G. Abdulnour, ON SOME FACTORS AFFECTING THE JUST-IN-TIME PRODUCTION SYSTEM OUTPUT VARIABILITY - A SIMULATION STUDY USING TAGUCHI TECHNIQUES, Computers & industrial engineering, 25(1-4), 1993, pp. 461-464
The main objectives of this research were to analyze the effect of dif
ferent maintenance policies, machines unreliability, and some other fa
ctors on the Just-In-Time (JIT) production system output variability o
r stability. Maintenance policies of type I and II which were introduc
ed by Proshan and Hunter, and maintenance policy III, which was introd
uced by Makabi Hajime et al., were considered in this study and their
effect on the JIT production system were analyzed. In this research, m
athematical predictive and integrative models were developed to demons
trate the effects of different maintenance policies (A), machine unrel
iability (B), ratio of preventive maintenance time to processing time
(D), production line size (C), processing time variability (E) and rat
io of minimal repair time to preventive maintenance time (F) on the pr
oduction line output variability (PLV) in a JIT production system envi
ronment. Functional relationship between the dependent variable PLV an
d die independent variables A, B, C, D, E and F were developed. Using
the Taguchi approach in this experimental design all main factors used
in this experiment were tested at three levels each using on L27 orth
ogonal plan, then all main factors and their first order interactions
were tested using an L32 orthogonal plan of experiment. Discrete-event
simulation, using the GPSS/H simulation language, was employed in ord
er to collect the needed data. The analysis of the data showed that un
der different situations, different maintenance policies do not have t
he same effect on the production line performance. With regard to the
PLV, maintenance policy III led to a higher variation than policy II,
except at the level where the number of machines is less than or equal
to 5. The results of this study also demonstrate that the production
line performance under policy II is more sensitive to the change on th
e ratio of minimal repair time to preventive maintenance time when und
er policy III the same production line performance is more sensitive t
o production line size. Therefore, the results of this study should he
lp the user in choosing a maintenance policy as a function of the prod
uction process parameters in order to decrease production line output
variability and improve productivity and stability.