الفهرس 
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Abstract
A queueing oriented decision process for capacity planning was discussed
In this thesis to show how queueing systems models can be applied in capacity
planning to reduce the waiting time for all work orders (demand) and as a
result, reduce the cost. This was clone using a mathematical model for capacity
planning in a job-shop environment under the constraints of the total production
cost and through a given time period. This leads to savings in the capacity, and
thus reduction in the total production cost.
This subject was discussed through the following:
I. Using known mathematical models for queueing systems to obtain the
waiting time for every product separately and design the necessary
production capacity to achieve these products within limited time period.
Different service policies were used in every case separately.
The mathematical model is composed of:
a) Objective function: the total production cost (setting - production-
storage - fixed - ... - etc).
b) Decision variables: the production batch size, the inventory level, and
the number of setting times.
c) Constraints: the production capacity.
2. Development of a mathematical model In case of multi-server senes
queues where the product is produced in more than one step. This is done
for di fferent number of production batch sizes.
3. Design of a software program and using this program to solve the
mathematical models and to get the results of the queueing systems model4. Development of the mathematical model of the single-server that is
suitable for the more complex and the most probable case to occur, the
production planning of different products produced in more than one stage.
5. Development of the single-server (machine) solution and using it as a tool
for solving the multi-product produced in different stages.
6. An experimental test has been performed with loading some products to
get the production planning charts, tables, the total production cost and the
net revenue in every case. The produced units with the net revenue curves
are plotted separately in every case and compared with the results obtained
from the mathematical models.
7. Analysis of the obtained results for capacity planning usmg the
mathematical models.
8. Comparison of the production cost of some products that are planned to be
produced separately.
The following results are obtained:
1. Capacity planning reduces the time and setting costs, and as a result,
gives better production planning.
2. Capacity planning reduces the setting time and production cost, and as
a result, results in saving in the production capacity.
3. Capacity planning leads to insuring that the required plan can be
achieved in the right time with the minimum cost.
4. Capacity planning leads to tile optimum use of the available capacity
and avoids the unnecessary capacity (excess capacity) leading to savings
in the total production cost and, as a result, increasing the net revenue
and the market standing with the minimum cost of product.
5. Efficiency of the model, with its savings in time and cost as compared
with the other conventional solution methods used for solving such
models