الفهرس 
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Abstract
Manufacturing systems modeling and analysis is a critical task in reengineering projects. Discrete-part serial production lines is an important class of manufacturing systems for which modeling and analysis is a complex problem. Serial production lines are dynamic, they exhibit concurrency, synchronization and parallelism. The most common modeling, and analysis tools used for serial production systems design and evaluation are queuing networks (QNs), Markov Chains (MCs), simulation techniques and -recently- Petri nets theory. Serial production lines are classified into ”transfer lines” where transfer of parts is synchronized and ”flow lines” where transfer of parts is not synchronized.
For the past ten years Petri nets theory has been used successfully in modeling and analysis of many automated manufacturing systems. This work contributes to the application of Petri nets theory and methods. in modeling and analysis of manufacturing systems. The contributions concentrate on performance analysis of open flow lines as well as deadlock detection and avoidance in closed flexible flow lines. This is achieved by building and validating open and closed flow line models using ”Colored Petri Nets” (CPN). The developed models are built using a bottom up approach, and validated by comparing their performance results with the results obtained trom exact and approximate models available in the literature.
A single reliable station with exponential processing time and a FIFO buffer module CPN model is developed and validated. This module is used to build and validate a three stations two buffers open flow line. The three stations flow line model is further extended into four, five and six stations flow line models. These models are used for’ simulation based
performance analysis to study the effect of the flow line characteristics on its performance. .
The used performance measure was the flow line capacity. The flow line capacity is derived from the throughput as depicted by the inter-departure times of the last station. -The considered line characteristics are the line length, variability of processing time manifested in the coefficient of variation of the processing time distribution, bottleneck location, total available buffer slots and the buffer allocation profile.
Simulation based performance analysis confirmed that the flow line capacity significantly falls with increased processing time variability and with longer. flow lines in the absence of buffers. Adding buffers significantly improves the performance, but, this improvement is