MS Engineering
Management
Department
Engineering
Level
Graduate
College
College of Computer Sciences & Information Systems
Program Details:
The Master of Science program in Engineering Management program provides students with a strong foundation in engineering and management principles integrated with emerging Artificial Intelligence (AI) technologies to address the evolving needs of modern industries. The program equips students with the knowledge and skills required to enhance efficiency, productivity, quality, and strategic decision-making in technology-driven organizations. It emphasizes the effective planning, organization, allocation of resources, and control of engineering activities while leveraging AI-enabled tools and data-driven approaches.
Students can develop specialized expertise through focused streams in AI for Project Management, AI in Supply Chain and Operations Management, and AI for Quality Engineering and Process Optimization, with opportunities to explore advanced topics such as predictive analytics, smart logistics, digital twins, intelligent automation, and machine learning applications in engineering systems. The program spans a minimum duration of two years, comprising at least four semesters, and requires the successful completion of 32 credit hours. Students must maintain a CGPA of 3.0 for the conferment of the degree.
Program Objectives
- To exemplify excellence in engineering management through in-depth knowledge and skills in the field of engineering management and applied sciences
- To engage in continuous professional development and exhibit a quest for lifelong learning
- To demonstrate professional integrity and commitment to social and ethical responsibilities required of them as leaders and entrepreneurs.
Learning Outcomes
After completion of the program, students will have the following:
- An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, engineering, technical, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
- An ability to plan, organize, allocate resources, and direct and control activities
- An ability to function on multidisciplinary teams.
- An ability to identify, formulate, and solve engineering problems.
- An understanding of professional and ethical responsibility.
- An ability to communicate effectively.
- A broad education is necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context.
- A recognition of the need for and ability to engage in life-long learning
- A knowledge of contemporary issues.
- An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.
Career Path
1. | Engineering Manager | 2. | Quality Engineering Manager |
3. | AI Project Manager | 4. | Process Optimization Specialist |
5. | Operations Manager | 6. | Digital Transformation Consultant |
7. | Supply Chain Analytics Manager | 8. | Technology and Innovation Manager |
Prospective Employers
1. | Manufacturing and Process Industries | 2. | Healthcare and Pharmaceutical Industry |
3. | Technology and Software Companies | 4. | Consulting and Engineering Services Firms |
5. | Supply Chain and Logistics Organizations | 6. | Research and Development Institutions |
7. | Automotive Industry | 8. | Government and Public Sector Organizations |
Eligibility
Sixteen years of education in any engineering \ computing discipline with minimum 55% marks in overall academic career in annual system and CGPA 2.5 in a semester system or equivalent from HEC recognized Institutes/Universities having PEC registration status.
Program Requirements
To fulfill the degree requirements, students must complete eight taught courses along with 6 credit hours of research thesis for MS by Thesis-I and Thesis-II, or 6 credit hours of Independent Research Studies, namely IRS-I and IRS-II, for MS by Independent Research Study, or 6 credit hours through two courses, Elective IV and Elective V, each carrying 3 credit hours, for MS by Coursework. The MS by Coursework option shall be subject to the approval of the departmental committee. For MS Thesis requirement, the students must refer to the MS Policy Manual available at https://basr.iobm.edu.pk/ms-mphil-and-phd-policy-and-thesis/
1. AI for Project Management
Course Code | Core Courses | Credit Hours |
MEM 611 | Project Management | 3+0 |
CSP 511 | Research Methodology | 3+0 |
MEM 581 | AI and Machine Learning for Engineering Managers | 3+0 |
MEM 582 | AI for Project Planning & Scheduling | 3+0 |
MEM 583 | Predictive Analytics for Project Risk and Cost Management | 3+0 |
Course Code | Elective Courses | Credit Hours |
MEM 588 | Generative AI for Project Managers | 3+0 |
MEM 589 | AI in Agile and Lean Project Management | 3+0 |
MEM 681 | Digital Twin Applications in Project Management | 3+0 |
MEM 682 | Big Data Analytics for Projects | 3+0 |
MEM 683 | AI in Project Controls | 3+0 |
MEM 684 | AI and Machine Learning in Decision-Making | 3+0 |
Note: Students must select at least three electives from the above list
2. AI in Supply Chain and Operations Management
Course Code | Core Courses | Credit Hours |
MEM 611 | Project Management | 3+0 |
CSP 511 | Research Methodology | 3+0 |
MEM 581 | AI and Machine Learning for Engineering Managers | 3+0 |
MEM 584 | AI for Demand Forecasting and Inventory Optimization | 3+0 |
MEM 585 | Smart Logistics and Transportation Systems | 3+0 |
Course Code | Elective Courses | Credit Hours |
MEM 685 | AI-Driven Procurement and Supplier Analytics | 3+0 |
MEM 686 | Blockchain and AI for Supply Chain Transparency | 3+0 |
MEM 687 | Resilient and Adaptive Supply Chain Systems | 3+0 |
MEM 688 | Warehouse Automation and Robotics | 3+0 |
MEM 689 | Predictive Maintenance in Operations | 3+0 |
MEM 571 | Intelligent Supply Chain Analytics | 3+0 |
Note: Students must select at least three electives from the above list
3. AI for Quality Engineering and Process Optimization
Course Code | Core Courses | Credit Hours |
MEM 611 | Project Management | 3+0 |
CSP 511 | Research Methodology | 3+0 |
MEM 581 | AI and Machine Learning for Engineering Managers | 3+0 |
MEM 586 | AI for Quality Control and Assurance | 3+0 |
MEM 587 | Machine Learning for Process Optimization | 3+0 |
Course Code | Elective Courses | Credit Hours |
MEM 572 | Computer Vision for Industrial Inspection | 3+0 |
MEM 573 | AI-Driven Six Sigma and Lean Systems | 3+0 |
MEM 574 | Digital Manufacturing and Smart Factories | 3+0 |
MEM 575 | Process Mining and Intelligent Automation | 3+0 |
MEM 576 | Predictive Quality Analytics | 3+0 |
MEM 577 | Statistical Learning for Engineering Systems | 3+0 |
MEM 578 | AI-Based Root Cause Analysis and Reliability Engineering | 3+0 |
Note: Students must select at least three electives from the above list
MEM691 | MS Thesis – I | 3+0 | MEM692 | MS Thesis – II | 3+0 |
MEM693 | Independent Research Study – I | 3+0 | MEM694 | Independent Research Study – II | 3+0 |
Note: Students must choose either the MS Thesis, the Independent Research Study, or two elective courses from the Elective Courses List. If a student opts for the MS Thesis, enrollment in MS Thesis–II is mandatory to maintain continuous registration until the thesis is formally submitted to the Board of Advanced Studies and Research (BASR) for further processing.
Course Structure
Semester One Research Methodology Project Management AI and Machine Learning for Engineering Managers Elective I | Semester Two Core Course I Core Course II Elective II Elective III |
Semester Three | Semester Four |
IRS-1/ Elective IV */ MS Thesis-I Understanding of Holy Quran I ** | IRS – II / and Elective V * / MS Thesis-II Understanding of Holy Quran II ** |
* Subject to the approval of departmental committee
** Muslim students are required to take Understanding of Holy Quran-I (1 Credit hour) and Understanding of the Holy Quran-II (1 Credit hour) and Non-Muslim students are required to take Comparative Religion-I and Comparative Religion-II.