Demand forecasting and decision making under uncertainty for long-term production planning in aviation industry

dc.contributor.advisor Cameron A. MacKenzie
dc.contributor.author Zhang, Minxiang
dc.contributor.department Industrial and Manufacturing Systems Engineering
dc.date 2018-08-11T19:47:42.000
dc.date.accessioned 2020-06-30T03:04:11Z
dc.date.available 2020-06-30T03:04:11Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2001-01-01
dc.date.issued 2017-01-01
dc.description.abstract <p>The aviation industry represents a complex system with low-volume high-value manufacturing, long lead times, large capital investments, and highly variable demand. Making important decisions with intensive capital investments requires accurate forecasting of future demand. However, this can be challenging because of significant variability in future scenarios. The purpose of this research is to develop an approach on making long-term production planning decision with appropriate demand forecasting model and decision-making theory.</p> <p>The first study is focused on demand forecasting. Probabilistic models are evaluated based on the model assumptions and statistics test with historical data. Two forecasting models based on stochastic processes are used to forecast demand for commercial aircraft models. A modified Brownian motion model is developed to account for dependency between observations. Geometric Brownian motion at different starting points is used to accurately account for increasing variation. A comparison of the modified Brownian motion and Autoregressive Integrated Moving Average model is discussed.</p> <p>The second study compared several popular decision-making methods: Expected Utility, Robust Decision Making and Information Gap. The comparison is conducted in the situation of deep uncertainty when probability distributions are difficult to ascertain. The purpose of this comparison is to explore under what circumstances and assumptions each method results in different recommended alternatives and what these results mean making good decisions with significant uncertainty in the long-term future.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/15475/
dc.identifier.articleid 6482
dc.identifier.contextkey 11054876
dc.identifier.doi https://doi.org/10.31274/etd-180810-5093
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/15475
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/29658
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/15475/Zhang_iastate_0097M_16417.pdf|||Fri Jan 14 20:41:31 UTC 2022
dc.subject.disciplines Industrial Engineering
dc.subject.disciplines Operational Research
dc.subject.keywords aviation
dc.subject.keywords Brownian motion
dc.subject.keywords decision-making
dc.subject.keywords decision science
dc.subject.keywords forecasting
dc.subject.keywords uncertainty
dc.title Demand forecasting and decision making under uncertainty for long-term production planning in aviation industry
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
thesis.degree.discipline Industrial and Manufacturing Systems Engineering
thesis.degree.level thesis
thesis.degree.name Master of Science
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