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Introduction to systems engineering, Some Areas of Industrial Engineering/Operations Research: Facility Location, Quality Control, Production Planning, and Linear Programming. Some Areas of Automation/Control: Automation, The Concepts of Automatic Control, Open and Closed Loop Control. Instrumentation, and Use of Computers in Control. Systems Approach to Engineering Problems, Integrating the Above Tools. Applications of Systems Concepts in Engineering

Sample space, events, random variables, conditional probability, some discrete and continuous distributions, functions of random variables, sampling distributions, estimation and test of hypotheses.

Principles of modeling, linear and nonlinear lumped parameter dynamic models. Introduction to Laplace transform and system analysis. Linearization of nonlinear models. Modeling of Mechanical and Electrical systems. Transfer function and state space models. Laboratory activities include analog and digital simulation of models.

Roots of nonlinear equations. Solution of systems of linear and nonlinear algebraic equations. Numerical differentiation and integration. Interpolation, extrapolation, and approximation. Least-squares approximation and regression analysis. Numerical solution of ordinary differential equations. Introduction to error analysis. Engineering case studies. Note: SE 301 and MATH 321 are equivalent; only one can be taken for credit.

Linear Systems; time and frequency domain representations; open and closed loop systems; time and frequency domain analysis, stability; root locus; frequency response; compensators, output and state feedback, PID, lag, lead and lead-lag compensators. Design of simple compensators. Laboratory activities include analysis and control of physical processes as well as analog simulation. Note: SE 302 and EE 380 are equivalent; only one can be taken for credit.

New description : Modeling in Operations Research. Linear Programming : Simplex Method, Duality, Sensitivity Analysis. Network Models : Shortest Path, PERT/CPM, Maximum Flow Problems, Transportation and Assignment Problems. Elements of Queuing Models. Case Studies.

Unconstrained optimization; necessary and sufficient conditions for unconstrained minima. Derivative-free algorithm. The steepest descent and Newton algorithms. Conjugate gradient and quasi-Newton methods. Constrained optimization: Karush- Kuhn-Tucker conditions for optimality, algorithms for constrained optimization including SUMT, approximation and methods of feasible directions. Case studies in different engineering disciplines.

Introduction to concepts of economic decision-making from a cash flowviewpoint.It includes worth analysis, cash flowequivalence,ratesofreturn,replacementanalysis,benefit-costanalysis,depreciationandtaxes,andprojectsbreak-evenpoint,selection,andsensitivity analysis.

Binary arithmetic. Boolean algebra. Boolean functions and their simplification. Implementation of Boolean functions using logic gates. SSI, MSI, and LSI chips. Analysis and design of combinational circuits. Sequential logic: flip-flops, counters and registers. Analysis and design of sequential circuits. Basic elements of digital computers: register-transfer, micro operations, instruction codes, processor organization, arithmetic logic unit.

General measurement systems; static and dynamic characteristics, loading effects, signals and noise; sensing elements, resistive, inductive, electromagnetic, thermoelectric, elastic, piezoelectric, electromechanical, optical etc.; signal conditioning elements, d.c. and a.c. bridges, compensation by linearization, feedback, operational amplifiers, modulation/demodulation; signal processing elements, microcomputer based instrumentation, I/O devices, interfaces, data display units, examples of measurement systems such as flow, pressure, level, temperatures, etc.

Basic models of continuous and discrete-time signals and systems. Basic characteristics of signals (energy, power, peak amplitude). Properties of LTI systems. Review of block diagrams. Signal flow graph representations of LTI systems. Fourier analysis of continuous and discrete-time signals and systems. Basic concepts of signal modulation, signal sampling and reconstruction. Basic properties of Z-transforms and concept of transfer function. Basic random signal analysis. Applications of signals and systems concepts to linear control systems and digital signal processing.

Statistical models for quality assurance and control. Control charts for variables and attributes and their applications in process control. Process capability studies. Quality audits. Operating characteristic curves. Acceptance sampling. Statistical analysis and design of integrated quality control systems and computer applications. Cost of quality and the effects of quality on productivity.Case studies in applied quality assurance and control.

Manufacturing methods of metals and plastics including metal casting, forming, machining, welding, and plastic processing. Laboratory experiments and demonstrations in material behavior, forming, casting, welding and machining operations, metrology and dimensional control.

History of methods design and work measurement. Methods design. Process analysis. Operation analysis. Introduction to human engineering. Standardization. Work measurement. Predetermined motion-time systems. Standard data. Work sampling. Term project.

Review and Extension of Estimation and Test of Hypothesis and their application in Engineering. Introduction to Planned industrial experiments including Analysis of Variance, Regression and Design of Experiments, Taguchi Arrays and their Application in Quality Control.

Beginning of coop in summer. Description as given in SE 351.

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End of coop in summer. Description as given in SE 351.

A continuous period of 8 weeks of training spent in industry to gain exposure and appreciation of the systems engineering profession. Students are required to submit a report and make a presentation about their summer training experience and knowledge gained before receiving a grade of Pass or Fail for the course.

Elements of Computer Control Systems, A/D and D/A, Sampling theorem, signal conditioning, anti-alias filters, sensors, actuators. Feedback, feed forward, cascade and ratio controls. DDC. Control implementation with centralized and distributed computer systems. Architecture, Communication, Sequential Control, programmable controllers. Multi-tasking environment, concurrent languages, software engineering, communication protocols, case studies of distributed control systems and programmable controllers.

Elements of functional organization. Forecasting in production systems. Product and process design considerations. Deterministic and Stochastic Inventory Systems. production scheduling and line balancing. Capacity planning. Material Requirement Planning (MRP). Computer applications in Production Control. Case studies and applications.

Basic discrete-event simulation modeling, review of basic probability and statistics, selecting input probability distributions, random-number generators, generating random variables, output data analysis for a single system, validation of simulation models. A simulation language is used to stimulate selected industrial and computer models.

Microprocessor Architecture; basic microprocessor concepts, timing and sequencing, memory and I/O synchronization, data transfers, arithmetic and logic operations. Software development, assembler source programs, assembler directives and pseudo instructions. Interrupts and DMA; interrupt structure, priority, FIFO buffers, time and DMA. Microprocessor interfaces, parallel and serial interfaces, digital/analog conversion, input/output programming. Case-studies of microprocessor based systems in automation.

Review of processes modeling principles, Mass balance, Energy balance, Models of representative processes, Dynamic response, and Linearization. Process identification sing time and frequency domain techniques. Time delay, Smith predictor. Basic and advanced control strategies, e.g. PID, Feedforward, Internal model, and supervisory control. Time domain controller design, Controller tuning. Controller design in the frequency domain. Digital control. Case studies.

Advanced topics in linear programming: Integer programming, dynamic programming. Introduction to Stochastic Processes. Case studies.

Introduction to facility planning issues. Material handling. Facility location and layout and computer-aided techniques and packages. Storage and warehousing functions, emphasizing quantitative and simulation techniques.

Maintenance organization, maintenance strategy, forecasting maintenance work, maintenance capacity planning, component replacement decision models, maintenance Measurement and standards, scheduling of maintenance, maintenance material control, quality of maintenance jobs, maintenance productivity, maintenance audit, maintenance management information systems, case studies

Discrete-time signals and systems. Z-transform. Discrete-Fourier transform, Fast-Fourier transform. Digital filter design techniques.Effect of parameter and signal quantization. Power spectrum estimation. Note: SE 432 and EE 406 are equivalent; only one can be taken for credit.

Basic classical design techniques, i.e. lead/lag, PID, Minor loop, etc. Process identification. Introduction to advanced control strategies. Lab projects will include design and hardware implementation.

This course introduces the concepts of uncertainty and Modeling Error in Control System Analysis and Design. Review the basic methods and tools of Classical Control. Introduction to H2, Hoo Optimal Control and m (the Structural Singular Value) Analysis and Synthesis.

Introduction to instrumentation and its role in process control. Analog and digital signal conditioning. Thermal, mechanical, optical, sensors. Analog controllers. Digital controllers. Control loop characteristics. Data acquisition.

A course in an area of Automation reflecting current theory and practice

Study of human response into man-machine systems. Study of visual displays as a medium of input. Auditory and tactual displays. Human control of systems. Human/ computer interface, forms and CRT design, code design. Applied anthropometry and work space. Environments, illumination, atmospheric conditions and noise. Conducting comparison studies.

Introduction to structuring decision problems with single and multiple criteria under certainty, uncertainty, risk and conflict. Discrete MCDM: MVT, AHP, TOPSIS and interactive methods; Expert choice. Single and sequential decision problems under uncertainty and risks static and dynamic models. Decision problems under conflict : Game theory. Case studies.

Scheduling problems, optimality of schedules, single machine processing, basic results, precedence constraints and efficiency, constructive algorithms for flow-shops and job-shops, dynamic programming approaches, branch and bound methods, integer programming formulations, hard problems and NP-completeness. Heuristic methods: general approaches and worst case bounds, simulated annealing approach.

Selected topics in Industrial Engineering and/or Operations Research

An overview of large scale problems and the framework for Systems Engineering. Graphic tools for Systems Engineering. Interaction matrices and graphs, interpretive structure modeling. Spare matrix and decomposition techniques. Model reduction techniques. Case studies.

High volume discrete parts production systems. Fundamentals of CAD/CAM. Computers in manufacturing. Computer process monitoring. Systems for manufacturing support. Group technology and integrated manufacturing systems. Case studies for robots in industry. CAD/CAM using computer graphics laboratory.

Review of basic Probability, Statistical Independence, Conditional Expectation and Characteristic Function. Introduction to Stochastic Processes, Stationarity and Ergodicity. Markov Chains and Poisson Processes. Linear Models of Continuous and Discrete Stochastic Processes. Engineering Applications.

Design of Industrial Information Systems in both operational and decision-making modes, special attention to the planning and control activities, engineering and production data control, systems requirements, analysis, design and implementation of typical computerized industrial information systems, including: Manufacturing activity planning, Plant monitoring and control, Inventory management, Plant maintenance system. Case studies involving available packages. Students are required to complete a major project.

The scope of occupational safety: human safety; environmental safety; setting safety standards; safety administration; legal aspects of industrial safety in the Kingdom.

Background matrix algebra, measuring vectors and matrices, the singular value decomposition, numerical matrix algebra, theory of linear system of equations, the eigenvalue problem. Variational principles and perturbation theory. Numerical solution of Lyapunov and Riccati equations.

Floating-point computation. Numerical solution of ordinary differential equations; initial value and boundary value problems. Stiffness. Numerical solution of partial differential equations: finite differences, applications to the heat conduction. Laplace, and wave equations. Introduction to the finite elements method. The use of numerical software in modeling and digital simulation. Case studies drawn from various engineering disciplines.

Introduction to reliability engineering, hazard and reliability functions, analyzing reliability data, reliability prediction and modeling, fault tree construction and decision tables, Maintainability, maintenance and availability, reliability improvement

A design course that draws upon various components of the undergraduate curriculum. The project typically contains problem definition, analysis, evaluation and selection of alternatives. Real life applications are emphasized where appropriate constraints are considered. Oral presentation and a report are essential for course completion. The work should be supervised by faculty members. Team projects are acceptable wherever appropriate

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