Date of Graduation
12-2008
Document Type
Thesis
Degree Name
Bachelor of Science in Industrial Engineering
Degree Level
Undergraduate
Department
Industrial Engineering
Advisor/Mentor
Rossetti, Manuel D.
Abstract
The world and life are filled with uncertainty. Statistics, and more specifically, forecasting techniques allow us to quantify uncertainty and make decisions based on that information. Many find forecasting advantageous in areas such as predicting consumer demand, stock prices, terrorist attacks, epidemiology, etc. This thesis will focus on forecasting intermittent demand, which is the study of analyzing sporadic demand. One application includes an airplane manufacturer’s sporadic or intermittent demand for spare parts in their distribution center. Since spare parts are not needed on any regular schedule, it is thought of as intermittent. Knowing the projected quantity for a given time period will allow manufacturers to plan accordingly with suppliers, transportation logisticians, procurement agents and the like. Also, for long lead time items this information is especially helpful to ensure a high service level for the customer. Imagine if a customer orders a specific part and the lead time is ninehundred days, without forecasting the customer will have to wait the entire lead time. By using intermittent demand forecasting techniques, on hand stock levels can be planned to decrease the likelihood that a customer has to wait for the part.
Citation
DeForest, J. (2008). Comparative analysis of forecasting techniques with intermittent demand. Industrial Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/ineguht/11
