Innovative fault prediction can play a crucial role in ensuring smooth and cost effective process management. In this project, we designed a solution for predicting failure events by leveraging modern bleeding edge AI techniques such as deep learning, meta-learning, Bayesian optimization etc. Using AI we were able to successfully predict process/plant faults from telemetric data. […]
Almost all kind of engineering industrial process and production is performed by rotating machinery like motors, pumps, gearbox, fans, and assembly lines, etc. The condition-based monitoring of these types of equipment helps to boost productivity and profitability. In recent years, the industry has moved steadily from reactive to predictive long-term maintenance. The vibration signals are […]
Semiconductor manufacturing is a complex process with hundred of subprocesses. Different sensors record diverse information including the profiles of tools used in each fabrication subprocess, temperatures, pressures, etc. The output of this process is a semiconductor wafer. Any malfunctioning subprocess can introduce a yield loss in the output wafer and hence render the entire batch […]
Why Predictive Maintenance is needed? Maintenance and reliability professionals in the manufacturing industry face a number of challenges, but the goal of any maintenance organization is always the same i.e. to maximize equipment availability. In order to achieve maximum availability, run-to-failure maintenance suggests that the equipment must be kept running until it fails. However, this […]
Root cause analysis (RCA) is a method of problem solving used for identifying the root causes of faults or problems. RCA is widely used in industrial process control, IT operations, health industry and accident analysis in aviation, nuclear plants and rail transport. Without delving in the intricate details of specific problems, several general conditions can […]
