Abstract
Systems that are simulated are generally made
up of one or more elements that have some uncertainty
associated with them. These systems may eventually evolve in a
manner that is not completely predictable and thus become
stochastic in nature. Simulation of stochastic systems requires
that the variability of the elements in the system be
characterized by probability distributions or concepts. An 'As-
Is-Analysis' of the plant layout and product process flows was
carried out at a furniture manufacturing company. Process
data for four of their main products namely, pallets, baby
tenders bunk beds and standard coffins was collected using a
specially designed data sheet. An analysis of the product flow
times was carried out by grouping the data into four time
variables namely, material movement, processing and waiting
(idle) times before and after processing at the active
workstation. The distributions of these variables were obtained
using graphical methods in which smooth distribution curves
were generated. The gamma distribution with shape
parameters of α= 3 and α=2 characterized the baby tenders
while the product flow times for pallets were characterized by
both the gamma distribution, α=3 and the exponential
distribution with the mean varying between 14.95 and 271.78
seconds. All the data and analysis carried out produced useful
information for input to the design of experiments for
simulation.