Predictive, Prescriptive and Detective Analytics for Smart Manufacturing in the Information Age

Investigation of Degradation and Upgradation Models for Flexible Unit Systems: A Systematic Literature Review

“…Adam Robinson [48], Pavlov et al [47], Garcia-Garza et al [44], Grohn et al [46], Du et al [45], Menezes et al [55], and Dong et al [19] investigated upgradation of a manufacturing system, which will help to enhance the performance and reliability of manufacturing equipment. Spendla et al [52], Dong et al [19], Fang et al [20], and Kaiser et al [71] present the predictive maintenance of machines using sensors degradation data for calculating the time to failure of various machines.…”

“…[54] An extended model with a system that connects a low-level execution condition monitoring information. [55] Presents the design and implementation of a conductance sensor for micromachining processes.…”

“…Nowadays, predictive maintenance is considered as the key point for many manufacturing industries because of a major part of the operational cost and system failure impacts on product quality and equipment availability. Menezes et al [55] explained that predictive maintenance considers close past information for predicting future tendencies, biases, behaviors, etc. through correlation.…”

“…The prescriptive maintenance empowers manufacturers to resolve their own maintenance needs without the need for a vast array of experts, as mentioned by Brian Brinkmann. Menezes et al [55] explained that prescriptive analytics finds the best route to operate (outputs) in the view of given information and models (inputs). Similarly, Lepenioti et al [61] said that prescriptive analytics tries to locate the best action for the future in the manufacturing industry and it is frequently considered as the subsequent stage towards improving data analytics maturity for business execution improvement.…”

A flexible alarm prediction system for smart manufacturing scenarios following a forecaster–analyzer approach

“…Smart Manufacturing leverages the tremendous advances in Big Data analytics to improve existing analysis capabilities and provide new ones, such as predictive analytics that analyze current and historical data to make predictions about future unknown events [31]. In this regard, the built forecaster allows to obtain future values of the sensors for a data-driven predictive analysis [30], by using models (i.e., analyzers) capable to detect events in the forecasted data. In this work, in particular, three different analyzers have been built for predicting three different types of alarms (see Section 3.2).…”