Il progetto automatizza l’analisi causa-effetto con algoritmi e IoT per migliorare il monitoraggio e ridurre errori e guasti.
Automac
Politecnico di Milano - Enginsoft
Automac Srl is an Italian company, specializing in the design and manufacture of mechatronic systems for the automation of assembly and testing processes.
Assembly process automation systems, particularly in the Automotive accessories sector, are composed of mechatronic modules (PLCs, sensors, electric or pneumatic actuators, control logic) and equipped with an advanced monitoring system capable of controlling productivity indices (throughput and availability) in real time. However, cause-and-effect correlation analyses (failures and possible origins) are the result of experience and key, highly specialized skills, and not of automatisms or algorithms developed autonomously by the system.
Development of a solution for predictive maintenance of production facilities based on artificial intelligence algorithms.
Advanced machine learning models capable of self-learning the fault diagnostic process and autonomously interfacing with the company’s logistics system for automatic management of the worn component procurement process.
Implementation of an IoT platform equipped with an HMI interface for remote reporting of operating states and faults.
Ability to granularly collect alarm and messaging data through which, with a predictive approach, anomaly detection and root cause analysis processes are implemented. In this way, Automac systems will be able to provide the suggestion on how to solve an anomaly with the indication of the root cause that triggered it.
Ability to predict potential failures before they occur through a combination of monitoring systems, machine learning techniques and artificial intelligence. This application enables analysis and prevention of failures of module tools such as riveting, screwing and tapping, preventing wear and tear; electric drives; pneumatic drives; belt conveyor systems; and vibratory feed systems.
A marked competitive advantage is created by reducing the cost of plant management by the customer who will implement Automac solutions.
The foundations for new business models are developed, for example by breaking down traditional supply paradigms, such as the pure sale of production equipment, to propose new, more competitive formulas, such as the rental of production capacity.
It increases the ability to control and monitor plant performance and, as a result, optimizes the management of maintenance activities; in fact, it allows maintenance to be strategically managed resulting in the reduction of the total cost of the production assets involved and the optimization of spare parts inventory.
