Nitish Singh joins OPAC
Nitish Singh has been appointed part time Assistant Professor at IE&IS. He combines his role at KMWE with research on smart manufacturing AI and operations research.
Researcher Nitish Singh has been appointed part time Assistant Professor at the Department of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology as of October 1. He is affiliated with the Operations Planning Accounting and Control research group OPAC and continues to work at high tech manufacturing company KMWE.
Dual role
Singh moves daily between academia and industry. At KMWE he works in complex manufacturing environments where technology planning and people intersect. He brings this practical experience into his role at OPAC where he conducts research on decision making in production and logistics.
Research domain
His research focuses on manufacturing technology AI and operations research. Within OPAC Singh studies how data and models can support better planning and control of industrial processes. A key element of his work is close attention to how these processes actually unfold on the shop floor.
Having seen firsthand what it takes to make high tech manufacturing smarter while working at KMWE, joining OPAC feels like a natural next step. It lets me bridge the gap between industry and academia.
Theory and practice
According to Singh progress in smart manufacturing emerges when theoretical insights are developed with a deep understanding of real world production. By combining mathematical modeling with hands on knowledge of manufacturing processes his work helps bridge analysis and execution.
Societal context
The societal relevance of this research lies in the need for industrial systems that operate more intelligently and resiliently. Improved planning and use of resources contribute to less waste more stable supply chains and an industry that can continue to innovate in a changing world.
Collaborative innovation
Within OPAC Singh places strong emphasis on collaboration between researchers and companies. Using data driven methods he aims to contribute to digital ecosystems in which knowledge is shared applied and developed jointly by high tech manufacturers.