parts from existing configurations of Copilote, and each configuration part is associated with the business requirement it fulfills in order to reuse it for next implementations of Copilote. To this aim, we propose to use constraint programming (CP) to easily integrate feedbacks of experts by means of new constraints or criteria. We introduce new CP models to solve conceptual clustering problems and a new global constraint for the exact cover problem with several propagation algorithms. We show it allows to model easily conceptual clustering problems and to solve it more efficiently thant existing delcarative approaches.