"SAIN4" SAIN4. ADVANCED PRODUCTIVE EFFICIENCY SYSTEMS FOR THE 4.0 INDUSTRY DESCRIPTION This project pursues the development of an Advanced Management System that allows companies in the Wood-Furniture and Metalworking sectors to increase their productive efficiency through support in decision-making, based on the capture and statistical analysis of process data manufacturing. To do this, it will be necessary to address technological challenges in the Big Data domain for the construction of a Production Efficiency Prognosis Engine, Machine Learning to identify the analysis techniques of the key variables of the manufacturing process and Business Intelligence to incorporate support elements to decision making. OBJECTIVES 1 Define an 4.0 Industry Reference Model, which allows (i) to conceptualize the 4.0 Industry paradigm, laying the foundations for the construction of the intelligent management system, and (ii) assessing the situation of an industrial company regarding its level of digitalization, and therefore the feasibility of achieving clearly positive results by implementing the systems developed in the project. 2 Design and build a Big Data and Data Capture infrastructure, after identifying the relevant data, which allows capturing, storing, processing and analyzing large volumes of data for the construction of predictive models that allow improving the efficiency of the production processes involved. 3 Design and build an Advanced Management System that allows visualizing, analyzing and interpreting the measurements of the manufacturing process for the improvement of productive efficiency through support in decision making. To do this, a Prognosis Engine will be used to model and recommend improvements to the OEE indicators. 4 Design and execute a Pilot Project that serves to demonstrate the validity and effectiveness of the Advanced Management System in two pilot companies, previously selected through the application of a selection methodology based on the I4.0 Reference Model. 5 Implement a Results Transfer plan, which includes actions to promote and transfer the results obtained in the project, including the companies participating in the Pilot Project and those belonging to the Valencian industry of the sectors object of the project. Project Number: 21700073 Grant Agreement: IMDEEA / 2017/81 Duration: From 01/01/2017 to 30/06/2018 Coordinated in AIDIMME by: SÁNCHEZ ASINS, JOSÉ LUIS R&D Line: TO BE DETERMINED RESULTS OBTAINED 2018 Year: Big Data and data capture infrastructure Deliverables:    2018 Year: Prognosis Engine Deliverables:    2018 Year: Development of the advanced management system Deliverables:    Year 2016: Review of the state of the art regarding the fundamental concepts of Industry 4.0. This analysis has been carried out based on the review of more than ninety bibliographical references cited in deliverable E 1.1 – Report on the state of the art of Industry 4.0. The analysis is approached from several perspectives: - The origin and impact of Industry 4.0 at all levels are reviewed, describing the potential benefits or competitive advantages that the adoption of the paradigm could bring to companies. - A review is also included regarding the impact of the paradigm on the training needs of people, as one of the central axes of the industry of the future. - The key concepts for the development of the industry model of the future are reviewed and a technical analysis of the most important digital enablers that may have the greatest impact on companies in the sectors involved in the project is carried out. - The most relevant agents and initiatives at national and European levels are identified and are related to Industry 4.0. European projects whose themes could be included in this field are included. - The new business models that could be developed within the framework of the digitalization of the industry are described, exploring some reference examples. Deliverables:    2017 Year: Global architecture of the Big Data Analytics and Data Capture infrastructure that will allow the construction of the Prognosis Engine for productive efficiency and will support the execution of the Advanced Management System (SGA) in the pilot environment. Deliverables:    PUBLISHED NEWS general broadcast http://www.noticiashabitat.com/2017/comienza-la-instalac (...) http://www.noticiashabitat.com/2018/medicion-de-parametr (...) http://actualidad.aidimme.es/2018/02/22/medicion-paramet (...) http://actualidad.aidimme.es/2017/06/22/comienza-la-inst (...) PARTNERS ITI-INFORMATIC TECHNOLOGY INSTITUTE, GRANT 147.875 € TARGET AUDIENCE AND IMPACT MEASUREMENT 2343 Access to the project website 349 Access to news published on own websites. Total Accesses: 2692 TRACTOR COMPANIES Thanks to its support and signature of the "declaration of participation" the project has been funded. COMPANIES DIFFUSION R&D PROJECTS They want to know first-hand the evolution of the project, and its progress to the final result. COMPANIES TRANSFER KNOWLEDGE They will implement technologies, develop strategies or look for new models based on the results.