The aim of this work is to propose a decision support system (DSS) to manage product life cycle in the middle of life phase in order to obtain data which may impact on the whole value chain. In particular, a new maintenance approach based on the integration of information gathered from different actors is taken under consideration and the evaluation of residual life cycle costs (LCCs) is used to define and plan maintenance actions. The system enables to create new value by transforming information into knowledge available for all phases of the life cycle improving product and service quality, efficiency and sustainability. The integrated DSS here described goes in the direction of predictive maintenance for machine tools and trucks to reduce the number of unexpected stops and minimise LCCs of the product avoiding component breakdowns.