Master of Engineering & Systems Management

The Ministry of Education (MOE) approved two-year M. Sc. in Engineering & Systems Management consists of both thesis and courses-only options. The program was developed in collaboration with the Centre for Complex Engineering Systems (CCES) at KACST (King Abdulaziz City for Science & Technology) and MIT (Massachusetts Institute of Technology). The elective courses span the themes: Decision Analysis & Data Analytics, Manufacturing & Supply Chain Management, and Development of Cyber-Physical Systems. This program is not an MBA; it is a technical master’s degree focused on engineering, data science and computation.  “Systems thinking” is an important part of the degree, whether applied to the improvement of existing systems and operations or the creation of new products and services. Personal engineering leadership development is a mandatory part of the program.

Classes

MEM 501: Statistics and Data Analytics

Review of probability and probability distributions. Data description. Random samples and sampling distributions. Parameter estimation. Tests of hypotheses. Design and analysis of single-factor experiments: the analysis of variance. Design of experiments with several factors. Simple linear regression and correlation. Multiple regression. Nonparametric statistics. Introduction to statistical quality control and reliability engineering.

MEM 502: Systems Architecture and Engineering

General introduction to systems engineering using both the classical V-model and the new META approach. Topics include stakeholder analysis, requirements definition, system architecture and concept generation, trade-space exploration and concept selection, design definition and optimization, system integration and interface management, system safety, verification and validation, and commissioning and operations. Discusses the trade-offs between performance, lifecycle cost and system operability. Readings based on systems engineering standards and papers. Students apply the concepts of systems engineering to a cyber-electro-mechanical system, which is subsequently entered into a design competition.

MEM 503: Project & Program Management of Complex Systems

Covers the elements of project management critical to the success of engineering projects: project management framework, strategic management and project selection, project organization, human aspects of project management, conflicts and negotiations, scope management, time management, cost management, risk management, contracts and procurement, project termination, the project management office, and modern developments in project management.

MEM 504: Advanced Engineering Economics & Cost Analysis

Covers the theory and application of advanced engineering economics principles and methods. Studies the effects of inflation, depreciation and taxes, cost estimation, sensitivity analysis, risk and uncertainty, capital budgeting, multi-attribute decision making, advanced asset replacement analysis and real option analysis.

MEM 505: Operations Engineering & Management

This course focuses on business processes, procedures, analytic methods and strategies used to transform various inputs into finished goods and services. The main course aim is to familiarize students with the problems and issues confronting operations managers, and provide them language, concepts, insights and tools to deal with these issues in order to gain competitive advantage through operations. Operational issues include designing, acquiring, operating, and maintain the facilities and processes; purchasing new materials; controlling and maintain inventories; and providing the proper labor to produce a good service so that customer expectations are met.

MEM 506: Leadership Development for Engineers & System Managers

This course includes topics such as public speaking, leading diverse and creative teams, dealing with uncertainty and adversity and strategies for having difficult conversations in the workplace. It is a general introduction of engineering leadership at the graduate level.

MEM 507: Applied Computation and Data Science

Presents fundamentals of computing and programming in an engineering context with an emphasis on data science. Introduces web computing, data structures, and techniques for data analysis. Includes filtering, linear regression, simple machine learning (clustering and classifiers), and visualization. Surveys techniques for ingesting, processing, analyzing, and visualizing big data from a range of fields, including environmental, transportation, supply chain, city data. Basic concepts of data storage and web server-side programming are covered. Students use JavaScript and HTML5 programming language to complete weekly assignments.

MEM 509: Systems Modeling and Simulation

Generating discrete and continuous random variables. Discrete-event simulation. Statistical analysis of simulated data.Variance reduction techniques. Statistical validation techniques. Markov chain and Monte Carlo methods. Experience with a modern discrete-event simulation package (e.g., ARENA, ProModel).

MEM 510: Decision & Risk Analysis for Eng & Syst Managers

Covers the theory and practice of analyzing decisions arising in engineering systems. Covers multiple objectives, influence diagrams, decision trees, and sensitivity analysis, and probability assessment, multi-attribute utility and human biases. Describes practical applications through real world systems model building. Uses decision analysis software and spreadsheets to solve real-life problems through case studies.

MEM 511: Deterministic Management Science

Mathematical modeling and the operations research approach for solving engineering decision problems. Formulation and classification of optimization models. The concept of improving search directions. Formulation of linear programs (LPs).The simplex algorithm and alternative approaches for solving LPs. Duality and sensitivity analysis in linear programming. Multi-objective optimization and goal programming. Network flow models. Formulation and solution methods of integer programs. Nonlinear programming. Introduction to metaheuristics. The course emphasizes problem formulation and solution via modern optimization modeling software

MEM 512: Special Topics I

Selected topics of current interest in Engineering & Systems Management. The course is designed to give the students an opportunity to pursue special studies not offered in other courses.

MEM 513: Special Topics II

Selected topics of current interest in Engineering & Systems Management. The course is designed to give the students an opportunity to pursue special studies not offered in other courses.

MEM 514: Logistics & Supply Chain Engineering

Explores key logistical issues related to the design, planning and operation of supply chain systems. Includes topics such as supply chain structure, supply chain performance metrics, network design, facility location in a supply chain, aggregate planning, planning and managing inventory in a supply chain, transportation in a supply chain, pricing and revenue management

MEM 515: Advanced Quality Engineering

Covers the techniques and applications of quality control using total quality management and reliability engineering. Includes sampling procedures, product quality and control, statistical process control charts and troubleshooting, product acceptance sampling plans, process capability analysis, an introduction to six sigma and design of experiment, time-to-failure, failure rate, reliability and system reliability.

MEM 516: Methodologies for Operational Excellence

Development of the concept of a lean organization. Identification of waste activities. How to use flow analysis to analyze a process and identify non-value-added activities. Understanding of the standard lean operations tools: 6S, visual workplace and visual order control, manufacturing cells, use of takt time, setup time reduction, standard worksheets, etc. The benefits of incorporating lean concepts during the development phase of new products. Error-controlling devices and how they can be used during the manufacturing process to reduce errors. Understanding what sigma quality concepts are, introduction to how to conduct kaizen blitzes, and why continuous improvement is important to the organization.

MEM 517: Production Systems Analysis & Design

This course investigates fundamental properties that govern production systems and utilizes them for analysis, design and continuous improvement. Using actual case studies of real-world problems and successful, implemented solutions, this course teaches students to design novel, efficient production systems, understand reasons for lost productivity and design continuous improvement projects, and use Measurement-Based Management techniques for operating production systems in Just Right regimes. Topics include quantitative methods for analysis of production systems; analytical methods for design of lean in-process and finished goods buffering; measurement-based methods for identification and elimination of production system bottlenecks; and system-theoretic properties of production lines.

MEM 518: Warehouse Systems Analysis & Design

This course focuses on efficient warehouse operations and covers the following topics: Management of warehouse fundamentals: space and time; Storage policies: dedicated and shared, and their use; Warehouse analytics: discover opportunities for improvement. Size and stock a forward area for split-pallet and split-case picks. Pallet operations and layout; Order-picking in high-volume and in low-volume environments; Benchmarking warehouse performance; Maintaining inventory accuracy; Warehouse Management Systems; and Issues and trends in automation.

MEM 519: Product & Service Development

The focus of this course is the integration of marketing, design, and production functions of the firm in creating a new product or service. The course is designed to prepare students to contribute in the development of strategies and tasks relevant to new product or service introductions.

MEM 520: Rapid Prototyping for Cyber-Physical Systems

Design and prototype of large-scale technology intensive systems. Design project incorporating infrastructure systems and areas such as transportation and hydrology; for example, watershed sensor networks, robot networks for environmental management, mobile Internet monitoring, open societal scale systems, crowd-sources applications, traffic management. Design of sensing and control systems, prototyping systems, and measures of system performance. Modeling, software and hardware implementation.

MEM 521: Internet of Things

The course introduces the Internet of Things (IoT) along with its definition, its enabling technologies, and its applications in various sectors. It further describes technology models for tagging, sensing and actuation, as well as data generation and processing. The latter includes both cloud- and edge-based IoT management and processing architectures. The course involves a hands-on-experience that culminates in an implementation project.

MEM 522: Information Systems Analysis and Design

This course provides students with concepts of the analysis and design processes and allows students to use industry standard methodology and framework to develop Industrial business information systems. The course combines terminology with conceptual and practical approaches to designing and implementing business systems. Analytical and problem-solving skills are developed through a modern integrated, structured approach. Predictive and adaptive approaches to systems development life cycle (SDLC) using an iterative approach are covered. The course contains the entire analysis and design process from conception through implementation, including training and support, system documentation and maintenance, and relevant project management techniques.

MEM 523: Telecommunications & Network System Analysis & Design

The course introduces telecommunications networks and their various design and operation considerations. After a review of the widely used technologies and their applications, the course focuses on technical and economic aspects of network design including architecture considerations (access-core-homing); link and network quality indicators; basics of teletraffic engineering; preliminaries of network provisioning and backbone design; and CAPEX/OPEX considerations and tradeoffs. The course culminates in a real-world network analysis and/or design case study.

MEM 600: Thesis A

Students completing a Thesis Option master’s degree are expected to write a report, referred to as a thesis, on the results of an original investigation, in conjunction with a Master’s Advisory Committee. Length and style of the thesis vary by college/department. All these are filed with the Office of Graduate Studies. A Master’s Advisory Committee will be formed for each student. The Chair of the Committee must have research and graduate student advising experience. This Committee will assist the student in the formulation of the Thesis Proposal, and later advise the student in the execution of the research, the Thesis write-up, and help the student to prepare for the oral defense.

MEM 600: Thesis B

Students completing a Thesis Option master’s degree are expected to write a report, referred to as a thesis, on the results of an original investigation, in conjunction with a Master’s Advisory Committee. Length and style of the thesis vary by college/department. All these are filed with the Office of Graduate Studies. A Master’s Advisory Committee will be formed for each student. The Chair of the Committee must have research and graduate student advising experience. This Committee will assist the student in the formulation of the Thesis Proposal, and later advise the student in the execution of the research, the Thesis write-up, and help the student to prepare for the oral defense.

MEM 601: Research/Capstone Project

This intent of this project is to enable to the student to learn to pursue a chosen topic through a literature search on atopic approved by the graduate advisor, collection and analysis of data, project report preparation and defence. Although this course officially begins in second year the trainees are encouraged to identify a project topic and supervisor in their first year so that they are able to begin their research project in the fall of their second year.