الفهرس 
MANUFACTURING SYSTEMS DESIGNOnly 14 pages are availabe for public view
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Abstract
Production line is defined as a mass manufacturing system, which is
characterized by very high production rate and product flow layout. The
problems associated with this type of manufacturing systems are mainly
design and operation problems. There are three major problems in the
area of design and operation of the production line: the balancing
problem, the buffer allocation problem, and the sequencing problem
[1,2,3].
Due to above mentioned problems; efficiency of the production line is
greatly affected by the blocking and starving phenomena that exhibits
due to these problems. This phenomena is mainly caused by variable
processing times and by the disruptions to the line caused by the
unreliability of individual stations.
As the production lines have been In use since the turn of the last
century, a lot of research work has been carried out in the area of the
study and analysis of such systems. In order to find solutions for the
above-mentioned problems and to enhance the system performance,
most of this work has been devoted to the study and analysis of the
system performance [5,6] ..
In order to solve the above-mentioned problems, three main types of
modeling techniques are used. These techniques are: simulation,
artificial intelligence (Fuzzy, Neural Net, Genetic), and mathematical
techniques (queuing theory, Markov processes, PERT diagram, Linear
Algebra) [15,16]Most of research works presented in literature are concentrated on the
evaluation of the performance of short production lines. Mainly, these
research works consider only the evaluation of performance of
production line in steady state conditions [17,18,19,20].
from the above discussions, two main problems should be solved. The
first problem is the analysis of dynamic behavior (transient period) of
production line. The second problem is the modeling of real production
line consisting of more than three stations.
The work presented in this thesis is devoted to the evaluation of
performance of production line in both transient and steady state
conditions. Different measures of the performance of production line are
calculated. Markov processes is a viable methodology that can be used
for evaluation of dynamic behavior and steady state [60,61,62,63,64].
The most important parameter of dynamic behavior (transient state) of a
system is the speed by which this system reaches the steady state. In
order to measure the speed by which the system reaches the steady state,
two methods are applied [65]:
1. Relative method: in which the dynamic behavior of two systems is
compared. The relative method is based on the calculation of the
shrinkage factor (SF) and the second maximum eigenvalue (SME) of
the two systems and compare between them. The system having less
SF and SME has better dynamic behavior than the other system.
2. Absolute method in which the number of products which are run on
the production line until it reachs the steady state is calculated. This