Inventory policies for a remanufacturing system with returns forecast from past sales
PhDs and postgraduate research
Self-funded PhD students only
School of Mathematics and Physics
Applications accepted all year round
The work on this project could involve:
- Investigate the optimality of a feasible inventory policy for the remanufacturing system with returns forecast from past sales.
- Propose and investigate a heuristic inventory policy that can be practically implemented for the system.
- Provide a theoretical guarantee, supported numerically, for the closeness of the heuristic inventory policy to optimality.
Environmental sustainability has attracted increasing attention in recent years as a result of the negative human impact on the environment. Humans impact the environment negatively through pollution, whereby used products are abandoned and left to disintegrate on their own without proper handling. This negative human impact on the environment has for example led to unfavourable climate change occurring in the world now.
Remanufacturing, an advanced form of recycling, is often considered an environmental preferable choice of end-of-life option in comparison to material recycling or manufacturing new products. As a preferable option for environmental gains, remanufacturing has the advantages of alleviating the depletion of resources, reducing global warming potential. Examples of remanufactured products are engines, photocopiers, toner cartridges, and the like.
In this project, we consider a periodic review inventory model for a remanufacturing system that has its returns of products at the end of their lives modelled to depend on past sales. Returns of used products that are sold previously is the focus of the remanufacturing industry, and these used products can be purchased by the remanufacturer at a cost. We call these buyback cores . We investigate inventory policies on remanufacturing these cores to serviceable products that are as good as new in a finite horizon setting so that system cost is kept as low as possible.
Fees and funding
Funding availability: Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).
2020/2021 entry (for October 2020 and February 2021 entries)
Home/EU/CI full-time students: £4,407 p/a
Home/EU/CI part-time students: £2,204 p/a
International full-time students: £16,400 p/a
International part-time students: £8,200 p/a
PhD by Publication
External candidates £4,407 p/a
Members of staff £1,680 p/a*
2021/2022 entry (for October 2021 and February 2022 entries)
PhD and MPhil
Home/EU/CI full-time students: £4,407 p/a*
Home/EU/CI part-time students: £2,204 p/a*
International full-time students: £17,600 p/a
International part-time students: £8,800 p/a
All fees are subject to annual increase.
PhD by Publication
External Candidates £4,407 p/a*
Members of Staff £1,720 p/a*
If you are an EU student starting a programme in 2021/22 please visit this page.
*This is the 2020/21 UK Research and Innovation (UKRI) maximum studentship fee; this fee will increase to the 2021/22 UKRI maximum studentship fee when UKRI announces this rate in Spring 2021.
Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.
You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
A good first degree or MSc degree in Mathematics, Operational Research or Industrial/Manufacturing Engineering with strong quantitative background. The candidate should have the ability to read and write mathematical proofs, and have programming experience.
How to apply
We’d encourage you to contact Dr Chee Khian Sim (email@example.com) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, you can use our online application form. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
If you want to be considered for this PhD opportunity you must quote project code SMAP5340220 when applying.