Operations and Supply Chain Management and Optimisation
Operations and supply chain management
Today’s global competitive business atmosphere, stringent concerns from environmental, social, risk and uncertainty requirements have affected global supply chain network structures for manufacturing and service industries. As a result, firms have to restructure their supply chain orientation to be more cost-effective, more sustainable, more flexible, more adaptive, more resilient, more robust, and more responsive to customer requirements and changing global markets.
Our research pioneers in applying agent-based technology in modelling, simulating and optimising the configuration of multi-objective global supply chain network designs. Our solution frameworks and methodologies ranges from simulation, exact methods, metaheuristics (i.e., genetic algorithms, ant colony optimisation, bee colony, etc.), hybrid approaches (i.e., matheuristics, artificial intelligent, machine learning, etc.). The goal is to provide sustainable competitive advantages for companies.
Our research focuses on but not limited to
- multi-objective optimisation of supply chain operations to reduce cost, carbon emissions and delivery time;
- a coordination of project-based supply chains with dynamically changing project portfolios;
- model sourcing and inventory decisions in a multi-tier supply chain and the coordination and optimisations of such decisions across supply chain member; and
- design resilient and robust supply chain network design to incorporate uncertainty, risks, and disruptions (i.e., demand, supply, natural events, etc.)
Our research covers a broad range of issues associated with supply chain, which currently focuses on the following sub-areas:
- Discrete Event Simulation of Manufacturing Processes
- Logistics Management
- Operations & maintenance of offshore wind energy
- Project supply chains and dynamic portfolio management
- robust and sustainable resilient supply chain network design
- Sustainable Closed-loop supply chain management
|Professor David Zhang||Professor of Manufacturing systems||
|Professor Voicu Ion Sucala||Associate Professor in Engineering Management||
|Dr Baris Yuce||Lecturer in Engineering Management||
|Dr Martino Luis||Lecturer in Engineering Management||
|Dr Miying Yang||Lecturer in Engineering Management||
|Dr Shuya Zhong||Lecturer in Engineering Management||
|Sam John Abraham||KTP Associate||
- Luis, M., Irawan, C.A. and Imran, A. (2019). A two-stage method for the capacitated multi-facility location-allocation problem, Int. J. Operational Research, Vol. 35 (3), 366–377.
- Irawan, C. A., Luis, M., Salhi, S., & Imran, A. (2019). The incorporation of fixed cost and multilevel capacities into the discrete and continuous single source capacitated facility location problem. Annals of Operations Research, 275(2), 367-392.
- Zhong, S., Pantelous, A. A., Goh, M., & Zhou, J. (2019). A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms. Mechanical Systems and Signal Processing, 124, 643-663.
- Zhong, S., Giannikas, V., Merino, J., Lu, W., & McFarlane, D. Evaluating the benefits of picking and packing integration in order fulfilment warehouses. Under review with European Journal of Operational Research.
Supply chain design and safety stock placement (Prof David Zhang)
This project has developed tools and methodologies to analyse complex supply chains configurations, using problem solving methods such as swarm intelligence, multi-agent and ant-colony optimisation that mimic the behaviour of social insects. We have worked with CIFUNSA, the North America based largest foundries in the world supplying to the world top three automotive companies, to address the problem of supply chain (SC) configuration and safety stock placement. We have formulated the problem using an ant-colony algorithm with the total supply chain cost (inventory and production cost) and lead time as factors. Reductions have been made in inventory and cost of goods sold, amounting to an estimated £80M per annum.
KTP with Smart Manufacturing ltd Bideford (Academic supervisor: Prof Voicu Ion Sucala, KTP Associate: Sam John Abraham)
This KTP project is creating and implementing a dual-production business model and a novel modelling and simulation tool to enable the optimisation of multi production manufacturing flows. This is enabling Smart Manufacturing to design and manufacture new and highly specialised equipment for ATEX rated environments in parallel with its traditional bespoke products. The KTP also developed a novel knowledge management tool that helped Smart Manufacturing acquire and formalise the highly specialised knowledge on ATEX regulations and practices. Work is ongoing to extend and generalise this tool so that it can be used by manufacturing SMEs to consolidate compliance knowledge in resource constrained environments.
- University of Exeter KTP plays key role in the manufacturing process of the new Covid-19 vaccine
- KTP helps power production of the new Covid-19 vaccine
EPSRC Internet of Food Things Network Plus on "DISTINCT: IoT and big data for productive, safe and sustainable aquaculture" (PI: Dr Miying Yang, Co-I: Dr Martino Luis)
The project seeks to explore digital technologies and new business models to improve aquaculture farming productivity, food safety and sustainability across supply chain. This project captures the challenges across the aquaculture supply chain, uses Internet of Things and big data to help aquaculture farmers monitor the changes of the farming water, so that they can better control water quality, take preventative actions to reduce death and disease, and reduce environmental impact.
Sustainable Value Analysis Tool (PI: Dr Miying Yang)
The tool is designed to help companies identify new opportunities to create and capture sustainable value by analysing value uncaptured for key stakeholders across the supply chain. Uncaptured value exists in almost all companies. Some uncaptured value is visible and some is invisible. Identifying the uncaptured value and creating value from it is not always easy. The tool supports this process, providing companies with a scheme to systematically look for each form of value uncaptured across the supply chain, and with a method to turn the identified value uncaptured into value opportunities. The tool has been used by over 50 companies in the UK, China and Brazil in business training programmes.