Department of Mechanical and Industrial Engineering

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About Department of Mechanical and Industrial Engineering

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44

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40

Academic Staff

910

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Who works at the Department of Mechanical and Industrial Engineering

Department of Mechanical and Industrial Engineering has more than 40 academic staff members

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Prof.Dr. MOHAMED SALEH GUMA OUN

محمد صالح عون هو احد أعضاء هيئة التدريس بقسم الهندسة الميكانيكية والصناعية بكلية الهندسة. يعمل السيد محمد صالح عون بجامعة طرابلس كـأستاذ منذ مايو 2019 وله العديد من المنشورات العلمية في مجال تخصصه

Publications

Some of publications in Department of Mechanical and Industrial Engineering

System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm

A requirement for new robotic manipulators is the ability to detect and manipulate objects in their environments. Robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain using conventional techniques. Therefore, an efficient technique is required to deal with these types of complex and dynamic systems. Differential Evolution (DE) algorithm is a very powerful optimization technique and has become popular in many fields. Arguably, it is now one of the most predominant stochastic algorithms for real-parameter optimization. However, DE is very sensitive to its control parameters of the mutation operation (F) and crossover operation (CR) in such a way that their fine tuning greatly affect DE performance. Fuzzy Adaptive DE (FADE) algorithm is one of the well known adaptive DE variants that show superiority and reliability in solving different types of optimization
Azeddien Kinsheel, Rawaa Dawoud Al-Dabbagh, Saad Mekhilef, Mohd Sapiyan Baba, Shahaboddin Shamshirband(12-2014)
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A Survey Investigation of Just-in-Time Implementation and its Implications for Management in Four key Industries within Libya

This paper investigates the current status of the implementation level of Just-In-Time (JIT) within the Oil & Gas (OGI), Iron & Steel (ISI), Cement (CI) and Construction (C) Industries within Libya and its implication for management within the said industries. A survey methodology has been applied in this investigation using an intensive questionnaire and one-to-one interviews of the correspondent organizations. Based on the analysis of the survey questionnaire and the one-to-one interview responses, the results show that the management body does not have a clear strategy towards most of the areas that are considered as being crucial in any successful implementation of the JIT techniques. The implementation levels of the JIT techniques are found to be in the modest levels even in the organizations that have indicated themselves as JIT implementers. The research has identified management limitations within the investigated areas and has pointed to areas where the management body needs to take immediate actions in order to achieve an effective and successful JIT implementation within their organizations. This is an important finding for the future success of the Libyan industries and the similar ones. arabic 18 English 107
ٌRajab HOKOMA(1-2016)
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Using Maximum Entropy Principle (MEP) to Assess Wind Energy Potential in Libya. Case Study Dernah

Abstract The aim of this study is to assess the wind energy potential and to compare Weibull and the Maximum Entropy Principle (MEP) distributions, with meteorological measured data. Dernah is selected site, which has good wind characteristics (seasonal, monthly and diurnal wind speed variations and wind direction variations), for possible wind energy applications. The data source is measured at an elevation of 40 m above the ground level for one year period (2003), and it is analyzed statistically. The functions of probability density and power density are calculated using the Weibull and MEP distributions. The Lagrangian multipliers of MEP distribution are estimated numerically at r values of 0 to 5 by using Newton Raphson, Simpson’s rule and Romberg’s methods. The MATLAB simulation is also applied for estimating Lagrangian multipliers. The verification of the results is also assessed by Maple software. The statistical analysis parameters based on wind speed and power density are used as the suitable judgment criterion for the distribution functions. It is found that for MEP distribution, the wind power (W/m2) 450, 395 and 407, are for the cold season, the hot season and for the year 2003, respectively. However, there is no significant difference of the presented peak values of the results in this study for Weibull and MEP distributions. Such result can be attributed to the fact that the average wind speeds were relatively high and the calm spells are about 7% in the year 2003 data.
جبريل يوسف الفيتوري (2010)
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