The constant demand for diversified/personalised consumers' goods leads to decrease time-to-market, and to plastic injection molds with smaller batch production, with no stock acceptable for cost and quality reasons. This generates huge productivity losses in the molding industry: - Tool Tuning is too long for tool makers before delivery of a turn key mold. - New production run set-up time is too long and generate too much scraps, due to different “operator and machine” parameters. Many approaches are currently adopted to reduce mold design and production time, but none of them addresses directly the parts productivity enhancement, where “trial & error” is still the most employed engineering approach. The innovative approach of Mold4ProdE is to develop and assess a methodology to tool makers, for them to propose and deliver quicker turn key intelligent molds, to clients with a reasonable extra cost, and offering them significant productivity enhancement. Technically, it aims at applying modern data mining techniques for modelling polymer injection molding process, based on virtual data coming from virtual sensors implemented in a CAD model of the mold. The purpose is to: - optimize the number and position of sensors in the mold - implement and assess the concept “Virtual Mold Signature” by using the data driven models, built from experimental data collected during production runs with sensors embedded in process equipments. Mold4ProdE shall also provide dedicated and optimised components for tool instrumentation, data collection and treatment. The project results will deliver the basis to efficiently use the intelligent moulds. This will move the European mold makers to the knowledge based service industry, identified as the key factor to increase their competitiveness. Project duration is 3 years and involves 12 mold makers, 4 end users, 7 RTD and 2 equipment suppliers, spanning the whole supply chain in more than 5 different application areas with 14 SMEs