Two of Prysmian Group’s flagship factories are discovering how to become even more efficient by analyzing their production data to improve manufacturing processes. This Big Data project is being carried out in Italy at the FOS optical fibres plant in Battipaglia and the submarine cables factory at Arco Felice using new enhanced tools based on advanced statistical algorithms and machine learning, in order to prevent quality issues, reduce costs and improve operations.
The Prysmian team working on this Predictive Quality project includes people from Digital Innovation Lab, HQ Quality, FOS Quality, FOS R&D, and Arco Felice Process Engineers, in partnership with MoxOff, a spin-off created at Politecnico di Milano to apply mathematics to industrial processes. The first round of analysis performed over the last month went well, and the project has now entered a second phase at FOS, where the team is implementing a customized solution to support the plant in reaching a challenging business objective.
“Predictive Quality” solutions are used to help manufacturers gain insights into the quality aspects of their production processes by crunching their data and applying predictive algorithms in order to reduce losses incurred due to quality issues, and to recommend corrective actions. Even at a high-tech factory, production problems can be traced to four main areas: men, machines, method, or material. In other words, human error, a machine glitch, a faulty operating procedure, or inadequate raw materials. Using Big Data analysis can help manufacturers get ahead of the curve, predicting these problems rather than reacting to them.