CELDi
UA04 NAVSUP
Performance Evaluation of Intermittent Demand-Forecasting Techniques
in Naval Aviation Maintenance Program of US Navy
Research Objectives
 Comparative evaluation of the reviewed
intermittent demand forecasting
techniques with the forecasting method
employed by US Navy; the measures of
performance being error and system
wide cost
 Study the effect of aggregating review
period while forecasting
 Develop and propose an improved
variant of the discussed forecasting
methods or a new technique.
Phase I
 Scope limited to O-Level
 Multi Indenture Multi Echelon (MIME)
system not considered
 Java implementation of the forecasting
technique to evaluate the errors like ME,
MAD, MSE, RMSE, MPE, and MAPE
 Artificially generated demand as well as
demand history provided by NavSup
Responses: ME, MAD, MSE, RMSE, MPE,
MAPE
Treatments: Various forecasting
techniques
Factors: Aggregation of review period,
Mean demand, Intermittency of demand,
Dependence of demand
Researchers:
Dr. Manuel D. Rossetti
Vijith Varghese
Dr. Heather L. Nachtmann
Dr. Justin R. Chimka
Relevance of the Research
 Difficulty in forecasting the demand of
repairable spare parts with intermittent
demand
 Accuracy of forecast ≡ Availability of
spare parts ≡ Mission Accomplishment
 High cost and long lead times
associated with the repairable spare
parts.
 US Navy recently implemented ERP
project named SMART. Doubts on
compatibility of demand forecasting of
slow moving items in an ERP system
 Recent integration of DRP into the
inventory system of US Navy. Accuracy
of forecast – important factor in DRP
Methodology
 Methodology to be implemented in two
phases:
 Phase 1: Analytically determine the
forecast errors associated with each of
the 5 forecast techniques, based on
which select the forecasting techniques
to be considered in Phase 2
 Phase 2: Simulation model of NAMP
that evaluates system wide cost
associated with each forecast
technique.
Research Scope
 NAMP (Echelons – Organization Level,
Intermediate level and Depot level)
 Repairable spare parts with
intermittent demand
 Forecasting techniques
Traditional methods: Simple
Exponential Smoothing (SES), and
Moving Average (MA)
Croston and variants: Croston
(1972), Syntetos et al. (2001).
Bootstrapping technique: Willemain
et al. (2002)
Phase II
 Model the NAMP in Java Simulation
Library developed by Dr.Rossetti
 Randomly generate
Intermittent demand at the O-Level
and Reparability at each level
 Forecasting technique incorporated
with the model
Forecasts spare parts demand at
each level, Attrition rate at D-Level
 Evaluates system wide cost as well as
forecast associated with each
forecasting techniques.
 Design of Experiment
Responses: ME, MAD, MSE, RMSE,
MPE, MAPE and Cost
Treatments: Various forecasting
techniques
Factors: Forecast period, Mean
demand, Variance of demand, Lead
time and the Number of constituents
in O-Level and I-Level in the multi
echelon system
Project Status
 Thesis proposal was approved by the
committee
 The intermittent demand generator
implemented in Java (Phase 1).
Constant process, Bernoulli process,
two stage Markov chain
Autoregressive process, Moving
Average process, Autoregressive
Moving Average process
 Implementation of forecasting
techniques (Phase 1)
Traditional methods: Simple
Exponential Smoothing (SES), and
Moving Average (MA)
Croston and variants: Croston
(1972), Syntetos et al. (2001).
Bootstrapping technique: Willemain
et al. (2002)
 Implementation of forecast error
evaluator
Intermittent Demand
Forecasting
 SES leads to overstocking Croston(1972)
 MA brings in a higher forecasting error
Venkitachalam(2003)
 Croston(1972) is the pioneering paper in
intermittent demand forecasting
Break down the intermittent demand
series into two constituent series of non
zero demand series and series of time
intervals between non zero demand and
estimates made for both the series
 Syntetos et al. (2001)
Completely eliminates the bias of
exponential smoothing in Croston.
 Willemain et al. (2002)
Whole distribution bootstrapping
approach
Contributions
 Evaluation of forecasting technique in
the perspective of the system wide
costs
 Recommendations as to the most
appropriate technique for spare parts
forecasting with the context of the
NavSup
 Variants to existing models or a new
forecasting technique most suitable for
US Navy supply system
 Intermittent demand generator –
independent demands and dependent
demands