Forecasting Fluctuating Demand in Manufacturing

这个项目的目标是研究预测产品和服务的“不稳定”需求的方法。不稳定的需求通常为零，但间歇性地非零。标准的预测系统无法应对需求不稳定，这是生产和库存控制中的一个常见问题。该公司对这一问题的关注是对制造业客户的回应。现有的块状需求预测方法要么将块状数据转换为常规数据用于常规处理，要么建立块状需求的参数模型(例如，泊松模型)。目前还没有对这些替代方案进行系统比较。研究人员将对这些替代方案的适当性和准确性进行实证评估。他们还将调查两种创新方法。一个是探索跨系列的关联是否出现在真实数据中，以及如何利用它们。另一种是分析实践中最常用的方法：“销售-力量组合”预测，它是销售人员对每个潜在客户的需求估计的总和。当统计数据稀少时，将销售队伍估计与时间序列技术相结合可能具有特殊的优点，比如需求不稳定。这项研究将导致基于PC的计算机软件的开发，以预测制造业中“不稳定”的需求。

The objective of this project is to investigate methods for forecasting "lumpy" demand for products and services. Lumpy demand is usually zero but intermittently non-zero. Standard forecasting systems cannot cope with lumpy demand, which is a common problem in production and inventory control. The firm's interest in the problem is a response to their customers in manufacturing. Existing approaches to lumpy demand forecasting either convert lumpy data into conventional data for conventional treatment or make parametric models of the lumpy demand (e.g., a Poisson Model). There has not been a systematic comparison of these alternatives. The researchers will empirically assess the appropriateness and accuracy of these alternatives. They will also investigate two innovative approaches. One is to explore whether associations across series occur in real data and how they might be exploited. The other is to analyze the method used most often in practice: "sales-force composite" forecasting, which totals the estimates of demand made by the sales force for each potential customer. Combination of sales force estimates with time-series techniques may have special merit when statistical data are sparse, as with lumpy demand. This research will lead to the development of computer software for PC-based forecasting of "lumpy" demand in manufacturing.