Prima vera: Synergising predictive maintenance

The full potential of predictive maintenance has not yet been utilised. Current solutions focus on individual steps of the predictive maintenance cycle and only work for very specific settings. The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. The PrimaVera project has identified four obstacles to tackle in order to utilise predictive maintenance at its full potential: lack of orchestration and automation of the predictive maintenance workflow, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. Furthermore, an intuitive generic applicable predictive maintenance process model is presented in this paper to provide a structured way of deploying predictive maintenance solutions

Electrochemical Characterization of Low Temperature Thermal Aging Embrittlement of Stainless Steel 304L Weld

Abstract. Thermal aging embrittlement of type 304L stainless steel weld is investigated on the basis of changes in microstructure, microhardness and electrochemical behavior after aging up to 20,000 h at 335, 365 and 400 °C. Spinodal decomposition and G-phase precipitation in the ferrite was observed after thermal aging. Aging led to increase in the hardness of ferrite phase while there was no change in the hardness of austenite. The changes in electrochemical behavior due to aging were studied using double loop electrochemical potentiokinetic reactivation (DL-EPR) test. Aging led to increase in the DL-EPR value which is attributed to Cr depletion in the ferrite phase