This thesis contains quantitative models to aid managerial decision making in various aspects of manufacturing operations. The first essay deals with the economic design of multivariate statistical quality control charts, which help users respond quickly to sudden changes in the manufacturing...

Prescriptive decision theory requires decision-makers to express their beliefs and tastes with explicit, precise, and complete information. This information, expressed in subjective probability and utility functions, is often difficult and costly to obtain from a decision-maker. It is obvious...

Motivated by a production planning problem in an actual global manufacturing network, we examine the impact of exchange-rate uncertainty ... namely the volatility in and correlations among exchange rates ... on the choice of various optimal production policies and the conditions which lead to...

The most commonly used techniques in statistical process control are parametric, and thus require assumptions regarding the statistical properties of the underlying process. For example, all traditional methods of statistical process control, Shewhart control charts, CUSUM charts, and EWMA...

Traditionally, the quality of a forecasting model is judged by how it compares, in terms of accuracy, to alternative models. However, by providing a relative measure, no indication is given as to how much scope there might be for improvements beyond the benchmark model. When judgemental methods...

A large literature has evolved in the thirty years since the seminal work on combining forecasts. Despite this, when evaluating performance we only look at measures of accuracy and thus ignore most of the rigour of time series analysis. Furthermore, the output from a combination of forecasts is...

Exponential smoothing methods do not involve a formal procedure for identifying the underlying data generating process. The issue is then whether prediction intervals should be estimated by a theoretical approach, with the assumption that the method is optimal in some sense, or by an empirical...

Despite a considerable literature on the combination of forecasts, there is little guidance regarding the assessment of their uncertainty. Since combining methods do not involve a formal procedure for identifying the underlying data generating model, theoretical variance expressions are not...

A novel proposal for combining forecast distributions is to use quantile regression to combine quantile estimates. We consider the usefulness of the resultant linear combining weights. If the quantile estimates are unbiased, then there is strong intuitive appeal for omitting the constant and...