Dr Navid Sahebjamnia
Senior Lecturer in Operations and Information Management
- Innovation and Sustainability
- Brunel Business School
- College of Business, Arts and Social Sciences
Research area(s)
Navid's research is centered around creating mathematical models to optimize supply chain and logistics operations. His passion lies in developing multi-objective and stochastic programming models to achieve sustainability and resilience objectives. His expertise includes:
- Sustainable and Resilient Operation Management,
- Supply Chain and Logistics,
- Multi-Objective and Stochastic Programming Methods,
- Business Analytics.
Navid is dedicated to leveraging his extensive knowledge and skills to drive a significant and positive transformation in the operations management of the transportation, Agri-Food, and Primary industry sectors.
Research grants and projects
Grants
Funder: European Commission
Duration: December 2023 - December 2026
Manufacturing and logistics companies are subject to unforeseen events that disrupt the supply chain, causing production slowdowns, reduced output, and increased costs, making it difficult to meet customer demand. To mitigate these risks, manufacturers must build resilience across entire value chains. NARRATE will develop a sophisticated tool using AI, Digital Twin, and IoT technologies allowing end-to-end visibility and control over supply chain operations to monitor and predict potential disruptions, enabling supply chains to achieve improved resilience. The Intelligent Manufacturing Custodian (IMC) will leverage data from various production sources to enable proactive decision-making and act as a nerve centre for a supply-chain network, providing real-time monitoring and coordination of intelligent production processes and logistics. Integrating an IMC into a supply-chain will evolve its operations into Smart Manufacturing Network (SMN): a connected and self-orchestrated ecosystem linked end-to-end with programmable Manufacturing-as-a-Service capabilities that can withstand disruptions. A Digital Twin will provide a reliable model to represent production and operational data of an SMN to unlock deeper IMC intelligence. Collected data will train machine learning models to predict potential disruptions, such as natural disasters or delayed shipments. AI algorithms will analyse the data and provide real-time reporting and visualization on a dashboard. The IMC and Digital Twin interaction will generate powerful insights and self-adapting abilities that support an SMN to evolve under human supervision by switching services between multiple external partners to respond to risks and disruptions and improve energy efficiency, product circularity and environmental sustainability across the entire production process. The effectiveness of NARRATE will be evaluated by testing the IMC in real production environments in quite diverse industry sectors.