The Fourth Industrial Revolution enables manufacturers to reduce their costs and improve the quality of both the products and production lines. As a result of comprehensive acquisitions, it provides an increase in overall productivity and profitability. Industry 4.0 and digital transformation of the manufacturing environments provides a complete connectivity with real-time processing abilities. The increasing amount of business data across industry verticals and the rising demand for market and competitive intelligence have fueled the growth of predictive analytics solutions within the organizations.

PIANiSM aims at putting together predictive and prescriptive maintenance techniques in order to achieve an end-to-end automated manufacturing process and optimize end-to-end manufacturing value chains. To disrupt traditional maintenance processes in manufacturing environments, a sophisticated system is required. This system will cover a wide range of domains such as data science, machine learning, analytics, simulation, real-time processing. PIANiSM will provide related missing analytics techniques and algorithms, introduce new generation data identification & integration & modeling processes, and try to put standards in order to enable more flexible and applicable solutions for manufacturers.

Manufacturers try to reduce both maintenance costs and downtime and increase equipment lifecycles. The PIANiSM project addresses the challenges of the transition to the predictive maintenance technology.

• Social challenges the challenges of the manufacturing companies
• Economical challenges
• Technical challenges