Graduates of the Bachelor of Science in Industrial and Systems Engineering program will:
Prof. Omar Ghrayeb (Profile)
Subject Proficiency Requirement
Full Admission:Conditional Admission:
Applicants with an average of 70% to 79% in Mathematics, Physics, and Biology or Chemistry will be required to pass a remedial course in the respective subject(s) where the score is below 80%.
Full Admission:
- A minimum score of 80% in the English subject, or its equivalent in other curriculums.
Conditional Admission:
Applicants scoring between 75% and 79% in the English subject will be conditionally admitted, provided they meet one of the following requirements:
1) Pass a remedial English course during the first semester, or
2) Submit an English proficiency test score before the start of the first semester:
- TOEFL: 500 (61 iBT or 173 CBT); or
- IELTS Academic: 5; or
- IESOL: B1; or
- Equivalent scores in other MOE-approved English proficiency tests (subject to evaluation).
Equivalent qualifications from other educational systems are accepted, see Student Handbook for more details.
For further information, please refer to the university admissions policy.
The Bachelor of Science Degree is awarded upon the fulfillment of the following:
Graduates of the Bachelor of Science in Industrial and Systems Engineering program at Ajman University are prepared for a wide range of careers across manufacturing, logistics, healthcare, aviation, consulting, technology, energy, and public-sector organizations. Industrial and Systems Engineers are highly valued for their ability to analyze, design, improve, and optimize complex systems that integrate people, processes, technology, and data.
Career opportunities include:
Graduates may also pursue graduate studies and professional certifications in areas such as industrial engineering, systems engineering, engineering management, operations research, supply chain management, data analytics, and artificial intelligence-driven operations systems.
Graduates of the Bachelor of Science in Industrial and Systems Engineering program at Ajman University are well-positioned for employment across a wide range of strategic sectors in the UAE and GCC region, including:
The multidisciplinary nature of Industrial and Systems Engineering enables graduates to contribute to operational excellence, productivity improvement, digital transformation, sustainability, and data-driven decision-making across diverse industries.
On successful completion of this Program, the graduate will be able to:
PLO (1): Identify, formulate, and solve complex industrial and systems engineering problems using principles of engineering, mathematics, and science.
PLO (2): Apply engineering design to develop systems-based solutions that meet specified needs while considering technical, economic, environmental, societal, and organizational constraints.
PLO (3): Communicate effectively with diverse audiences using oral, written, and graphical methods.
PLO (4): Recognize ethical and professional responsibilities and make informed decisions considering societal, environmental, and organizational impacts.
PLO (5): Function effectively as members and leaders of multidisciplinary teams, demonstrating leadership, collaboration, and accountability.
PLO (6): Develop and conduct experiments, analyze and interpret data, and use engineering judgment to draw valid conclusions for system improvement.
PLO (7): Engage in lifelong learning by acquiring and applying new knowledge to adapt to evolving technologies, industry trends, and emerging engineering practices.
The Bachelor’s degree in Industrial and Systems Engineering (ISE) requires the completion of 130 Cr. Hrs., classified as follows:
|
Course Type |
Credit Hours |
|
University Required Courses |
18 |
|
University Elective Courses |
12 |
|
College Required Courses |
10 |
|
Math and Science |
26 |
|
Specialization Required Courses |
42 |
|
Graduation Project Courses |
6 |
|
Specialization Elective Courses |
12 |
|
Training Courses |
4 |
|
Total Credit Hours |
130 |
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
EMS112 |
Emirates Studies |
3 |
0 |
0 |
3 |
- |
|
ENG113 |
Advanced English Writing |
3 |
0 |
0 |
3 |
- |
|
ENG211 |
Public Speaking |
3 |
0 |
0 |
3 |
- |
|
THI211 |
Critical Thinking and Quantitative Reasoning |
3 |
0 |
0 |
3 |
- |
|
INN311 |
Innovation & Sustainable Entrepreneurship |
3 |
0 |
0 |
3 |
- |
|
AIT111 |
Artificial Intelligence |
3 |
0 |
0 |
3 |
- |
The student must take the first three courses and select one elective.
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
CHM111 |
General Chemistry |
2 |
2 |
0 |
3 |
- |
|
ENV113 |
Science of Energy |
3 |
0 |
0 |
3 |
- |
|
DAT100 |
Introduction to Data Analytics |
3 |
0 |
0 |
3 |
- |
|
XXX### |
Elective |
3 |
0 |
0 |
3 |
- |
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
MEC101 |
Introduction to Engineering |
1 |
0 |
0 |
1 |
- |
|
MEC103 |
Engineering Drawing and Mechanical Workshop |
2 |
0 |
0 |
3 |
- |
|
MEC105 |
Computer Programming |
3 |
0 |
2 |
3 |
- |
|
MEC201 |
Fundamental of Electrical Engineering |
3 |
0 |
0 |
3 |
- |
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
MTH141 |
Calculus I |
3 |
0 |
2 |
3 |
- |
|
MTH142 |
Calculus II |
3 |
0 |
2 |
3 |
MTH141 |
|
MTH241 |
Diff. Eq. and Linear Algebra |
3 |
0 |
0 |
3 |
MTH142 |
|
MTH242 |
Calculus III |
3 |
0 |
2 |
3 |
MTH241 |
|
ISE350 |
Probability and Statistics for Engineers |
3 |
0 |
0 |
3 |
MTH142 |
|
ISE420 |
Design of Experiments for Engineers |
3 |
0 |
0 |
3 |
ISE350 |
|
PHY121 |
Engineering Physics I |
3 |
2 |
2 |
4 |
- |
|
PHY122 |
Engineering Physics II |
3 |
2 |
2 |
4 |
PHY121 |
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
ISE220 |
Engineering Economy |
3 |
0 |
0 |
3 |
MTH141 |
|
ISE210 |
Introduction to Lean Systems Engineering |
3 |
0 |
0 |
3 |
- |
|
ISE310 |
Work Measurement and Work Design |
2 |
2 |
0 |
3 |
ISE350 |
|
ISE320 |
Principles of Manufacturing Processes |
3 |
0 |
0 |
3 |
- |
|
ISE370 |
Operations Research: Deterministic Models |
3 |
0 |
0 |
3 |
MTH241 |
|
ISE371 |
Operations Research: Probabilistic Models |
3 |
0 |
0 |
3 |
ISE350, ISE370 |
|
INT302 |
Database Management System |
3 |
0 |
0 |
3 |
- |
|
ISE410 |
Human Factors |
2 |
2 |
0 |
3 |
ISE310, PHY121 |
|
ISE430 |
Quality Control |
3 |
0 |
0 |
3 |
ISE210, ISE320 |
|
ISE440 |
Production Planning and Control |
3 |
0 |
0 |
3 |
ISE371 |
|
ISE460 |
Facilities Planning and Design |
3 |
0 |
0 |
3 |
ISE320, ISE370 |
|
ISE480 |
Simulation Modeling and Analysis |
2 |
2 |
0 |
3 |
ISE370 |
|
ISE450 |
Six Sigma & Process Improvement |
3 |
0 |
0 |
3 |
ISE371 |
|
ISE470 |
Analysis and Design of Supply Chain Systems |
3 |
0 |
0 |
3 |
ISE371, ISE370 |
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
ISE491 |
Graduation Project I |
3 |
0 |
0 |
3 |
ISE420 |
|
ISE492 |
Graduation Project II |
3 |
0 |
0 |
3 |
ISE491 |
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
ISE415 |
Service Operations Management |
3 |
0 |
0 |
3 |
- |
|
ISE420 |
Project Management for Engineers |
3 |
0 |
0 |
3 |
- |
|
INT323 |
Big Data Technology and Analytics |
3 |
0 |
0 |
3 |
- |
|
ISE431 |
Reliability Engineering |
3 |
0 |
0 |
3 |
- |
|
ISE475 |
Decision Analysis for Engineering |
3 |
0 |
0 |
3 |
- |
|
ISE472 |
Queueing Methods for Services and Manufacturing |
3 |
0 |
0 |
3 |
- |
|
ISE474 |
Scheduling and Logistics |
3 |
0 |
0 |
3 |
- |
|
ISE444 |
Safety Engineering Management |
3 |
0 |
0 |
3 |
- |
|
ISE411 |
Management for Engineers |
3 |
0 |
0 |
3 |
- |
|
ISE404 |
Directed Studies |
3 |
0 |
0 |
3 |
- |
|
Course No. |
Course Title |
Th. |
Lab. |
Tut. |
Cr. Hrs. |
Prerequisite |
|
ISE490 |
Engineering Training |
- |
- |
- |
4 |
- |
This course introduces methods for evaluating the economic feasibility and net worth of engineering and business ventures. Topics include time value of money, cash flow analysis, comparison of alternatives, depreciation and income tax considerations, break-even analysis, sensitivity analysis, and economic evaluation of public sector projects. Emphasis is placed on applying economic decision-making techniques to engineering and industrial systems.
Pre-requisite: MTH141.
Introduction to various lean concepts and lean tools at the basic level. Topics include lean principles, kaizen, wastes identification, flow charting, capacity analysis, productivity analysis, value stream mapping, workplace organization and standardization, visual control/management, plant layout, and line balance.
Pre-requisite: ---.
Techniques for improving and designing better methods; procedures for measuring work and developing time standards in production and service activities. Study of work center design and methods for improving human work.
Pre-requisite: ISE350.
Introduction to basic manufacturing processes such as casting, powder metallurgy, bulk deformation, sheet metal forming, metal cutting, and joining. Integration of manufacturing processes and the effect of design and materials on manufacturing processes.
Pre-requisite: ---.
This course introduces fundamental concepts of probability and statistics with emphasis on engineering applications and decision-making under uncertainty. Topics include sampling and descriptive statistics, random variables, discrete and continuous probability distributions, fitting data to distributions, confidence intervals, hypothesis testing using parametric and nonparametric methods, correlation, simple regression, and analysis of variance. Emphasis is placed on data analysis and the application of statistical methods to engineering and industrial systems problems.
Pre-requisite: MTH142.
This course introduces fundamental operations research techniques for solving engineering and managerial decision-making problems under deterministic conditions. Topics include mathematical modeling, linear programming, simplex method, duality, transportation and assignment models, network optimization, integer programming, and dynamic programming.
Pre-requisite: MTH241.
This course introduces elementary probabilistic models used in operations research for decision-making under uncertainty. Topics include reliability of simple systems, probabilistic decision models, applications of Markov chains, Poisson processes, and queuing systems. Emphasis is placed on modeling and analyzing real-world problems in engineering, manufacturing, logistics, and service systems.
Pre-requisite: ISE350, ISE370.
This course is designed to give a theoretical and practical background in database techniques. It covers database concepts, data models, data dictionary, entity-relationship (ER) and enhanced entity relationship (EER) diagrams, and the relational data model, converting an E-R model to a relational model, Structured Query Language (SQL), normalization, and physical database design. Oracle software is used in the Lab.
Pre-requisite: ---.
This course introduces the principles of human factors engineering and ergonomics in the design of systems, products, and work environments. Topics include human capabilities and limitations, workplace design, cognitive and physical ergonomics, human-machine interaction, safety, work measurement, environmental factors, and ergonomic risk assessment. Emphasis is placed on improving productivity, safety, comfort, and overall system performance through human-centered design principles.
Pre-requisite: ISE310, PHY121.
This course introduces statistical techniques for designing and analyzing relationships among variables in engineering processes. Topics include engineering applications of analysis of variance (ANOVA), single- and multi-factor experiments, factorial and fractional factorial designs, regression models, response surface methods, and experimental optimization. Emphasis is placed on planning, conducting, analyzing, and interpreting experiments to improve process performance, product quality, and engineering decision-making.
Pre-requisite: ISE350.
This course introduces the principles and techniques of quality control in manufacturing and service systems. Topics include statistical quality control, control charts, process capability analysis, acceptance sampling, quality improvement tools, and continuous improvement methodologies. Emphasis is placed on monitoring, analyzing, and improving process quality to enhance productivity, reliability, and customer satisfaction.
Pre-requisite: ISE210, ISE320.
This course covers the analysis, design, and management of production systems. Topics include productivity measurement, forecasting techniques, project planning, line balancing, inventory systems, aggregate planning, master scheduling, material requirements planning (MRP), operations scheduling, capacity planning, and shop floor control. Modern approaches to production management, including just-in-time (JIT) production and continuous improvement practices, are also introduced. Emphasis is placed on improving productivity, operational efficiency, and resource utilization in manufacturing and service systems.
Pre-requisite: ISE371.
This course covers the principles and practices of facilities planning and design for manufacturing and service systems. Topics include analytical approaches to site location, facility layout, material handling equipment, storage systems, workspace design, flow analysis, and warehouse planning. Systematic planning procedures and computer-aided techniques for facility analysis and optimization are also introduced. Emphasis is placed on improving productivity, safety, efficiency, and effective utilization of space, equipment, and resources.
Pre-requisite: ISE320, ISE370.
This course covers the design and analysis of industrial and operational systems using computer simulation models. Topics include discrete-event simulation, choice of input distributions, generation of random variates, design and construction of simulation models and experiments, model verification and validation, and interpretation of generated output. Emphasis is placed on analyzing system performance and supporting decision-making in manufacturing, logistics, healthcare, and service systems using simulation software tools.
Pre-requisite: ISE370.
This course introduces the principles and methodologies of Six Sigma and continuous process improvement in manufacturing and service systems. Topics include DMAIC methodology, process mapping, statistical process control, root cause analysis, quality improvement tools, lean principles, process capability analysis, and performance measurement. Emphasis is placed on reducing variability, eliminating waste, improving quality, and enhancing operational efficiency through data-driven decision-making and continuous improvement practices.
Pre-requisite: ISE371.
This course introduces the analysis, design, and management of supply chain systems in manufacturing and service environments. Topics include supply chain strategy, demand forecasting, inventory management, logistics, transportation, distribution systems, procurement, network design, and supply chain coordination. Emphasis is placed on improving efficiency, responsiveness, sustainability, and integration across supply chain operations using analytical and decision-making tools.
Pre-requisite: ISE371, ISE370.
This course introduces the principles and practices of managing operations in service organizations. Topics include service design, capacity and demand management, process analysis, quality management, waiting line systems, service productivity, customer satisfaction, and performance improvement. Emphasis is placed on analyzing and improving service processes to enhance efficiency, quality, and customer experience in healthcare, banking, hospitality, logistics, and other service industries.
Pre-requisite: ---.
This course presents an integrated approach to the management of engineering and high-technology projects throughout the entire project life cycle, including project initiation, organization, planning, implementation, control, and termination. Topics include project evaluation, scheduling, resource allocation, cost control, contract selection, risk management, quality management, and human resource management. Emphasis is placed on the use of quantitative methods and project management tools to successfully manage engineering projects within scope, time, cost, and quality constraints.
Pre-requisite: ---.
The aim of the course is to introduce students to the techniques, tools, and technologies used for big data analytics using appropriate programming language. Topics covered in this course include: statistical evaluation of data, clustering techniques, linear regression, logistic regression, classification methods, MapReduce, Apache Hadoop, Pig, Hive, Hbase, and NoSQL.
Pre-requisite: ---.
This course covers reliability analysis for the design, implementation, and operation of engineering systems, processes, and products. Topics include probability models for reliability, fault tree analysis, lifetime and failure distributions, life testing, reliability prediction, availability, maintainability, preventive maintenance, and system reliability analysis. Emphasis is placed on improving system performance, reducing failures, and enhancing operational effectiveness through analytical and quantitative reliability methods.
Pre-requisite: ---.
This course introduces quantitative methods and analytical techniques for engineering decision-making under certainty, risk, and uncertainty. Topics include elementary decision-making methods when random factors are present, decision trees, expected utility analysis, influence diagrams, value of information, sensitivity analysis, and multi-criteria decision-making. Emphasis is placed on evaluating alternatives and supporting effective decision-making in engineering and industrial systems using analytical and probabilistic models.
Pre-requisite: ---.
This course introduces the principles and analytical methods of queueing theory for manufacturing and service systems. Topics include stochastic processes, waiting line models, Poisson arrivals, service time distributions, single- and multi-server systems, queueing networks, system performance measures, and applications in production, logistics, healthcare, telecommunications, and service operations. Emphasis is placed on analyzing congestion, improving resource utilization, and optimizing system performance under uncertainty.
Pre-requisite: ---.
This course covers applied operations research methods with a focus on scheduling and logistics systems in manufacturing and service environments. Topics include single- and multiple-stage scheduling problems, workforce scheduling, vehicle routing and scheduling, bin packing problems, transportation and distribution systems, and supply chain concepts. Modern optimization tools, heuristics, and solution implementation issues are also introduced. Emphasis is placed on improving operational efficiency, resource utilization, and logistics system performance.
Pre-requisite: ---.
This course introduces the principles and practices of safety engineering and management in industrial and engineering environments. Topics include hazard identification, risk assessment, accident prevention, safety regulations and standards, occupational health, safety management systems, human factors, incident investigation, and safety performance evaluation. Emphasis is placed on developing safe work environments, minimizing operational risks, and promoting a culture of safety in manufacturing, construction, and service industries.
Pre-requisite: ---.
This course introduces the fundamental principles of systems engineering and their applications to the development and management of complex engineering systems. Topics include systems thinking, systems definition, requirements analysis, system design and implementation, system life-cycle management, project integration, risk management, configuration management, and performance evaluation. The course also presents modeling and optimization tools used for system architecture evaluation and decision-making. Emphasis is placed on coordinating technical, organizational, and managerial aspects of engineering systems throughout the system life cycle.
Pre-requisite: ---.
This course provides students with the opportunity to pursue supervised independent study or advanced investigation in a specialized area of industrial and systems engineering. Topics are selected in consultation with a faculty member. Emphasis is placed on independent learning, critical thinking, technical communication, and application of industrial engineering principles to emerging or specialized topics.
Pre-requisite: ---.
Pre-requisite: ---.
This course introduces the fundamental approaches to the design of industrial and systems engineering solutions for complex real-world problems. Emphasis is placed on the application of industrial engineering techniques to problem definition, analysis, system design, synthesis, and evaluation. Topics include project proposal development, solution implementation, technical reporting, presentation skills, teamwork, and ethical considerations. Students work in teams under faculty supervision on projects proposed by industrial, service, or governmental organizations, or on emerging research and innovation challenges.
Pre-requisite: ISE420.
This is the second stage of the graduation project, which includes the practical aspects: design, implementation, and testing of the project speciļ¬cation developed in Graduation project I. Team members are evaluated by the project supervisor and a committee in the midterm in week 6 of the term and at the end of the term. Team members are required to meet weekly with the supervisor.
Pre-requisite: ISE491.