Graduate Programs - Industrial Engineering
2018-19 academic year MSc program
Degrees and Tracks
The Department offers three types of M.Sc. degrees:
1. Academic M.Sc. in Industrial Engineering
Requirements for this degree include:
Research Track
- Completing courses for a minimum total of 24 credit points in accordance with the curriculum
- Writing a final thesis for a total of 12 credit points, in compliance with the Faculty's Regulations for Advanced Degrees (Total of 36 credit points)
- Participation in a minimum of 14 departmental seminars
Final Project Track
- Completing courses for a minimum total of 36 credit points in accordance with the curriculum
- A project for 3 credit points (Total of 39 credit points)
- Participation in a minimum of 8 departmental seminars
2. Academic M.Sc. in Industrial Engineering & Management
Requirements for this degree include:
Research Track
- Completing courses for 27 credit points, including 18 credits in Engineering and 9 credits in Management, in accordance with the curriculum
- Writing a final thesis for a total of 12 credit points, in compliance with the Faculty's Regulations for Advanced Degrees (Total of 39 credit points)
- Participation in a minimum of 14 departmental seminars
Final Project Track
- Completing courses for a minimum total of 38 credit points, including 26 credits in Engineering and 12 credits in Management in accordance with the curriculum
- A project for 3 credit points (Total of 41 credit points)
- Participation in a minimum of 8 departmental seminars
3. Combined academic degree: MSc in Industrial Engineering & MBA from the School of Management
Requirements for MSc in Industrial Engineering
- Completing courses for a minimum total of 18 credit points from the Industrial Engineering M.Sc. program. For exemption from 6 credit points in the Management Cluster students must complete the combined degree. Students who do not meet the full requirements in both programs will be required to take more courses, as needed to receive a M.Sc. degree in Industrial Engineering or Industrial Engineering & Management, as specified above.
- Writing a final thesis for a total of 12 credit points, in compliance with the Faculty's Regulations for Advanced Degrees
- Participation in a minimum of 14 departmental seminars
Requirements for MBA
The MBA program includes courses for 22 credit points, in accordance with the MBA curriculum. For exemption from 3 courses (6 credit points), students must complete both programs in the combined degree.
Stages of the study program:
(See Paragraph 3.4 of the M.Sc. Regulations of the Faculty of Engineering)
- In general, M.Sc. studies at the Faculty of Engineering comprise of two stages: First - Accumulative Studies, and second – Regular (Full) Studies. The Accumulative Stage, designed for students who work while they study, must be completed within a maximum of three academic years, during which students must take all mandatory departmental courses, and accumulate a minimum of 12 and a maximum of 18 credit points. Students completing the Accumulative Studies are recognized as Regular Students – in either the Research of Final Project Tracks. To be admitted to the Research Track, a student must have a permanent supervisor guiding his research for the thesis. It must be emphasized that admission to Accumulative Studies is considered admission to the MSc program in every respect.
- Students studying on scholarships attend the Fulltime program. They are admitted directly to Regular Studies, only in the Research Track. They must choose a permanent supervisor no later than the end of their first semester of studies.
- Students opting for the Industrial Engineering & Management program must inform the Department during the first semester of Accumulative Studies.
- M.Sc. candidates requiring supplementary studies are admitted to a supplementary program.
For a detailed description of study stages, conditions for continuing on to the next year, requirements at each stage and conditions for advancement to the Regular Studies stage, please see the M.Sc. Regulations.
Specializations
The Department offers three areas of specialization, reflecting the current interests, courses and knowledge of its faculty members:
- Operations & Logistics
- Business Analytics
- Human Aspects of Systems
The curriculum allows but does not require specialization. To specialize, a student must take courses in accordance with the relevant requirements and write a thesis or final project in the field of specialization.
Prerequisites
The relevant registration and admission requirements (in addition to general TAU requirements) are published annually in the Registration Center's Guide for Candidates.
- For the Industrial Engineering M.Sc. program – to apply for admission a candidate must meet all requirements specified in the Registration Guide, as well as:
- B.Sc. in Engineering or the Exact Sciences from an institution of higher education recognized by the Council for Higher Education
- Minimum weighted average grade of 80 in undergraduate studies
- Admission to the combined M.Sc. & MBA program depends on openings in the program. Prerequisites include: Fulltime status, Completion of the B.Sc. in Industrial Engineering & Management in the top 20% of the class, minimum average grade of 90, meeting the admissions requirements of the School of Management, based on the average grades and GMAT results.
- The minimum required for admission -varies from one year to another, and depends on the level of candidates and the Department's capacity in that particular year. Admission depends on the candidate's knowledge base, background of undergraduate studies, average grade in the B.Sc. studies, and the relative placement in the undergraduate class. Candidates must submit their grade records and documentation of their undergraduate placement.
- A candidate whose grade average is lower than the required minimum but not lower than 75, may, in exceptional cases, be admitted to the MSc program in a provisional status, depending on the Department's capacity in that particular year, and for a maximum period of one year. Students in this status must complete the Department's two mandatory courses with a minimum average of 70.
- Based on the criteria of knowledge base and undergraduate background, some candidates will be required to complete several undergraduate courses. Admission will be in a special status – supplementary studies.
- The supplementary program will be determined by the Head of the Departmental Committee for M.Sc. Studies, based on the candidate's knowledge base and undergraduate background. For more information please see the M.Sc. Regulations.
- Prerequisites for continuing to M.Sc. studies: completing each course with a grade of 75, and all courses with an average grade of 80. In addition, the students must meet any other requirements set by the Faculty.
Course categories
- Mandatory courses
- Core courses
- Elective courses
- Elective Management courses
Requirements according to Study Tracks:
Research Track
|
|
Industrial Engineering |
Industrial Engineering & Management |
Combined with MBA |
|---|---|---|---|
|
Mandatory |
6 |
6 |
6 |
|
Core |
10 |
10 |
10 |
|
All Cores & Electives |
4-8 |
2 |
2 |
|
Management |
0-4 |
9 |
- |
|
Total for degree |
24 |
27 |
18 |
For specializations students must choose core courses of the elected specialization and write a thesis in the relevant field.
Final Project Track
|
|
Industrial Engineering |
Industrial Engineering & Management |
|---|---|---|
|
Mandatory |
6 |
6 |
|
Core |
12 |
12 |
|
All Cores & Electives |
12-18 |
8 |
|
Management |
0-6 |
12 |
|
Total for degree |
36 |
38 |
For specializations students must choose core courses of the elected specialization and conduct a final project in the relevant field.
Courses in the Program:
Mandatory courses
M.Sc. students in all tracks must take the following mandatory courses during their first year of studies:
|
Course No. |
Course name |
Credit points |
Hours |
Prerequisites |
|---|---|---|---|---|
|
Applied Optimization for Engineers |
3 |
3 |
Deterministic Models of Operations Research |
|
|
Stochastic Methods for Industrial Engineering |
3 |
3 |
Stochastic Models of Operations Research |
Core courses for Operations & Logistics specialization (not all courses are given every year)
|
Course No. |
Course name |
Credit points |
Hours |
Prerequisites |
|---|---|---|---|---|
|
Service Systems |
2 |
3 |
Analysis of Production Systems; Stochastic Models of Operations Research; Deterministic Models of Operations Research |
|
|
Dynamic Systems |
2 |
2 |
|
|
|
Design of Production Lines |
2 |
2 |
Analysis of Production Systems |
|
|
Combinatorial Optimization from Theory to Practice |
2 |
2 |
Applied Optimization for Engineers |
|
|
Operations Scheduling |
2 |
2 |
Analysis of Production Systems |
|
|
Supply Chain Management |
2 |
2 |
Analysis of Inventory Systems |
|
|
Management of Distribution Systems |
2 |
2 |
Applied Optimization for Engineers |
|
|
Operation of Transportation Systems |
2 |
2 |
Applied Optimization for Engineers |
|
|
Game Models in Operation Systems |
2 |
2 |
Introduction to Probability |
Core courses for Business Analytics specialization (not all courses are given every year)
|
Course No. |
Course name |
Credit points |
Hours |
Prerequisites |
|---|---|---|---|---|
|
Statistical Learning |
3 |
3 |
Probability; Statistics |
|
|
Statistical Machine Learning |
3 |
3 |
Random signals and Noise |
|
|
Applications of Information Theory to Search Problems |
2 |
2 |
Probability; Statistics |
|
|
Applications of Anomaly Detection in Service and Industrial Systems |
2 |
2 |
|
|
|
Data Privacy |
2 |
2 |
Introduction to Probability; Communication Networks |
|
|
Data Visualization |
2 |
2 |
|
|
|
Big Data Technologies and Databases 3 |
2 |
2 |
Programming; Statistical Analysis of Data; Introduction to Information Systems; Data Warehousing |
|
|
Introduction to Data Science 3 |
2 |
2 |
Design of Database Systems; Data Warehousing |
|
|
Curiosity: Models and Applications |
2 |
2 |
Optimization and Meta-Heuristics |
|
|
Advanced Data Mining for Structured and Unstructured Data |
2 |
2 |
Design of Database Systems; Deterministic and Stochastic Models |
|
|
Information Retrieval and Recommender Systems 1 |
2 |
3 |
Programming; Linear Algebra; Optimization and Meta-Heuristics; Data Structures |
|
|
Information Security 1 |
2 |
3 |
Linear Algebra; Analysis and Design of Information Systems |
Core courses for the Humans Aspects of Systems specialization (not all courses are given every year)
|
Course No. |
Course name |
Credit points |
Hours |
Prerequisites |
|---|---|---|---|---|
|
Service Systems 1 |
2 |
3 |
Analysis of Production Systems; Stochastic Models of Operations Research; Deterministic Models of Operations Research |
|
|
Quantitative Models of Human Performance 1,2 |
2 |
3 |
Statistics |
|
|
Human-Computer Interface Design and Evaluation 1 |
2 |
3 |
Cognitive Aspects in Human Factors Engineering; Analysis and Design of Information Systems |
|
|
Research Methods in Human-Computer Interaction |
2 |
2 |
|
|
|
Data Privacy |
2 |
2 |
Introduction to Probability; Communication Networks |
|
|
Data Visualization |
2 |
2 |
|
|
|
Interaction with Autonomous Systems |
2 |
2 |
Statistics; Stochastic Methods of Operations Research; Cognitive Aspects in Human Factors Engineering |
|
|
Decision Making Under Uncertainty |
2 |
2 |
|
|
|
Game Models in Operation Systems |
2 |
2 |
Introduction to Probability |
|
|
Human-Robot Interaction |
2 |
2 |
|
Elective Courses (not all courses are given every year)
|
Course No. |
Course name |
Credit points |
Hours |
Prerequisites |
|---|---|---|---|---|
|
Design of Experiments and Analysis of Variance 1 |
3 |
4 |
Statistical Data Analysis
|
|
|
Regression Analysis 1 |
2 |
3 |
Statistics |
|
|
Statistics for the Big Data |
3 |
3 |
|
|
|
Flows in Networks |
3 |
3 |
Deterministic Models of Operations Research; Linear Algebra |
|
|
Approximate Algorithms in Combinatorial Optimization |
3 |
3 |
|
|
|
Queuing Theory |
3 |
3 |
Stochastic Methods for Industrial Engineers |
|
|
Information Theory |
3 |
3 |
Random Signals and Noise |
|
|
Scientific Writing in English |
None |
|
|
|
|
Computational Learning Theory |
2 |
2 |
Data Structures and Algorithms; Introduction to Probability and Statistics |
|
|
Multi-Objective Optimization |
3 |
3 |
|
|
|
Thinking and Creativity: Cognitive Systems for engineers |
2 |
2 |
|
|
|
Selected Topics in Industrial Engineering: the Mathematics of Mind |
2 |
2 |
|
|
|
Selected Topics in Industrial Engineering: Identifying Redundancy of Constraints |
2 |
2 |
|
|
|
Selected Topics in Industrial Engineering: Group Testing |
2 |
2 |
|
|
Course No. |
Course name |
Credit points |
Hours |
Prerequisites |
|---|---|---|---|---|
|
Principles of Strategy |
1.5 |
1 |
- |
|
|
Business Ethics |
1.5 |
1 |
- |
|
|
Strategic Thinking 1 |
1.5 |
1 |
- |
|
|
The Capital Market in Israel |
1.5 |
1 |
Investment Theory and Security Analysis |
|
|
Banking Management |
1.5 |
1 |
Introduction to Finance and Engineering Economics |
|
|
Financial Management |
3 |
2 |
Introduction to Finance and Engineering Economics; Industrial and Cost Accounting |
|
|
Investment Theory and Security Analysis |
3 |
2 |
Introduction to Finance and Engineering Economics |
|
|
Options and Futures |
1.5 |
1 |
Investment Theory and Security Analysis |
|
|
Behavioral Finance |
1.5 |
1 |
Principles of Finance |
|
|
Methods of Research in Markets and Organizations |
1.5 |
1 |
Introduction to Marketing; Stochastic Models in Operations Research |
|
|
Consumer Insights and Strategic Marketing |
3 |
2 |
Marketing Management |
|
|
Industrial Marketing (B2B) |
1.5 |
1 |
Marketing Management |
|
|
Strategic Management |
1.5 |
1 |
Principles of Strategy |
|
|
Industry Analysis |
1.5 |
1 |
Principles of Strategy |
|
|
Measuring Eco-Efficiency in Business Context |
1.5 |
1 |
- |
|
|
Development and Use of Patents as a Strategic Business Tool |
1.5 |
1 |
- |
|
|
Information Systems and Business Strategy |
1.5 |
1 |
Principles of Information Systems |
|
|
|
Information in Decision-Making Processes |
1.5 |
1 |
Economics for Industrial Engineers |
|
Managing the Information Resource |
1.5 |
1 |
Principles of Information Systems; Economics for Industrial Engineers |
|
|
Knowledge Data Discovery and Neural Networks |
1.5 |
1 |
Statistics |
|
|
Risk Management and New Business Models in the Cyber World |
1.5 |
1 |
- |
|
|
Sustainable Product Life Cycle Management |
1.5 |
1 |
- |
|
|
Networks, Crowds, and Markets |
1.5 |
1 |
- |
|
|
International Management 1 |
1.5 |
1 |
Organizational Behavior |
|
|
Management of Teams |
1.5 |
1 |
Organizational Behavior |
|
|
Managing Negotiations |
1.5 |
1 |
Organizational Behavior |
|
|
Organizational Design |
1.5 |
1 |
Organizational Behavior |
|
Course No. |
Course name |
Credit points |
Hours |
Prerequisites |
|---|---|---|---|---|
|
Organizational Behavior for Business Administration |
3 |
2 |
- |
|
|
Principles of Strategy |
1.5 |
1 |
- |
|
|
Principles of Finance |
3 |
2 |
Statistics |
|
|
Management of Technology and Information |
1.5 |
1 |
- |
|
|
Marketing Management |
3 |
2 |
Economics |
|
|
Business Ethics |
1.5 |
1 |
- |
|
|
Financial Management |
3 |
2 |
Principles of Finance; Accounting |
Registration for courses at the School of Management is per available openings.
- A student may register for a maximum of three courses outside the curriculum, as approved by his permanent supervisor.
- A course outside the curriculum will be considered an elective course. A course outside the Faculty will receive credit points, as allocated by its home Department, and can count for up to 3 credit points at the Faculty of Engineering.
- Students with a B.Sc. in Industrial Engineering will select management courses from Section 4.1; Students with a BSc in other Disciplines will select management courses from Section 4.2.
Course No. Legend:
0571 – Industrial Engineering (Undergraduate)
0572 – Industrial Engineering (M.Sc. program)
0510 – School of Electrical Engineering
0540 – School of Mechanical Engineering
0368 – Computer Science
0365 – Dept. of Statistics
1231-1243 – School of Management
