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A Comprehensive Signal Processing and ML Solution for Prognosis and Diagnosis of Faults and Rotating Machinery using Vibration Signals

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 […]

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An ML Solution to Identify the Root Cause of Yield Loss in Semiconductor Manufacturing

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 […]

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An ML Solution for Predicting the Remaining Useful Life of a Ball Bearing Based using Vibration Sensors Data.

Accurate failure time estimation of mechanical components plays a significant role in enhancing the reliability of the machines. Ball-bearing failures are the most probable failures in the industrial rotating machinery. Therefore, predicting the remaining useful life of ball bearing proves to be helpful for maintenance scheduling. In data-driven methods for prognostics, the remaining useful lifetime […]

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Predictive Maintenance/Industry 4.0

An ML Software Solution for the Root Cause Analysis of Industrial Plant Faults. 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. […]

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