janak suthar
Institute of Rural Management Anand, Zensung pvt ltd, Indian Institute of Management Mumbai
Research areas: Engineering · Mechanical Engineering · Advanced machining processes and optimization · Advanced Machining and Optimization Techniques · Fault Detection and Control Systems
0000-0001-7964-8093
About
Janak Suthar is an Assistant Professor at the Institute of Rural Management, Anand (IRMA), in Production and Operations Management (POM&QT). Before his academic role, he held the position of Data Analyst at Zensung Pvt Ltd in Mumbai, India. Dr. Suthar is an accomplished professional with a robust background in Operations Management.
He earned his Ph.D. in Operations Management and supply chain from the Indian Institute of Management Mumbai (NITIE) and holds a Master's in Engineering in Manufacturing Systems from Mumbai University. Driven by a passion for research, Janak has contributed significantly to esteemed international journals such as Computers in Industry and the International Journal of Reliability and Quality Management.
His research focus encompasses the applications of artificial intelligence and machine learning, along with the optimization of manufacturing processes. Beyond his research endeavors, Janak brings a wealth of teaching experience, covering diverse subjects, including Operations Management and supply chain management, Project Management, and practical applications of Machine Learning.
Employment
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Institute of Rural Management Anand Assistant Professor2023 - Present
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Zensung pvt ltd Data Analyst2022 - 2023
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National Institute of Industrial Engineering Research scholar2018 - 2022
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (9)
- Modeling blockchain implementation barriers for sustainable supply chains: an ISM-MICMAC study of Indian SMEs Save
- Data-Driven Process Management for High-Quality Hip Joint Implants—A Case Study in Investment Casting Save
- Exploring smart quality predictive modelling approach: a case study of the injection-molding industry Save
- Analytical modeling of quality parameters in casting process – learning-based approach Save
- Critical parameters influencing the quality of metal castings: a systematic literature review Save
- Drilling process improvement with genetic algorithm Save
- EDM parameters optimization for sustainable machining Save
- Drilling Process Quality Improvement by Grey Relation Analysis Save
- Performance analysis of metaheuristics optimization techniques for drilling process on CFRP composites Save