Ritwik Basu

Applying machine learning techniques such as Random Forest, Gradient Boosting, and Lasso regularization to optimize processes, reduce defects, cut processing time, and minimize resource wastage in manufacturing operations., Developing time series models to forecast furnace parameters, optimizing energy consumption, ensuring consistent material properties, improving operational reliability, and reducing process variability for enhanced manufacturing efficiency., Conducting statistical process control using Design of Experiments (DOE) and ANOVA to identify key manufacturing factors, enhance efficiency, improve durability, and reduce operational costs across production processes., Integrating imaging data with clustering models and statistical analysis techniques to guide material selection, ensure quality standards, and improve production outcomes through data-driven decision-making., Forecasting microstructural changes in materials by using advanced analytics to optimize manufacturing processes, improve structural integrity, and predict critical parameters for manufacturing and material performance., Optimizing predictive maintenance using Random Forest and XGBoost models to minimize downtime, enhance operational reliability, and boost overall efficiency in heavy manufacturing and steel forging environments.

Delivered training and technical support on advanced microstructural analysis techniques, focusing on Electron Backscatter Diffraction (EBSD) and Energy Dispersive Spectroscopy (EDS), enabling clients to enhance research outcomes and quality control processes.
Guided clients in applying EBSD and EDS techniques for improved material optimization, facilitating detailed microstructural characterization and advancing manufacturing processes through precise and actionable insights.
Utilized advanced statistical analysis and data visualization methods to interpret microstructural data, providing clients with comprehensive insights into material properties and their impact on performance and reliability.
Enhanced client outcomes through expertise in microstructural analysis tools, aiding in the adoption of cutting-edge technologies and techniques for research, development, and quality assurance in material science applications.

Led in-process inspections and quality assurance by monitoring production stages, identifying deviations, and implementing corrective measures to ensure adherence to design specifications and maintain product reliability.
Developed technical documentation and 3D designs using AutoCAD, creating detailed blueprints and schematics to support manufacturing processes and facilitate accurate assembly, reducing design errors and improving operational efficiency.

Managed daily production planning and operations in machine shops and heat treatment facilities, optimizing resource allocation, ensuring process efficiency, and meeting production targets within strict deadlines and quality standards.
Supervised manufacturing workflows by coordinating tasks, monitoring equipment performance, and troubleshooting operational issues to maintain seamless production processes and deliver high-quality forged components.

Assigned workloads and monitored production targets to ensure timely delivery of high-quality products, while maintaining adherence to production schedules, resource utilization, and operational standards in a fast-paced manufacturing environment.
Supervised and optimized production processes by coordinating team efforts, addressing bottlenecks, and implementing quality control measures to enhance efficiency and meet organizational goals effectively.

Developed a flexible skill education model aligned with government guidelines, fostering industry-ready skills by integrating innovative teaching methodologies and advanced curricula tailored to the evolving needs of the workforce.
Collaborated with Swiss experts to establish state-of-the-art machinery and infrastructure for skill-based training programs, enhancing the quality of technical education and improving hands-on learning opportunities for students.
Designed and implemented academic programs focused on skill development, ensuring alignment with industry standards and preparing students for technical roles through practical training and theoretical knowledge.
Mentored students and faculty members to enhance their technical expertise, encouraging research-driven initiatives and promoting continuous learning to support the university's vision of providing high-quality skill development education.

Introduced data science applications in manufacturing engineering courses, incorporating Python for process optimization and failure prediction, enabling students to understand and implement cutting-edge techniques in industrial applications.
Conducted advanced research in data-driven techniques, securing industry project funding to support innovative studies and practical applications, fostering collaboration between academia and industry.
Designed and delivered academic curricula focusing on the integration of data science with mechanical engineering principles, bridging the gap between theoretical knowledge and real-world industrial challenges.
Mentored students on research projects and guided them in exploring predictive analytics and process optimization, contributing to their academic growth and preparing them for successful careers in engineering and data science.

Focused on NiTi Shape Memory Alloys, researching processing and microstructure design using statistical and machine learning techniques.
Developed predictive models for alloy properties and material behavior optimization.

Led data-driven research in mechanical engineering, focusing on predictive analytics and process optimization, advancing knowledge in the application of data science to solve engineering challenges in industrial settings.
Supervised student projects involving predictive modeling and data analysis, guiding students to apply theoretical concepts to real-world engineering problems and fostering critical thinking and innovation in data-driven solutions.
Developed and delivered academic courses on predictive analytics and machine learning, equipping students with the skills needed to apply data science techniques to enhance manufacturing processes and operational efficiency.
Collaborated with industry partners to integrate practical, data-driven research into the academic curriculum, bridging the gap between academic learning and industry requirements while securing funding for projects and research initiatives.