Speeding-up the prototypes development, optimizing the shape of the components, increasing the quality of the manufactured goods, preventing failure and interruptions during processes are essential aspects to address in order to save time and money in industrial engineering and productions processes. Ad-hoc mathematical models and algorithms, together with user-friendly software and dashboard, can incredibly help to address these issues.
M3E develops mathematical models and algorithms customized for the specific industrial process of the clients, that can simulate multiple aspects (e.g. fusion, injection, diffusion of temperature etc.). Developing a mathematical model of the process that can be used for optimization and automatic design purposes, finding in a short amount of time the optimal design or configuration of the system. For this approach, M3E uses best-in-class multi-objectives optimization libraries, gaining significant competitive advantages with respect to other commercial software.
Moreover, M3E implements data-driven model based on large dataset (Big Data) provided by the clients, in order to develop predictive models. Such approach, based on Data Analytics and Supervised and Un-Supervised Machine Learning techniques, find large applications in predictive maintenance and predictive quality activities. It is possible in fact identify patterns in the acquired data, and estimate when an anomalous condition may arise.
Main activities include:
• the simulation of production processes (fusion, injection, diffusion of temperature, etc.)
• the multi-objectives optimization of manufactured goods and process;
• virtual prototyping
• data analysis for predictive maintenance and quality
