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العنوان
STUDY OF UNPREDICTABLE FAILURES IN
BUS MAINTENANCE WORKSHOPS \
المؤلف
SALEM,SAAD EMAM.
هيئة الاعداد
باحث / سعد امام سالم
مشرف / صلاح الدين ذكى عبد البر
مشرف / ناهد صبحى عبد النور
تاريخ النشر
1995.
عدد الصفحات
239p.;
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة
تاريخ الإجازة
1/1/1995
مكان الإجازة
جامعة عين شمس - كلية الهندسة - التصميم و هندسة الانتاج
الفهرس
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Abstract

Planning of maintenance activities plays a dominant role in determining the effectiveness of the
system. It represents a major task for the planner to try to plan his activities effectively.
Preventive maintenance or planned maintenance and reprur work or unplanned maintenance are two
facets of maintenance activities. Planning the maintenance activities for unpredictable failure
is a complex situation because of the highly randomness involved. Handling such activities needs
an effective and reliable technique. Simulation techniques offer the only tool to plan
maintenance of the unpredictable activities and to aid the planner to effectively use his
resources.
This thesis designs a simulation model that handles the unpredictable maintenance
activities in bus maintenance workshop in order to include the required expected capacity of
the servers for these activities into the plan of work of the workshop. Moreover , the model could
present an aid to planner to simulate his requirements and to test the limits of his system.
The workshop consists of seven main service units. The total number of buses allocated
for the workshop is two hundred and fifty buses. Recorded data. are available for the type and
frequency (giving the interarrivals time) of the failure. The data for the present work is
collected from records for fifty buses representing 20 % sample size. The service time
required for each failure is not recorded. An analytical estimation technique is used
to determine the minimum and maximum expected time for each failure.
A thorough statistical analysis is carried out for the data collected to identify the controlling
variables for theoretical distributions that could, with high level of significance, represent
these data. Four well known distributions are