MAP4ID-Multipurpose Analytics Platform 4 Industrial Data
The MAP4ID project fully addresses some of the emerging issues in the context of enterprise information systems and platforms supporting the development of new paradigms emerging from the migration towards the Industry 4.0 paradigm.
The partnership involved in the development of MAP4ID has decided to address the ambitious goal of developing a research phase on three purely industrial issues dictated by as many different key users involved collaterally to the project, which is aimed at the definition of a new ambitious product/service to be brought to market in a synergy of intent and resources among all actors involved.
The aim of the project is to create a technological contribution that can be quickly extended and customized to meet the diverse business needs of small and medium-sized SMEs in filling a gap in information systems and processing services that would require time, investment and qualified personnel to be realized.
The MAP4ID project, therefore, has the ambitious goal of transferring new methodologies, technologies and tools born in the world of academic research, to the industrial context, but all oriented to concrete cases of real key-users and with the stated objective of defining a platform of services that can be easily customized, used and managed in daily operations in different contexts and in different industrial scenarios.
In many of the operational scenarios where the project proponents have operated in the course of the most recent project initiatives, it is noted that the biggest issue was having to guarantee the company’s ownership that the data transmitted out of it was not distributed and saved on “public” cloud systems but on specific server machines installed at their premises or at the partner’s offices. This sense of concern and mistrust towards possible uncontrolled and unclear access to operational data that may characterize important competitive information for an SME with active patents on manufacturing processes or unique product features pushed them to renounce to a massive integration with the outside world and in particular with the Industrial IoT, in order to preserve the privacy and anonymity of their own production feature.
In order to address these operational issues, Intelligentia has made targeted investments over the last few years in the development of a Cloud services platform based on some of the best known and established OpenSource technologies for hosting and distributing specific content in industrial contexts. The platform called ELISA (Enterprise Light Information System Architecture) has been revised several times over the years to try to integrate the most requested features emerging from the field.
In the course of the project, leveraging the three real application cases, a new product will be realized based on the lessons learned from ELISA, but at an even lower level, i.e. a PaaS (Platform as a Service) that can be directly integrated and used also by other system integrators and partners. All this by adding the main Artificial Intelligence techniques as plug&play application modules that can be reused in different operational contexts.
The project, therefore, goes in the direction of creating a new product that leverages the state of the art and industrial applicability of data analysis and reasoning methodologies born in the field of computer science research, dropping them into three case studies in as many industrial companies belonging to the Intellimech Consortium. In particular, the case studies will concern:
– A case study on predictive maintenance applied to the context of a company producing textile looms
– A case study on production optimization in a complex environment with high production variants in the beverage industry
– A case study on vision technologies for quality and compliance of electrical panels