Process variability aware Health Index for the optimal cutting blade replacement in industrial environments

Avoiding downtime is one of the major concerns of manufacturing industries. In the era of the connected industry, acquiring data has become cheaper than ever but, at the same time, how to turn that data into operator actionable insight is not always obvious. This work proposes an approach to develop a Health Index that is based on the cross-matched data created in an industrial setup. For the creation of this Health Index a usage based model that considers the type of material being cut is proposed and compared with a simpler Weibull distribution based survival approach. In addition, different strategies that consider key economic actors, such as unprogrammed blade replacement and programmed replacement, are consider to re-scale the Health Index.According to the results, considering the process variability improves the accuracy of the modelling of the data. However, a good definition of the cost is really the most important and decisive factor for the development of the Health Index.