Manufacturing companies struggle to be efficient and effective when conducting root cause analyses of production disturbances; a fact which hinders them from creating developing resilient systems. This article aims describe the challenges enablers identified in current research relating different phases analysis. A systematic literature review was conducted, total 14 17 are described. These cor...

Process mining provides analytical tools and methods which can distil insights about process behaviour from big process-related data. Yet challenges relating to the impact of poor quality data on event logs, input analyses, remain. Despite researchers raising concerns log quality, preparation is, in practice, generally handled mechanistically, focusing fixing symptoms rather than uncovering roo...

A daunting mine disaster took place in 13 May 2014 at Soma and 301 men lost their lives. Brief information about the Eynez coal mine and some of the inherent characteristics of the field in terms of their effects on mining are presented. This paper basically concentrates on the factors that played an important role in the occurrence of this disaster. Progress of mine fire, firefighting, and res...

Background and Aims: Leukoreduction of blood components has reduced the incidence of transfusion-associated adverse events. Leucofiltration is the most effective method of leukoreduction. We encountered haemolysis in a series of leucofiltered units. This stressed our precious inventory, added to financial loss, increased our turn-around time to issue leucofiltered blood units, and placed doubts...

Purpose Manufacturing companies struggle to manage production disturbances. One step of such management deals with prioritising those disturbances which should undergo root cause analysis. The focus this work is on two areas. First, investigating current challenges faced by manufacturing when analysis Second, identifying the stakeholders and factors impacted Understanding allows development mor...

A popular method to detect anomalous behaviour or specific failures in wind turbine sensor data uses a type of neural network called an autoencoder. These models have proven be very successful detecting such deviations, yet cannot show the underlying cause failure directly. Such information is necessary for implementation these planning maintenance actions. In this paper we introduce novel meth...