Modelling breakdown durations in simulation models of engine assembly lines

Description/Abstract

Machine failure is often an important source of variability and so it is essential
to model breakdowns in manufacturing simulation models accurately. This thesis
describes the modelling of machine breakdown durations in simulation models of
engine assembly lines. To simplify the inputs to the simulation models for complex
machining and assembly lines, the Arrows classification method has been derived
to group machines with similar distributions of breakdown durations, where
the Two-Sample Cram´er-von Mises statistic and bootstrap resampling are used to
measure the similarity of two sets of data. We use finite mixture distributions fitted
to the breakdown durations data of groups of machines as the input models for
the simulation models. We evaluate the complete modelling methodology that involves
the use of the Arrows classification method and finite mixture distributions,
by analysing the outputs of the simulation models using different input distributions
for describing the machine breakdown durations. Details of the methods and
results of the grouping processes will be presented, and will be demonstrated using
examples.