Dr Sarah Marshall

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Senior Lecturer

Email: sarah.marshall@aut.ac.nz

ORCID: ORCID logo https://orcid.org/0000-0002-6220-2105

Academic appointments:

  • Senior Lecturer, Auckland University of Technology (2018 - ongoing)
  • Lecturer, Auckland University of Technology (2014 - 2017)
  • Teaching Associate, University of Strathclyde (2011 - 2013)

Qualifications:

  • PhD, University of Edinburgh
  • MSc, Victoria University of Wellington
  • PG Diploma Advanced Academic Studies, University of Strathclyde
  • BSc, Victoria University of Wellington
  • BCA, Victoria University of Wellington

Overview:

Dr Sarah Marshall is a senior lecturer in the Department of Mathematical Sciences at AUT. Sarah joined AUT in February 2014. Sarah completed her undergraduate studies in Economics, Psychology and Operations Research at Victoria University of Wellington. After graduating, she worked in the Australian stockbroking industry before returning to New Zealand to complete a Master of Science in Statistics and Operations Research at Victoria University of Wellington. Sarah completed her PhD in Management Science on the application of deterministic and stochastic models to product recovery systems at the University of Edinburgh in 2012. Sarah taught in the Department of Management Science at the University of Strathclyde in Glasgow for three years before beginning at AUT. Sarah is a member of the Mathematical Sciences Research Group and the Data Science Research Group. Her research focuses on the use of stochastic modelling to address problems of interest to business and industry. Examples of application areas include remanufacturing systems, inventory management and warranty cost analysis. Sarah has a keen interest in analytics is the Industry Liaison for the Master of Analytics. Sarah is a member of the ORSNZ Council and was co-chair of the 2016 Joint NZSA+ORSNZ Conference.

Research interests:

Stochastic modelling, in particular geometric process, Markov decision processes and queueing theory, with applications to warranty analysis, reliability, inventory management, product recovery and recycling.

Teaching summary:

2019 Teaching:
STAT600 Probability
STAT804 Optimization and Operations Research
STAT700 Applied Stochastic Models
STAT702 Industry and Business Analytics

Research outputs:

Journal articles

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2020). Nonzero repair times dependent on the failure hazard. Quality and Reliability Engineering International, 36(3), 988-1004. doi:10.1002/qre.2611

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2019). Warranty cost analysis with an alternating geometric process. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(4), 698-715. doi:10.1177/1748006X18820379

  • Marshall, S., & Archibald, T. (2018). Lot-sizing for a product recovery system with quality-dependent recovery channels. Computers & Industrial Engineering, 123, 134-147. doi:10.1016/j.cie.2018.06.004

  • Archibald, T. W., & Marshall, S. E. (2018). Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty. Environmental Modeling and Assessment, 1-25. doi:10.1007/s10666-018-9628-0

  • Marshall, S., Arnold, R., Chukova, S., & Hayakawa, Y. (2018). Warranty cost analysis: Increasing warranty repair times. Applied Stochastic Models in Business and Industry, 34(4). doi:10.1002/asmb.2323

  • Marshall, S. E., & Chukova, S. (2010). On analysing warranty data from repairable items. Quality and Reliability Engineering International, 26(1), 43-52. doi:10.1002/qre.1032

Book chapters

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2019). Geometric and geometric-like processes and their applications in warranty analysis. In M. Ram, & S. B. Singh (Eds.), Mathematics applied to engineering and management. CRC Press.

Conference contributions

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2019). Geometric and geometric-like processes: An overview and some applications. In 11th International Conference on Mathematical Methods in Reliability (MMR2019). Hong Kong. Retrieved from http://mmr2019.org/public.asp?page=techprog.htm

  • Marshall, S., Arnold, R., Chukova, S., & Hayakawa, Y. (2019). Computation of the mean value function of an alternating geometric process. In 2019 AUT Mathematical Sciences Symposium (pp. 15). Auckland. Retrieved from https://www.aut.ac.nz/

  • Marshall, S., Arnold, R., Chukova, S., & Hayakawa, Y. (2019). Mean value function of an alternating geometric process. In ORSNZ Conference Proceedings (pp. 8). Auckland. Retrieved from http://orsnz.org.nz/Repository/CONF53/abstracts-print.pdf

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2018). Modelling a renewing free repair warranty using an alternating geometric process. In Abstracts Book for the 2018 Joint NZSA/ORSNZ Conference. Palmerston North. Retrieved from https://r-resources.massey.ac.nz/nzsa2018/

  • Marshall, S., Arnold, R., Chukova, S., & Hayakawa, Y. (2018). Modelling a renewing free repair warranty using an alternating geometric process. In AUT Mathematical Sciences Symposium. Auckland: AUT Department of Mathematical Sciences. Retrieved from https://www.aut.ac.nz/

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2018). Warranty Cost Analysis with an Alternating Geometric Process. In 2018 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling 2018 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering. Qingdao.

  • Marshall, S., Arnold, R., Chukova, S., & Hayakawa, Y. (2017). Modelling warranty costs with a generalised geometric alternating renewal
    process (GGAR). In 2017 ORSNZ Annual Conference (with the NZSA / IASC-ARC conference). Auckland. Retrieved from http://orsnz.org.nz/

  • Marshall, S., & Archibald, T. (2017). Lot-sizing for a Product Recovery System with Quality-dependent Recovery Channels. In 2017 AUT Mathematical Sciences Symposium. Auckland. Retrieved from https://www.aut.ac.nz/events/aut-mathematical-sciences-symposium2

  • Marshall, S., Arnold, R., Chukova, S., & Hayakawa, Y. (2015). Modelling warranty costs with a generalised alternating renewal process. In AUT Mathematical Sciences Symposium (pp. 15). Auckland.

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2015). Modelling warranty costs with a generalised alternating renewal process. In 2015 Joint NZSA+ORSNZ Conference. Christchurch. Retrieved from https://secure.orsnz.org.nz/conf49/index.php

  • Marshall, S., Arnold, R., Chukova, S., & Hayakawa, Y. (2015). Modelling Warranty Costs using Geometric Repair Times. In 27th European Conference on Operational Resear. Glasgow. Retrieved from http://www.theorsociety.com/

  • Marshall, S. E., & Archibald, T. W. (2015). Substitution in a hybrid remanufacturing system. In 12th Global Conference on Sustainable Manufacturing. Johor Bahru. Retrieved from http://gcsm.eu/Malaysia/programme.html

  • Marshall, S. E., & Archibald, TW. (2015). Substitution in a hybrid remanufacturing system. In Procedia CIRP Vol. 26 (pp. 583-588). Johor Bahru: Elsevier. doi:10.1016/j.procir.2014.07.073

  • Marshall, S. E. (2014). Modelling rainfall in New Zealand under future climate scenarios. In 2014 AUT Mathematical Sciences Symposium (pp. 16). Auckland. Retrieved from http://www.aut.ac.nz/

  • Marshall, S. (2014). Modelling rainfall in New Zealand under future climate scenarios. In Joint NZSA + ORSNZ Conference (pp. 51). Wellington. Retrieved from https://secure.orsnz.org.nz/conf48/content/2014_abstract_booklet_final.pdf

  • Marshall, S., & Archibald, T. (2013). Managing the quality of returns in a product recovery system with uncertainty. In 26th European Conference on Operational Research: EURO26. Rome. Retrieved from https://www.euro-online.org/media_site/reports/EURO26_AB.pdf#page=312

  • Marshall, S. E., & Archibald, T. W. (2012). The value of substitution in a product recovery system with separate markets. In Operational Research Society (ORS) Annual Conference: OR54 (pp. 123). Edinburgh. Retrieved from http://www.theorsociety.com/

  • Marshall, S. (2010). Managing inventory in a product recovery model. In Operational Research Society (ORS) Annual Conference: OR52. London. Retrieved from http://www.theorsociety.com/

  • Marshall, S. (2008). A product recovery model that uses the quality of returns to determine type of
    recovery. In Proceedings of the 43rd Annual Conference of the Operational Research Society of New Zealand (ORSNZ) (pp. 96-105). Wellington. Retrieved from https://secure.orsnz.org.nz/conf43/content/ORSNZ08_conference_proceedings.pdf

  • Marshall, S. (2006). Farthest insertion heuristics for the freeze-tag problem. In Proceedings of the 41st Annual Conference of the Operational Research Society of New Zealand (pp. 39-48). Christchurch. Retrieved from https://secure.orsnz.org.nz/

Reports

  • Marshall, S. (2016). Analysis of Physiologic Data.

  • Marshall, S., & Hankin, R. (2014). Report to Gravity re TelTag: analysis of cow weight.

Theses

  • Marshall, S. (2012). Refuse or reuse: Managing the quality of returns in product recovery systems. (University of Edinburgh, Edinburgh, United Kingdom). Retrieved from http://hdl.handle.net/1842/6415

  • Marshall, S. (2008). On the analysis of reliability data. (Victoria University of Wellington, Wellington, New Zealand). Retrieved from http://vuw.summon.serialssolutions.com/

Oral presentations

  • Marshall, S. (2015). Warranties: The good, the bad, the ugly. Auckland, New Zealand.

  • Marshall, S., & Archibald, T. (2015). Modelling a product recovery system using Markov Decision Processes. Chapel Hill, North Carolina, United States of America.

  • Marshall, S., & Archibald, T. (2015). Modelling a product recovery system using Markov Decision Processes. Wellington, New Zealand.

Working paper/discussions

  • Arnold, R., Chukova, S., Hayakawa, Y., & Marshall, S. (2018). Warranty Cost Analysis with an Alternating Geometric Process. arXiv.org. Retrieved from https://arxiv.org/abs/1804.06707v1

  • Marshall, S. E., & Archibald, T. W. (2017). Lot-sizing for a product recovery system with quality-dependent recovery channels. Retrieved from http://dx.doi.org/10.2139/ssrn.3080590

  • Welsh, M., Marshall, S., & Noy, I. (2016). Modelling New Zealand milk: From the farm to the factory. School of Economics and Finance, Victoria University of Wellington. Retrieved from http://www.victoria.ac.nz/

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