Development of a hybrid predictive maintenance model

Abstract

Progress in the field of technology and science enables the digitalization of manufacturing processes in the era of Industry 4.0. For this purpose, it uses tools which are referred to as the technological pillars of Industry 4.0. Simultaneously with the changes in the field of manufacturing, the interdisciplinary cooperation between production and machine maintenance planning is developing. Different types of predictive maintenance models are being developed in order to ensure the good condition of the machines, optimize maintenance costs and minimize machine downtime. The article presents the existing types of predictive maintenance and selected methods of machine diagnostics that can be used to analyze machines operating parameters. A hybrid model of predictive maintenance was developed and described. The proposed model is based on diagnostic data, historical data on failures and mathematical models. The use of complementary types of predictive maintenance in the hybrid model of predictive maintenance is particularly important in the case of high-performance production lines, where high quality of products and timeliness of orders are crucial.