Joyam Jayakumar

Experience

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  Bajaj Auto Ltd

  Jan 2018 - May 2018

  Inplant Trainee

  ▪ Designing components and working with a team to solve problems in the engine assembly department

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  Grind Master Machines Pvt. Ltd.

  Feb 2019 - Jun 2019

  Marketing Intern

  ▪ Generating leads for potential customers through targeted contact.▪ Providing comprehensive information about products and services to potential customers, responding to inquiries and encouraging engagement.

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  Werkzeugmaschinenlabor, WZL der RWTH Aachen

  Jan 2023 - Dec 2023

  Student Research Assistant

  ▪ Topic: - Use of supervised learning methods for the process evaluation of PECM▪ Carrying out experimental trials in the PECM machine▪ Pre-processing of raw data for the extraction of pulses▪ Performing feature extraction and feature selection using the Tsfresh library for time series data▪ Visualization of pulses and features to facilitate analysis▪ Development of a machine learning model to classify impulses based on processing stability

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  Alpamayo

  Jan 2024 - Jun 2024

  Machine Learning Engineering Intern

  ▪ Performing failure mode analysis of industrial machinery using machine learning models to improve predictive maintenance strategies.▪ Implemented condition monitoring through anomaly detection algorithms to improve early fault detection and reduce downtime.▪ Managed the loading, querying and visualization of data in InfluxDB to ensure efficient handling and analysis of time series data.▪ Executed feature extraction and feature selection processes using time series Python libraries such as Tsfresh.▪ Visualize complex data patterns using t-SNE charts, providing deeper insights and a better understanding of data distributions.▪ Development of anomaly detection models with an accuracy of over 90%, significantly improving the reliability of error detection▪ Co-authored a research paper using a publicly available dataset for demonstration purposes to potential clients Show less

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  Manufacturing Technology Institute – MTI der RWTH Aachen

  Jan 2024 - Sept 2024

  Master Thesis Student

  Topic: - Development of a data-driven process monitoring model with real-time capabilities for precise electrochemical machining (PECM)▪ Preprocessing of process signals▪ Performed feature extraction and feature selection▪ Development of a machine learning models for the prediction of occurrence of short-circuit▪ Validation of the model by using data from additional experimental trials