Undergraduate Courses | Industrial & Management Systems Engineering

Definition and concepts of industrial and management systems engineering (IMSE), the roles and jobs of industrial engineers, professional conduct and ethics of engineers, activities of IMSE, applications of IMSE tools and techniques to real-world organizations.

Lab experiments, analysis, and writing reports, basic lab experiments covering quality, work design and measurement, facilities, simulation, and ergonomics and safety, exposure to IMSE instruments and equipment and their functions, lab safety provisions.

Work study, productivity, and quality of life, the work study approach, method study procedure, techniques and tools for process analysis and redesign and simplification, work measurement sampling and time study, setting time standards.

Safety and health engineering fundamentals, engineering and administrative controls of hazards in industry and business, risks to employees, facilities, production, and the environment, local and international safety and health laws, regulations and standards, incident data recordkeeping and reporting, hazard assessment techniques and controls, safety and health management systems.

Random samples and sampling distributions, point and interval estimation, confidence intervals and tests of hypotheses for a single and two populations for different parameters (mean, variance, proportion), simple linear regression and correlation, multiple linear regression, analysis of variance, nonparametric statistics.

Analysis of cost elements. Cost centers, modeling of cost functions, overhead allocation, taxes, depreciation methods, financial reports and performance analysis, break-even analysis, probabilistic and stochastic cost systems.

Models and methods of operations research in solving engineering and management problems, linear programming (LP), simplex method, duality, sensitivity analysis, transportation, assignment and transshipment problems and solutions, network flow models, integer programming (IP).

An overview of project management, proposals and contracts, project scope definition, work breakdown structure, developing a network plan, project scheduling, managing risk, time-cost trade-off, resource allocation and leveling, managing project teams, progress and performance measurement and evaluation (project control), using a project management software, case studies.

Exploring data by using different tools including Data Analysis and Pivot Tables using a spreadsheet software, regression analysis for categorical data, decision analysis involving multiple objectives. Measuring attributes, determining weights of attributes, aggregating benefits, trading benefits against costs, sensitivity analysis, decision analysis under uncertainty, single and multi-attribute utility functions, expected utility criterion, decision trees and utilities, multi-stage decision trees.

Practical work for at least 200 hours on a specific practical Industrial & Management Systems Engineering (IMSE) problem or area in one of the manufacturing or service organization under the supervision of a faculty member and a focal person from the selected organization.

A topic to be selected by the department to address new subjects in Industrial Engineering.

Definitions and concepts of human factors/ ergonomics, man-machine systems, human capabilities. Design of displays and controls. Introduction to engineering anthropometrics and bio-mechanics, design of hand tools and tasks/jobs, introductory manual material handling, design of workstations, environmental conditions.

Review of ergonomic, safety and environmental assessment methodologies, ergonomics applications in process industry, impact of environment on workplace design, control of hazards and risks to employees, facilities, production, and the environment, safety and health regulations and standards.

Facilities planning and its relation to product, process, and schedule design, methods to generate effective layout designs based on flow, space, and activity relationships using analytical, simulation, and computer-aided layout design tools, material handling systems, modeling and analysis of single and multi-facility location problems.

Manufacturing systems and models, high volume production and analysis of production flow lines, assembly systems and line balancing methods, material flow and multi-stage systems, process scheduling with different products, modern manufacturing management systems including just in time and flexible systems, applications of analytical and simulation models in manufacturing systems.

High Volume Discrete Parts Production Systems, CAD/CAM fundamentals, Numerical Control (NC) Manufacturing Systems, part programming, NC justification advances in NC (CNC, DNC, Adaptive Control), tooling for NC and CNC, overview of group technology, Flexible Manufacturing Systems (FMS), and robotics in manufacturing, related laboratory experiments.

Reliability theory and modeling approaches, topics include: failure data analysis, maintainability, reliability models, reliability and maintainability systems, applications and implementation issues and case studies.

Methods of production planning, deterministic and stochastic inventory control models, short to intermediate production planning decisions using quantitative techniques, forecasting techniques, aggregate production planning, material requirements planning, production scheduling models.

Identification of bottleneck impact of human performance on productivity, effect of the interaction between technological advances and human capabilities on performance and productivity, cost reduction and productivity improvement programs.

Understanding the concepts of quality in products and services, specifications and tolerances, design of quality control systems, quality control techniques, statistical process control charts for variables and attributes, acceptance sampling techniques, operating characteristics curves, process capability analysis, international quality standards, total quality management (TQM), quality control software.

Introduction to experimentation, review of simple comparative experiments, analysis of variance models and applications, randomized blocks and Latin square designs, factorial designs, regression models and process optimization.

Philosophy and concepts of quality management, tools and techniques for quality improvement, applications of statistical process control in healthcare, quality and measurement in healthcare, the process of patient satisfaction, TQM/CQI strategies in healthcare.

Probabilistic models in operations research, Queuing Theory, Markov Decision Processes and Markov Chains, decision analysis, and utility functions.

Multi objective optimization and goal programming, discrete optimization models and discrete optimization methods, unconstrained and constrained nonlinear programming.

Supply chain and logistic problems, multi-facility networks and location analysis, supply chain restructuring, applications of linear programming and transportation algorithms to supply chain management problems, managing risk and uncertainty in supply chain analysis, software applications.

Engineering management and leadership, the functions of engineering management, business Fundamentals for engineering managers, marketing management, engineers as managers and leaders, quality management systems, ethics in engineering management, globalization, engineering management in the New Millennium.

The course is intended to develop the appreciation and know-how of the design of quality management systems, knowledge of the principles and criteria of organizational excellence models and programs, and the application of operational excellence methodology to achieve outstanding operations and business performance. Students will learn primarily through workshops, case studies, and projects.

The course is intended to develop appreciation of the importance and basic knowledge of accounting and finance for the engineering manager. The aim is to develop basic understanding of the development and analysis of financial statements, e.g. income statement, balance sheet, and cash flow, time value of money, valuation techniques, replacement analysis, and projects evaluation.

The course is intended to develop the knowledge and skills in marketing decision making in marketing planning, deployment, and product design through a technology-enabled and model-supported decision process. Students will learn the various issues and problems in making decision in the marketing of new products and services, new product marketing process opportunity identifications, concepts selection, product design, pretest and test marketing, launching and profit managements.

The course is intended to inspire entrepreneurial innovation and creativity through interactive lectures, workshops, and case studies. The aim is to develop the understanding of students regarding how innovation leads to the emergence of new knowledge which forms the basis of new products, services and processes, and the role which entrepreneurship plays in shaping the ways in which opportunities are identified, shaped and taken to the market through the formation of new enterprises or the integration of innovation into existing organizations.

The course is intended to develop appreciation of the importance -- and knowledge of -- the various topics of law for the practicing engineer and engineering manager. The aim is to develop practical understanding of the business types, legal system, sales and marketing laws, contract laws, environmental laws, patents, copyrights, trademarks and trade secrets, and the employment law.

System definition, manufacturing and service systems, model formulation, discrete events simulation, random number generation, data gathering, simulation input and output analysis, system entities and its attributes, application of simulation languages and software to manufacturing and service systems.

Artificial intelligence and expert systems, applications of expert systems, expert systems components, expert systems development, rule-based knowledge acquisitions and representation.

A topic to be selected by the department to address new subjects in Management Systems Engineering.

Application of Industrial & Management Systems Engineering (IMSE) in oil and chemical industries, and power generation and distribution, application in banking and investments firms, application in healthcare and emergency service systems, application in government and public services.

A capstone design course, students are exposed to creative design and synthesis in the various areas of industrial and management systems engineering. All knowledge acquired in mathematical modeling and economic techniques are utilized in conducting the design analysis.