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(A*STAR) Simultaneous optimisation of production scheduling and cleaning scheduling in pharmaceutical plants under uncertainty


Department of Chemical Engineering & Analytical Science

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Dr J Li , Dr N Zhang No more applications being accepted Competition Funded PhD Project (European/UK Students Only)

About the Project

Pharmaceutical industries have great contribution to the economic development and human health. Most processes in pharmaceutical plants are batch processes. Scheduling is one of the important optimisation tools to improve their operational efficiency, reduce operating cost and improve profit margin. The operations in pharmaceutical plants often include production, cleaning, and maintenance. Scheduling of production operations in pharmaceutical plants are often separated from scheduling of their cleaning and maintenance operations, which will reduce their profit margin and result in orders unmet. Therefore, simultaneous optimisation of production scheduling and cleaning scheduling is very important. In this project, we will use advanced mathematical modelling approach especially mixed-integer programming approach to develop reliable and efficient mathematical models for this simultaneous optimisation. The solution approach combining deterministic approach and stochastic approach will be proposed to solve the model to near global optimality within reasonable computational time. During operations, some uncertainty often happens such as processing time variation, demand fluctuation, and product quality variation. The schedules based on deterministic parameters are often suboptimal or infeasible. In this project, we will apply robust optimisation techniques to obtain robust schedules with incorporation of different uncertainties in the operation.

Entry Requirements:
Applications should be submitted online and candidates should make direct contact with the Manchester supervisor to discuss their application directly. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.

Funding Notes

This project is available to UK/EU candidates. Funding covers fees (UK/EU rate) and stipend for four years. Overseas candidates can apply providing they can pay the difference in fees and are from an eligible country. Candidates will be required to split their time between Manchester and Singapore, as outlined on www.manchester.ac.uk/singaporeastar.

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

References

1. Nikolaos Rakovitis, Jie Li, Nan Zhang, A novel modelling approach to scheduling of multipurpose batch processes, Proceedings of the 13th International Symposium on Process Systems Engineering – PSE 2018 July 1-5, 2018, San Diego, California, USA.

2. Jie Li, Xin Xiao, Christodoulos A. Floudas, Integrated Gasoline Blending and Order Delivery Operations: Part I: Short-Term Scheduling and Global Optimization for Single and Multi-Period Operations, AIChE Journal, 2016, 62 (6), 2043-2070.

3. Jie Li, Christodoulos A. Floudas, Optimal Event Point Determination for Short-Term Scheduling of Multipurpose Batch Plants. Industrial and Engineering Chemistry Research, 2010, 49, 7446-7469.

4. Nikolaos Rakovitis, Jie Li, Nan Zhang, New Approaches for Scheduling of Multitasking Multipurpose Batch Processes in Scientific Service Facilities, Proceedings of the 28th European Symposium on Computer Aided Process Engineering, June 10-13, 2018, Graz, Austria

5. Nikolaos Rakovitis, Jie Li, Nan Zhang, A New Approach for Scheduling of Multipurpose Batch Processes with Unlimited Intermediate Storage Policy, IEEE-2018 5th International Conference on Control, Decision and Information Technologies, Thessaloniki, Greece 2018
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