Forecasting in airforce supply chains

Author:

Downing Matthew,Chipulu Maxwell,Ojiako Udechukwu,Kaparis Dinos

Abstract

PurposeThe UK Chinook helicopter is a utility and attack helicopter being operated by the Royal Air Force (RAF). Its versatile nature is of enormous importance to the strategic capability of the RAF's operations. The purpose of this paper is to utilise systems‐based forecasting to conduct an evaluation of inventory and forecasting systems being used to support its maintenance programme.Design/methodology/approachA case study is conducted. Data are collected from existing monthly Component Repair (CRP) data and performance evaluation of software. For propriety reasons, all data have been sanitised.FindingsAnalysis of the current inventory and forecasting system suggests a possible lack of forecasting precision. Current non‐specific formulation of forecasting techniques implied several of the cost driver's demands were being miscalculated. This lack of precision is possibly a result of the smoothing value of 0.01 being too low, especially as the results of statistical modelling suggest that current parameter values of 0.01 might be too low.Originality/valueThe paper reports on work conducted jointly between Boeing and the University of Southampton that sought to create an intermittent demand forecasting model.

Publisher

Emerald

Subject

Transportation,Business and International Management

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A simulation based optimization approach for spare parts forecasting and selective maintenance;Reliability Engineering & System Safety;2017-12

2. Collaborative academic–industry SCM research and knowledge building;International Journal of Logistics Research and Applications;2015-07-24

3. Evaluation of forecasting models for air cargo;The International Journal of Logistics Management;2014-11-04

4. A Data Mining Approach To Improve Military Demand Forecasting1;Journal of Artificial Intelligence and Soft Computing Research;2014-07-01

5. Improving Military Demand Forecasting Using Sequence Rules;Intelligent Information and Database Systems;2014

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