Industrial and Systems Engineering Minor

Introduction to computer science. Covers problem solving methods and algorithm development; modern programming methodologies; and fundamentals of high-level block structured language using Python. Prerequisite: EGR181 or MAT115 (3 Units)

Introduction to computer science. Covers problem solving methods and algorithm development, modern programming methodologies, and fundamentals of high-level block structured language using C++. Prerequisite: MAT115 or EGR181 (3 Units)

An introduction to the primary statistical and probabilistic models used in the collection and interpretation of engineering data. The focus is on summary techniques, regression models, and application of the central limit theorem, confidence intervals, hypothesis tests, and analysis of variance. Prerequisite: MAT245 (3 Units)

Mathematical theory and applications, development of formulae, principles of statistical decision theory, descriptive measurements, probability concepts, random variables, normal distribution, inferential statistics, sampling distributions, confidence intervals, hypothesis testing, chi-squared procedures, linear regression, and the use of computers in statistics. (3 Units)

The first semester of a two-semester course providing a systematic development of the theories of probability and statistics. Students learn and use fundamental concepts of probability models, random variables and their distributions, reduction of data, estimation, testing of hypotheses, univariate normal inference, and statistical decision theory. The first semester is required for BA and BS statistics majors of all concentrations. Prerequisite: (MAT245,EGR120) or EGR121 or STA144 (3 Units)

Economic concepts of supply, demand, and production; cost-benefit analysis and break-even analysis; return on investment; analysis of options; time value of money; management of money: economic analysis, accounting for risk applied to the engineering process. Prerequisite: MAT245 or STA144 (3 Units)

The primary purpose of this course is to teach students the philosophies, principles and tools of industrial and systems engineering (ISE) through lectures, case studies and hands-on projects. The major topics include productivity and efficiency, Six Sigma, product and process design with systems engineering approaches, optimization and simulation, and AI, robotics and automation. Prerequisite: EGR305 or STA114 or STA310 (3 Units)

Properties of the principal families of materials used in mechanical engineering design with an introduction to the manufacturing processes used to convert these materials into finished products. Application of statistics and probability to material properties and manufacturing. Laboratory experiments in strength of materials, property of materials, and manufacturing processes. Prerequisite: EGR242 (4 Units)

Quantitative aspects of statistical quality control (process control, acceptance sampling by attribute and by variable, rectifying inspection), quality assurance and the management of QC/QA functions. Prerequisite: EGR305 (3 Units)

Production planning, forecasting, scheduling, and inventory; computer integrated decision systems in analysis and control of production systems, facilities layout and design. Prerequisite: (EGR305,EGR381) (3 Units)

The course focuses on the systematic planning, design, and operations of the business process that ultimately impacts the management of production and the delivery of goods and services to end-users. Particular emphasis will give an overview of the business processes, and outlines and supports the understanding of how a business operates. The topics of the course will cover the tactical and strategic sourcing relationships of resources including supply aspect, purchasing, procurement, forecasting, inventory control, quality, sustainability, work-in-process, and negotiations that provide management with the tools to deliver goods and services to end-users. (3 Units)

This course explores quantitative methods utilized in business decision-making, with an emphasis placed on problem solving and evaluation, as well as applications in marketing, finance, accounting, and operations. Topics may include decision analysis, linear programming, forecasting techniques, statistical process control, and inventory models. A project with practical problem solving is required. Prerequisite: BUS315 (3 Units)

The course focuses on management techniques with analytical framework needed to solve problems associated with a firm's logistics planning and control. The course covers the core competencies to manage the planning, implementing, controlling, and distributing of goods and services for a firm. This course will address topics of production planning and scheduling, inventory management, and the design and management of supply and distribution networks. (3 Units)