Industrial analytics, the pros: between anomaly identification and prediction

Industrial analytics is a pillar of Smart Manufacturing. When the data ecosystem and the data-driven approach drive the business, the techniques of data collection, monitoring and analysis that industrial analytics involves are a fundamental element.

Industrial analytics: when a crisis drives innovation

The legacy of these last difficult – and tragic – years is there for all to see and new business and asset management models have been adopted in manufacturing companies to ensure survival.

The remote management of operation, the digital partnership with the different participants of the value chain that requires an immediate analysis of factory, logistics and distribution data. We have seen the exponential growth of IoT and IIoT solutions as a logical consequence, the request and the development of Digital Twin to simulate the behavior of complex systems in design, production, maintenance, up to sale, all the models and phygital systems that enable industrial automation, traceability tools and Real Time Location System that affect the Smart Product Lifecycle.

All this and much more has had an impressive acceleration with the global health crisis and an impact on the entire production and distribution system in the world. Therefore, before being applications and solutions, industrial analytics is a paradigm that covers the entire product life process, the only useful tool for enhancing data, or rather, Big Data.

Industrial analytics: what advantages in the Smart Factory

Industrial analytics includes both data monitoring and analysis applications, such as the latest generation SCADA (such as GE Digital’s HMI-SCADA iFix or Cimplicity), which can provide information on production flows and anomalies and logistics, and predictive ones such as AI and Machine Learning, which allow new operating methods, improve the use of resources to guarantee maximum flexibility to face market changes.

The industrial analytics application solutions therefore allow the collection and processing of data in order to optimize its use: it is no longer just a matter of acquiring data to extract information, but of creating digital models for the interpretation of Big Data, in order to ensure better operational continuity and resource management.

Thanks also to Internet of Things technologies, industrial analytics allows Chief Operating Officers to respond promptly to demand flows, but also to activate procedures that anticipate potential anomalies, breakdowns and downtime with constant analysis of production data.

The logical consequence is the improvement of products and an optimization of the use of resources, both in the plants and professional resources.

Industrial analytics allows comparison of collected data and better planning of production by identifying any problems in advance: the analytical processing of Big Data also allows for product quality control through periodic and accurate tests.

Furthermore, in the manufacturing sector, predictive maintenance of machinery is one of the most important benefits of industrial analytics, which affects the performance of plants and production lines.