91爆料

IND E 101 Introduction to Industrial Engineering (1) SSc
Examines the basic concepts and methods of industrial engineering through team-based hands-on activities. Explores the profession of industrial engineering. Discusses resources available to industrial engineering students at the 91爆料. Offered: A.

IND E 250 Fundamentals of Engineering Economy (4) NSc
Basics of industrial cost analysis and accounting. Application of interest computations to engineering decision making. Analysis of engineering alternatives based on use of interest computations, valuations, depreciation, and cost estimates. Offered: ASp.

IND E 310 Linear and Network Programming (4)
Modeling and optimization of linear network problems. Topics include: optimization of linear systems, mathematical model design, simplex method, primal-dual algorithms, parametric programming, goal programming, network problems and algorithms, and PERT/CPM. Prerequisite: either MATH 136 or MATH 208; and either CSE 121, CSE 122, or CSE 142. Offered: A.

IND E 311 Stochastic Models and Decision Analysis (4)
Stochastic systems analysis to industrial engineering problems. Topics include: Markov chains, queueing theory, queueing applications, and decision analysis. Prerequisite: IND E 310 and IND E 315. Offered: W.

IND E 315 Probability and Statistics for Engineers (3) NSc
Application of probability theory and statistics to engineering problems, distribution theory and discussion of particular distributions of interest in engineering, statistical estimation and data analysis. Illustrative statistical applications may include quality control, linear regression, and analysis of engineering data sets. Course overlaps with: TME 351. Prerequisite: either MATH 135, MATH 136, MATH 207, or AMATH 351. Offered: AWS.

IND E 316 Design of Experiments (4) NSc
Introduction to the analysis of data from planned experiments. Analysis of variance for multiple factors and applications of orthogonal arrays and linear graphs for fractional factorial designs to product and process design optimization. Regression analysis with applications in engineering. Prerequisite: either IND E 315, STAT 341, or STAT 390. Offered: jointly with STAT 316; W.

IND E 321 Statistical Quality Control (4)
Design of quality control and assurance systems. Statistical Process Control (SPC) design and implementation. Control charts for attributes and variables. Process capability analysis and process improvement techniques. Statistical tolerance design. Quality management and recent developments. Prerequisite: IND E 315 Offered: Sp.

IND E 337 Introduction to Manufacturing Systems (4)
Description of manufacturing systems. Includes discussion of current trends in manufacturing. Introduces process flow analysis, manufacturing organizations including job-shop, assembly lines, and group technology, manufacturing inventory philosophies (just-in-time, MRP, OPT), work environment, and work simplification.

IND E 338 Simulation (4)
Discrete-event simulation methodology emphasizing model formulation and construction with modern simulation languages and environments, statistical basis for evaluating model results, design and management of simulation projects. Application to manufacturing, retail, and service industries. Prerequisite: IND E 311, which may be taken concurrently; and IND E 337. Offered: W.

IND E 351 Human Factors in Design (4)
Engineering considerations of the abilities and limitations of the human aspect in the design of operational systems and components. Functional, psychological, physiological, and environmental considerations. Offered: Sp.

IND E 412 Integer and Dynamic Programming (4)
Modeling and optimization of problems and dynamic programming approach to optimization. Topics include: integer programming formulation techniques, linear and Lagrangian relaxation, branch-and-bound and cutting-plane methods, integer programming applications, and dynamic programming. Prerequisite: IND E 311. Offered: Sp.

IND E 426 Reliability Engineering and System Safety (4)
Reliability and system safety measures. Life distributions and their applications in reliability. System reliability models. Design by reliability and probabilistic design. Reliability and safety analysis through FMECA and FTA. Reliability estimation and measurement by testing for binomial, exponential, and Weibull distributions. Prerequisite: IND E 315.

IND E 427 Data Analytics for Systems Engineering (4)
Emphasizes data-driven system modeling, including basic statistical learning models, and system modeling and decision-making. Covers experimental design for data collection, tree-based control charts for process monitoring, rule-based decision-making, and diagnosis of root causes as learning problems. Students develop connections between emerging statistical learning techniques with system modeling and optimization methods. Prerequisite: either IND E 315, STAT 390, or STAT 391; recommended: basic programming skills; and experience with R programming language or Matlab.

IND E 430 Manufacturing Scheduling and Inventory (4)
Manufacturing scheduling and inventory control for different work organizations. Coverage of workforce scheduling, job- and flow-shop scheduling and order release, production line balancing, MRP II, Lean Production, and data management. Particular attention to computer-based aspects of management and scheduling for manufacturing and service industries. Prerequisite: IND E 310 and IND E 337, both of which may be taken concurrently. Offered: A.

IND E 439 Plant Layout and Material Handling (4)
Design of new or expanding industrial facilities. Consideration of work organization and layout. Study of basic design of plant systems, including plumbing, electrical, HVAC, illumination, acoustics, and waste handling. In depth coverage of material handling system design and equipment choices. Prerequisite: IND E 310, which may be taken concurrently. Offered: A.

IND E 455 User Interface Design (4)
Design oriented to cover fundamentals of user interface design; models on human computer interaction, software psychology, input devices, usability, cognitive and perceptual aspects of human-computer interaction, advanced interface, and research methodologies are discussed.

IND E 470 Systems Engineering (4)
Concepts of system approach, system hierarchies, functional analysis, requirements, trade studies, and other concepts used to define and integrate complex engineering systems. Introduction to risk analysis and reliability, failure modes and effects analysis, writing specifications, and lean manufacturing. Offered: jointly with A A 470; Sp.

IND E 491 Professional Practice Seminar (1)
Speakers from industry help students explore the wide variety of careers and opportunities available in the ISE field. Speakers cover topics such as elective coursework and extra-curriculars, networking, getting hired, professional ethics, and how to be flexible in a dynamic work environment. Credit/no-credit only. Offered: A.

IND E 494 Design in the Manufacturing Firm (4)
Engineering design in manufacturing firms is presented. Topics include design methodology, concurrent engineering, and project management. Focus on the relationship between product design and manufacturing (design for production and assembly). Prerequisite: IND E 337. Offered: W.

IND E 495 Industrial Engineering Design (4)
Capstone senior design project involving identification and synthesis of industrial engineering skills. Students apply their knowledge of industrial engineering to actual industrial problems. Prerequisite: IND E 494. Offered: Sp.

IND E 496 Technology-Based Entrepreneurship (3)
Concentrates on hands-on aspects of innovation and entrepreneurial enterprise development. Examines relationships between innovation, iterative prototyping, and marketing testing. Students identify market opportunities, create new technology-based products and services to satisfy customer needs, and construct and test prototypes. Offered: jointly with M E 496; Sp.

IND E 498 Special Topics in Industrial Engineering (1-5, max. 9)
Lecture and/or laboratory.

IND E 499 Special Projects (2-5, max. 12)

IND E 508 Stochastic Processes in Engineering (3)
Non-measure theoretic introduction to stochastic processes. Topics include Poisson processes, renewal processes, Markov and semi-Markov processes, Brownian motion, and martingales, with applications to problems in queuing, supply chain management, signal processing, control, and communications. Prerequisite: E E 505. Offered: jointly with E E 508.

IND E 512 Introduction to Optimization Models (3)
Presents optimization models that are used in applications such as industrial engineering, production, transportation, financial investment, healthcare systems, and environmental ecology. Problems span a variety of continuous and integer optimization models, with discussion of multi-objectives and incorporating randomness into optimization models.

IND E 513 Linear Optimization Models in Engineering (3)
Advanced formulation techniques to expand applications of linear programming to large-scale models. Appreciation of role of optimization models in engineering applications through introduction of techniques such as decomposition. Individual engineering projects. Prerequisite: IND E 310 or permission of instructor.

IND E 515 Optimization: Fundamentals and Applications (5)
Maximization and minimization of functions of finitely many variables subject to constraints. Basic problem types and examples of applications; linear, convex, smooth, and nonsmooth programming. Optimality conditions. Saddlepoints and dual problems. Penalties, decomposition. Overview of computational approaches. Prerequisite: Proficiency in linear algebra and advanced calculus/analysis; recommended: Strongly recommended: probability and statistics. Desirable: optimization, e.g. Math 408, and scientific programming experience in Matlab, Julia or Python. Offered: jointly with AMATH 515/MATH 515.

IND E 516 Applications of Optimization in Engineering Design (3)
Discussion of issues arising in applications of optimization to engineering design. Emphasis on formulating problems and selecting appropriate solution techniques. Random search methods for problems otherwise computationally intractable. Individual projects in engineering optimal design. Prerequisite: AMATH 515/MATH 515/IND E 515 and MATH 328 or permission of instructor.

IND E 517 Markov Decision Processes (3)
Markov Decision Processes (MDPs) encapsulate a broad class of mathematical models for solving sequential decision problems under uncertainty. Combines techniques from linear/convex optimization, probability, statistics, and machine learning to build a modeling, theoretical, and algorithmic foundation for MDPs. Prerequisite: either IND E 508 and IND E 513, other similar classes in optimization and stochastic models, or permission of instructor. Coding experience with languages such as MATLAB or Python; recommended: graduate level optimization, probability, and statistics. Computer programming.

IND E 519 Healthcare Modeling and Decision Making (3)
Applications of operations research in healthcare. Introduction to a variety of modeling techniques including decision analysis, cost-effectiveness analysis, Markov models, Markov decision processes, dynamic programming, simulation, queuing, scheduling, machine learning and their applications in healthcare management and medical decision making.

IND E 521 Statistical Quality Engineering (3)
Introduction to statistical methods for quality engineering. Topics include modeling and inference about quality, and design and implementation of quality control methods.

IND E 524 Robust Design for Process Improvement (3)
Introduction to robust design for process improvement. Applications of design of experiments for product and process design optimization. Experimental design using factorial design and fractional factorial design. Robustness in design and quality improvement for complex systems including Taguchi methods and response surface methodology. Prerequisite: IND E 316/STAT 316 or equivalent. Offered: W.

IND E 526 Reliability in Product Design and Testing (3)
Product assurance including reliability and quality engineering. Reliability design, measurement, and optimization. Advanced topics in probabilistic design. Design of reliability test plans and analysis of test data. Design of reliability programs and their management.

IND E 527 Data Analytics for Systems Engineering (3)
Emphasizes data-driven system modeling, including basic statistical learning models, and system modeling and decision-making. Covers experimental design for data collection, tree-based control charts for process monitoring, rule-based decision-making, and diagnosis of root causes as learning problems. Students develop connections between emerging statistical learning techniques with system modeling and optimization methods. Prerequisite: either IND E 315, STAT 390, or STAT 391; recommended: coursework in probability and statistics; basic programming skills; and experience with R programming language or Matlab. Offered: A.

IND E 535 Engineering Simulation (3)
Advanced applications of discrete event, continuous, and combined discrete-continuous simulation modeling, detailed examination of fundamental computer programming concepts underlying the design and development of simulation languages, variance reduction techniques, and output analysis for various engineering, service systems, and manufacturing applications. Prerequisite: IND E 424 or equivalent.

IND E 537 Smart Manufacturing Systems (3)
Design, modeling and analysis of manufacturing systems, capable of intelligent decision making for optimal and/or robust productivities. Covers automation, digitization, on-demand design, and demand-supply forecasting. Course overlaps with: TECE 557. Offered: A.

IND E 543 Virtual Interface Technology (3)
Explores advanced concepts and technologies for interfacing humans to complex machines, with focus on virtual interfaces. Interface design principles reviewed from psychological and technological perspectives. Hardware, software, and mindware aspects of virtual interfaces investigated. Applications postulated and designed. Prerequisite: graduate standing in College of Engineering or permission of instructor.

IND E 546 Inferential Data Analysis for Engineers (3)
Application of statistical methods to analyze transportation systems, with an emphasis on modeling individual behaviors and drawing sound inferences about cause and effect. Addresses linear regression and common misuses; generalized linear models including logit and negative binomial; multilevel modeling; matching methods. Emphasizes frequentist approaches but introduces Bayesian analysis and extensions of regression modeling to machine learning. Prerequisite: either IND E 315, STAT 390, or equivalent; recommended: standard introductory probability and statistics course. Offered: jointly with CET 521; W.

IND E 548 Human Performance Modeling (3)
Covers emerging concepts and methods of human performance modeling (HPM). Offers an integrated perspective on the behavioral, neural, and physiological bases of HPM at work. Students learn about each stage of the human information processing model and its neural and physiological recordings. Students also review recent articles to understand how HPM can be applied to diverse work settings. Recommended: an introductory course in human factors at the undergraduate level.

IND E 549 Research Methods in Human Factors (3)
Includes fundamental guidelines for survey design, controlled experiments, quasi-experimental, and observational studies. Focus on safety, productivity, functionality, and usability. Review of journal articles on research methods and design issues, given functional, psychological, physiological, and environmental constraints. Recommended: introductory class in human factors. Offered: jointly with ENV H 549; Sp.

IND E 564 Recognition of Health and Safety Problems in Industry (2)
Develops skills in occupational health and safety hazard recognition in a variety of important Northwest industries. Focuses on process understanding and hazard recognition skills during walk-through inspections of several local facilities, stressing a multidisciplinary approach. Offered: jointly with ENV H 564; A.

IND E 566 Introduction to Ergonomics (3)
Basic principles of ergonomics in work environment applied to problems of worker and management. Topics include measurement of physical work capacity, problems of fatigue and heat stress, applied biomechanics, worker-machine interactions and communication, design of displays and controls. Prerequisite: basic human physiology or permission of instructor. Offered: jointly with ENV H 566/NSG 508; W.

IND E 567 Applied Occupational Health and Safety (3)
Application of occupational safety and health principles. Student teams perform evaluations, assess production methods/processes and exposures, health and safety procedures and programs, and develop engineering and administrative controls. Students perform on a consulting project with a local company including budgeting, project reporting, and presentation. Offered: jointly with ENV H 559/NSG 505; Sp, even years.

IND E 569 Occupational Biomechanics (4)
Lectures and laboratories address human occupational biomechanical and physiological limits and measurement, analysis, and modeling techniques that are used by ergonomists for design of safe, healthful, and productive physical work. Prerequisite: ENV H 566 or permission of instructor. Offered: jointly with ENV H 569; Sp, even years.

IND E 570 Supply Chain Systems (3)
Develops concepts related to the design, evaluation, and performance of supply chain systems through an exploration of contemporary practice and research, focusing on current issues, analytical frameworks, and case studies. Prerequisite: IND E 315 or equivalent.

IND E 581 Navigating the Business Environment (3)
Covers the fundamentals of finance and accounting, marketing, strategy, and business communication as well as the skill of identifying and influencing the key decision maker. Offered: A.

IND E 582 Technical Leadership (3)
Includes how to motivate, reach consensus, work virtually, recruit, and work with engineers from different cultures. Offered: W.

IND E 583 Decision Analysis in Engineering (3)
Examines multi-criteria decision tools involving qualitative and quantitative methods. Covers decision trees, subjective probability, utility and value theories, goals and objectives, risk, optimization, and simulation. Includes case studies in decision and systems analysis. Offered: Sp.

IND E 584 Project Performance (3)
Examines the fundamentals of project performance and application of systems engineering theory, concepts, and tools and techniques to plan, manage, and accomplish organizational objectives in a project framework. Also considers the critical roles leadership and team development plays in successful completion of projects. Offered: S.

IND E 585 Systems Architecture and Model-Based Systems Engineering (3)
Introduction to systems architecture through development of system requirements, allocations of functionality and reintegration. Utilizes model systems engineering as a graphical, mathematical, and modeling tool for systems analysis. Offered: A.

IND E 586 Systems Engineering Risk: Assessment and Management (3)
Management of systems engineering risk ensures costs, schedule, and technical performance objectives are achieved. Covers analysis methods and stochastic modeling for assessing and making decisions about projects and financial and technical risks associated with complex systems engineering projects. Also covers balancing risks across the systems development like cycle.

IND E 587 Technical Entrepreneurship for Systems Engineering (3)
Demonstrates how a well-modeled system can simulate potential operations and outcomes as well as system viability. Topics include: analytical modeling and simulation, value creation and comparative metrics, risk identification and inter-dependent requirements within the system architecture. Offered: S.

IND E 591 Seminar (1-)
Topics of current interest in industrial engineering. Prerequisite: graduate standing in Industrial Engineering or permission of instructor. Credit/no-credit only. Offered: A.

IND E 592 Seminar (-1-)
Topics of current interest in industrial engineering. Prerequisite: graduate standing in Industrial Engineering or permission of instructor. Credit/no-credit only. Offered: W.

IND E 593 Seminar (-1)
Topics of current interest in industrial engineering. Prerequisite: graduate standing in Industrial Engineering or permission of instructor. Credit/no-credit only. Offered: Sp.

IND E 595 Global Integrated Systems Engineering ([4/5]-, max. 9)
Covers systems engineering, project management, finance and economics in a global environment. Offered: AW.

IND E 596 Global Integrated Systems Engineering Project (3)
Project-based systems design course. Prerequisite: IND E 595. Offered: Sp.

IND E 599 Special Topics in Industrial Engineering (1-5, max. 9)
Prerequisite: permission of supervisor.

IND E 600 Independent Study or Research (*-)

IND E 700 Master's Thesis (*-)

IND E 800 Doctoral Dissertation (*-)