29 May 2018
Predictive maintenance makes it possible to detect in real time on the machines the warning signs of the defects, which will avoid costly production shutdowns.
The communicating industry will drastically change our ways of working; for the benefit of the man who will be more soliciting to understand, decide, collaborate and imagine, and therefore less to operate. It is in this mind that Sirfull – with SiRFULL® | Asset Performance Management – outlines Industry 4.0 as a set of solutions to collect data throughout the life of the industrial asset:
– The collection begins during the manufacturing process by manual or automatic actions;
– It next continues during the maintenance process and integrates information from field surveys carried out by the operators or directly by communicating sensors.
The collection and processing of this data – thus allowing anticipation of breakdowns – is made possible by new technical innovations born of Industry 4.0. For example the “Smart REX” – an intelligent assistant to anticipate a failure from spreading from one asset to another by quickly identifying the trigger spot. Moreover the connection of the “Smart REX” to different sensors – allows you to trace thousands of data and to do various treatments in real time, such as:
– thickness measurement;
– process data that can influence the degradation modes of materials;
– operating data of rotating machines such as vibration sensors.
– The development of predictive algorithms – allows the setting up of alert thresholds allowing the anticipation of events, notable thanks to the Learning machine;
– The modeling of failure schemes – test correlated with the criticality of the asset.
Ergonomic visualization tools to instantly identify a deviation in the state of assets with KPIs:
– automatic notification systems (SMS, e-mail) to inform drifts of an asset;
– a large capacity for processing and updating information, to facilitate real-time decision-making based on reliable data.
To be able to work perfectly, a mastery of data is vital..
Big Data is the essence of Machine Learning. In addition, this innovation is the technology that offers a comprehensive utilization of Big Data.
Traditional analytics tools are not powerful enough to exploit big data values, but technologies such as Apache Mahout, SparkMLlib are particularly relevant for this.
Predictive maintenance has positive effects on these performance indicators (or KPIs) as follows:
– The improvement of the overall rates of return (TRG) of the asset;
– The reduction of the costs of repair and intervention of the asset;
– An improvement of the manufacturing quality of the asset.
At the time of industry 4.0, it is fundamental to find and implement all the possible optimization levers to maintain the competitiveness of the industry. Implementing predictive maintenance can streamline the process globally and generates cost and time savings that can be substantial.
Tomorrow companies that will turn to this type of maintenance will no doubt be the leaders of the 4.0 factory.
The SiRFULL® platform that we have designed offers these many features and uses dedicated to predictive maintenance, and that we invite you to discover on our website
Sirfull is a software vendor with a strong industrial culture and French know-how, which develops solutions that enable its customers to anticipate changes in their market.
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