EIND - Industrial Engineering

EIND 101  Introduction to Industrial & Management Systems Engineering: 1 Credits (1 Lec)

(F) Overview of the profession including the breadth of career opportunities available to Industrial and Management Systems Engineers. Course focuses on common tools and methods of Industrial and Management System Engineering, how those tools are utilized to improve outcomes for organizations in many sectors of the economy, and the benefits to society from these applications.

View Course Outcomes:

  1. Define the role of Industrial and Management Systems Engineers (IMSEs) in a variety of settings.
  2. Identify ways that IMSEs create value for their organizations.
  3. Apply simple tools from the IMSE toolkit to design process improvements.
  4. Summarize the varied career options available to IMSEs
  5. Explain the importance of career management and design a plan for lifelong learning.

EIND 142  Introduction to Systems Engineering: 2 Credits (1 Lec, 1 Lab)

(Sp) Introduces students to the importance of systems thinking including recognizing systems and understanding how they function and interact. Includes exploring the role of Industrial and Management Systems Engineers in analyzing, designing, and managing human-centered systems. Labs provide hands on opportunities for this exploration. Emphasis on contemporary topics including automation and sustainability.

View Course Outcomes:

  1. Describe systems thinking. Solve problems using systems thinking.
  2. Recognize the complexity of our own relationships with systems.
  3. Explain different ways to change systems.
  4. Define Industrial and Management Systems Engineering.
  5. Write technical memos applying course concepts.

EIND 290R  Undergraduate Research: 1-6 Credits (1-6 Other)

(F, Sp, Su) Directed undergraduate research which may culminate in a written work or other creative project. Course will address responsible conduct of research. May be repeated.
Repeatable up to 99 credits.

EIND 291  Special Topics: 1-4 Credits (1 Lec)

PREREQUISITE: None required but some may be determined necessary by each offering department. On demand. Courses not required in any curriculum for which there is a particular one-time need, or given on a trial basis to determine acceptability and demand before requesting a regular course number
Repeatable up to 12 credits.

EIND 300  Engineering Management & Ethics: 3 Credits (1 Lec, 2 Other)

PREREQUISITE: WRIT 101W and COMX 111US and Junior standing. (F) Introduction to management, leadership and organizational theory with applications to the engineering profession. Communication skills, social responsibility and ethical decision making for managers and engineers emphasized throughout. Cases and class exercises used to illustrate contemporary problems and environments

View Course Outcomes:

  1. Summarize the role of managers in organizations.
  2. Interpret and apply management theory to the engineering context.
  3. Illustrate the implications of organizational structures within an engineering function.
  4. Apply social responsibility and ethical frameworks to engineering decision making.
  5. Summarize the fundamentals of leadership within the role of the engineering manager.
  6. Explain the importance of career management and design a plan for lifelong learning.
  7. Determine the impact of managers in a global, economic, environmental, and societal context.
  8. Effectively apply the course concepts in oral and written communications.

EIND 313  Work Design and Analysis: 3 Credits (2 Lec, 1 Lab)

PREREQUISITE: WRIT 101W and EIND 142 for IMSE majors, Instructor permission for non-IMSE majors. (Sp) Covers analysis and design methods for occupational tasks to improve productivity, workplace health, and safety. Topic areas include fundamental aspects of work standards development, ergonomics, and industrial safety. The labs demonstrate example applications of these topic areas

View Course Outcomes:

  1. Apply the basic principles of work design, ergonomics, and occupational health and safety to improve work processes in terms of efficiency, comfort, and safety.
  2. Develop and establish appropriate work standards.
  3. Perform technical writing and documentation to demonstrate comprehension of material and laboratory exercises.

EIND 354  Engineering Probability and Statistics I: 3 Credits (3 Lec)

PREREQUISITE: M 172, Junior standing, or consent of instructor. (F) Understanding the statistical nature of engineering processes. Emphasis on proper data collection and classification, characteristics of variables and their distributions, joint probability distributions, and establishing hypotheses and statistical significance over engineering design specifications

View Course Outcomes:

  1. Define basic Probability Concepts and apply these concepts to decision making.
  2. Utilize Descriptive Statistics for engineering design and decision making.
  3. Make decisions about a population using Inferential Statistics, including hypothesis testing for parametric and non-parametric populations.

EIND 364  Principles of Operations Research I: 3 Credits (3 Lec)

PREREQUISITE: M 221. (F) Formulation of models and optimization techniques to facilitate engineering management decisions. Resource allocation, transportation and multiple goals via networks, linear, and integer programming with primal-dual emphasis

View Course Outcomes:

  1. Explain the history and development of techniques and algorithms in operations research (OR)
  2. Formulate linear programming (LP) problems, solve those problems using different techniques, and analyze the sensitivity of the solutions
  3. Formulate and solve the dual problem of a basic LP problem
  4. Formulate, analyze, and solve transportation problems, transshipment problems, assignment problems, and network models
  5. Apply other topics in OR such as queuing and decision theory and solve problems
  6. Use different hands-on software tools in solving/analyzing problems based on (1) to (5) above

EIND 371  Introduction to Computer Integrated Manufacturing: 3 Credits (2 Lec, 1 Lab)

PREREQUISITE: ETME 215 or consent of instructor. (F) Introduces core concepts of computer controlled manufacturing systems and their applications. Topics include fundamentals of automation, programmable logic controllers, numerical control, industrial robotics, material handling and storage, and flexible manufacturing systems. Laboratories require students to apply course concepts in solving simulated industrial problems, and implement hardware-software solutions to meet stated objectives

View Course Outcomes:

  1. Introduce students to fundamental concepts related to modern computer integrated manufacturing technology.
  2. Give students hands-on experience implementing solutions in several core technologies to achieve specific objectives.
  3. Sharpen critical thinking and problem-solving skills through implementation and validation of proposed solutions to open-ended problems.

EIND 373  Production Inventory Cost Analysis: 3 Credits (3 Lec)

PREREQUISITE: M 161Q, M 165Q, or M 171Q. (Sp) This course is designed to give the engineering student an overview of the accounting processes used in service and manufacturing businesses today, including financial and managerial accounting practices. Understanding topics such as cost analysis of manufacturing processes; budgeting; break-even analysis; financial statement analysis; and internal controls supports engineers when making product design and product line decisions

View Course Outcomes:

  1. Describe the accounting processes of a service, merchandising and manufacturing business.
  2. Explain the relationship between assets, liabilities and equity.
  3. Describe the budgeting process of a business.
  4. Perform break-even analysis, financial statement analysis.
  5. Use accounting information to perform engineering job functions.

EIND 410  Interaction Design: 2 Credits (2 Lec)

PREREQUISITE: EIND 313 or EGEN 310R or consent of instructor. (Sp) This course focuses on the human-centered design process for products, services, and systems. It emphasizes the need to understand the needs, capabilities, and emotions of the user to produce designs that are not only usable and useful, but also desirable. Emphasis is placed on innovation in design to create enjoyable (fun) user experiences

View Course Outcomes:

  1. Upon completion of this course, students will be able to: Define interaction design.
  2. Describe the user-centered design process.
  3. Discuss attributes of effective interaction design.
  4. Justify the need for emotion and not just usability.

EIND 411  Interaction Design Project: 1 Credits (1 Other)

COREQUISITE: EIND 410. (Sp) A team-based project based on knowledge and skills introduced in EIND 410 to develop a design concept for a product, service, or system to address issues of social justice

View Course Outcomes:

  1. apply EIND 410 course knowledge to develop a product concept
  2. follow a rationale design process
  3. advocate (justify) a design solution

EIND 413  Ergonomics & Human Factors Engineering: 3 Credits (2 Lec, 1 Lab)

PREREQUISITE: EGEN 205 or KIN 322; EIND 313 for IMSE majors; or consent of instructor. (F) Applications of ergonomics and human factors engineering. Topics include principles of anthropometrics, biomechanics, bioinstrumentation, physiology, design error, design for special populations (e.g., those with disabilities), mental stress/workload, and risk assessment methods for work applied to common problems faced by engineers. Emphasis on design and analysis of occupational systems and consumer products which best "fit" job tasks or user requirements to human capabilities

View Course Outcomes:

  1. Understand the principles and applications of ergonomics and human factors.
  2. Understand the relevance of ergonomics and human factors in the practice of engineering.
  3. Apply ergonomics and human factors tools and concepts introduced in class to industrial and office work environments.

EIND 415  Smart Manufacturing: 3 Credits (2 Lec, 1 Lab)

PREREQUISITE: ETME 215 and CSCI 127 or ETME 202 or EMEC 203 or consent of instructor. (Sp) This course will introduce key enabling technologies that make manufacturing operations ‘smart’. It introduces some of the key concepts and fundamental knowledge necessary to implement ‘smart manufacturing’ within factory floors. This includes sensor technology, IoT architecture, and machine learning. Various sensors will be used to collect real-time manufacturing data, which will be streamed and stored via IoT architecture. Common machine learning algorithms will be implemented to realize various smart manufacturing applications

View Course Outcomes:

  1. Explain key enabling technologies in a smart manufacturing factory
  2. Identify and select appropriate sensors commonly used in smart manufacturing systems
  3. Demonstrate the usage of various industrial communication protocols in digital manufacturing
  4. Demonstrate the usage of databases that capture real-time sensing data from devices
  5. Implement various machine learning algorithms using Python programming
  6. Apply machine learning algorithms in various smart manufacturing applications

EIND 422  Introduction to Simulation: 3 Credits (3 Lec)

PREREQUISITE: CSCI 127 or equivalent, and EIND 354 or equivalent. (F, Su) Discrete simulation modeling methodology; sampling, output analysis, validation, and verification; application to varied systems design and analysis problems

View Course Outcomes:

  1. Understand and apply general systems models, Littles Law, and other “intuitive" systems principles.
  2. Apply statistical concepts to simulation model development and output analysis.
  3. Gain an appreciation of the importance of variability effects on dynamic systems' behavior.
  4. Analyze simulation input data.
  5. Develop and practice model verification and validation skills.
  6. Apply and refine statistical output analysis methods.
  7. Interact with others during model walkthroughs and class team project.
  8. Solve open-ended problems with an emphasis on real modeling objectives.
  9. Assess the sensitivity of design parameters and other inputs on system performance.
  10. Identify important system features for design and decision making.
  11. Build a sense of responsibility by meeting deadlines, collaborating without plagiarism or "division of labor", and accurately reporting model results and recommendations to "client."
  12. Better use the computer as a problem-solving tool.

EIND 425  Technology Entrepreneurship: 3 Credits (3 Lec)

PREREQUISITE: EGEN 325 or EGEN 330 or equivalent. (F) The purpose of this course is to Introduce students to the principles of entrepreneurship and give them the background appropriate to start their own business. The course utilizes the Lean Launch Pad approach to evaluating a concept value in the market. Building business models and understanding the market opportunity are key aspects of this course. Multiple case studies are developed and presented by the students. Multiple guest lectures by entrepreneurial leaders augments the course learning

View Course Outcomes:

  1. Understand entrepreneurship and the entrepreneurial process and the challenges of launching and operating a technology venture.
  2. Understand intellectual property development and management.
  3. Understand valuation, deal structuring, and equity preservation issues.
  4. Address the issue of leading, managing, motivating and compensating technical workers.
  5. Understand the fundamentals of marketing and selling in an entrepreneurial environment.
  6. Understand the role of entrepreneurship and new venture creation in economic development.
  7. Understand the role and activities of entrepreneurship in a global setting.
  8. Evaluate your own entrepreneurial tendencies and create a new venture.
  9. Understand the concepts of Lean Startup, Business Model Canvas and the Customer Development Process.
  10. Complete a business model analysis of a product/service concept.

EIND 434  Project Management for Engineers: 3 Credits (3 Lec)

PREREQUISITE: Junior standing. (F) Fundamental principles of planning, estimating, budgeting, scheduling, implementing, evaluating, and controlling engineering and research projects. Common engineering management concerns such as labor scheduling, human resource management, international impacts, agile project management approaches, and related governmental compliance are also explored. These principles are practiced through several projects throughout the semester

View Course Outcomes:

  1. Explain what project management is and identify key roles in project based organizations.
  2. Differentiate between successful and unsuccessful project management applications.
  3. Describe how project management is influenced by an organization.
  4. Apply fundamental project management tools (e.g. planning and scheduling techniques, cost control, etc.) to successfully solve text based homework exercises.
  5. Identify key issues in open ended project management problems, discover what tools are needed to solve those problems and utilize needed tools to develop solutions to the problems.
  6. Compose solutions to case study problems in project management using course concepts.
  7. Effectively apply the course concepts in oral and written communications.
  8. Construct Project Management Plans for 3 separate projects.

EIND 442  Facility and Material Handling Systems Design: 3 Credits (3 Lec)

PREREQUISITE: EIND 313, EMEC 103, ETME 215
COREQUISITE: EIND 300. (F) IMSE seniors in their last 3 semesters. The first course in the senior capstone sequence. Principles and techniques for planning and designing production facilities and material handling systems. Product and process analysis, requirements, layout and support facilities. Computer-aided analysis and design
.

View Course Outcomes:

  1. Students should be able to articulate systematic procedures for facilities planning and the corresponding design steps.
  2. Analyze complex process flows using engineering tools and approaches.
  3. Generate alternative solutions to different types of facility layout problems,\\nand evaluate those alternatives.
  4. Apply the principle of unit load in facility layout design.
  5. Identify appropriate material handling solutions for a given application.
  6. Acquire new knowledge and apply it to a problem on which they’re\\nworking.

EIND 454  Engr Probability and Stats II: 3 Credits (3 Lec)

PREREQUISITE: EIND 354. () Offered on demand. Identification, characterization, and analysis of variation in engineering data. Includes inferential statistics, goodness of fit, applications of non-parametric statistics, curve fitting, regression, and the design of engineering experiments. A team design project is required

View Course Outcomes:

  1. Applying Hypothesis Testing for engineering decision making.
  2. Solving single and multivariate problems through Single and Multiple Regression
  3. Designing solutions to engineering problems through Analysis of Variance and Design of Experiments techniques.

EIND 455  Design of Experiments for Engineers: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 or consent of instructor. (Sp) Odd years. Statistical analysis for managerial decision-making as applied to engineering problems. Single and multi-factor ANOVA, randomized complete, full-blown and fractional designs with blocking and confounding. Introductions to nested and split-plot designs, multiple regression and response surface designs

View Course Outcomes:

  1. Explain how to decompose a real world problem and develop a list of data\\nneeded to solve that problem.
  2. Plan how to acquire and work with data in order to solve engineering\\nproblems.
  3. Plan how to solve engineering problems utilizing single factor\\nexperiments.
  4. Identify critical factors in system performance utilizing various DOE\\ntechniques.
  5. Recommend specific ways to improve processes through application of\\nmultifactor factorial experiments.
  6. Recommend efficient ways to reduce data needs in engineering problem\\nsolving through application of fractional factorial and other experimental\\ndesigns.
  7. Explain how response surface techniques and other advanced DOE related\\ntools can aid in process optimization.

EIND 457  Regres & Multivar Analysis: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 or consent of instructor. (Sp) Even years. Advanced topics in applied statistical analysis for engineers. Topics include regression techniques: ANOVA, simple linear regression, multiple linear regression, and variable selection procedures; and multivariate analysis techniques: principal components, factor analysis, canonical correlation analysis, and clustering methods. Statistical analysis for managerial decision-making as applied to engineering problems

View Course Outcomes:

  1. Develop and analyze single variable regression models.
  2. Develop and analyze multiple variable regression models.
  3. Analyze single factor experiments using ANOVA techniques.
  4. Apply DOE techniques.
  5. Apply and analyze multivariate techniques such as MANOVA, factor analysis,\\nprincipal components, linear discriminant and clustering methods.

EIND 458  Production & Engineering Mgmt: 3 Credits (3 Lec)

COREQUISITE: EIND 464 or consent of instructor. (Sp) Design and management of efficient production/delivery systems for goods and services, emphasizing quantitative analysis and systems approaches. Topics include forecasting, inventory management, production planning, scheduling, material planning, and lean manufacturing systems

View Course Outcomes:

  1. Effectively design and manage a production system.
  2. Estimate total inventory costs for a given lot size when demand rate,\\nholding costs, and setup costs are known; and describe the sensitivity of\\ncost to changes in holding costs, setup costs, demand, and order quantity.
  3. Set appropriate safety stock levels and reorder points given demand and/or\\nlead time fluctuation to meet a given overall service level.
  4. Identify the key inputs to a material requirements planning (MRP) system.
  5. Create a current state Value Stream Map of a production line depicting the\\npertinent material and information flows, process steps, inventories, and\\nvalue time-line.
  6. Describe the Toyota Production System.
  7. Create a future state Value Stream Map that incorporates the above\\nconcepts to create a substantially improved production system.
  8. Understand and apply general systems models, Littles Law, and other\\n“intuitive" systems principles.
  9. Understand the difference between Push and Pull Systems and between\\nmake-to-order and make-to-stock systems.
  10. Understand dynamics of manufacturing systems.
  11. Understand the effects of variability in operations and identify the sources\\nof process time variability and flow rate variability.
  12. Define the central concepts of cycle time, throughput, WIP, capacity, and\\nutilization.
  13. Given a description of a production process, estimate key performance\\ncharacteristics such as throughput, capacity, station and worker utilization,\\ncycle times, minimum average queue sizes.

EIND 464  Prin of Operations Research II: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 and EIND 364. (Sp) Advanced formulation of models, optimization techniques and application to engineering design and operations management decision making. Integer programming algorithms. Stochastic models including advanced queuing and general Markov processes

View Course Outcomes:

  1. Model deterministic and stochastic processes.
  2. Apply principles of Operations Research to solve practical problems.
  3. Model and solve problems related to network models, integer programming, dynamic programming, Markov chains.
  4. Understand and apply the concepts of queuing theory in any system.
  5. Solve optimization problems with multiple objectives.
  6. Make decisions in the presence of uncertainty.

EIND 468  Managerial Forecasting & Decision Analysis: 3 Credits (3 Lec)

PREREQUISITE: EIND 354. (F) Time series analysis through classical approaches; auto-regression, smoothing models, and advanced time series models. Technical applications emphasized. Includes investigations into financial and dependent data. Approaches designed for managers to test real applications for making decisions

View Course Outcomes:

  1. Describe how forecasting tools are used to solve engineering problems in the financial and big data domains.
  2. Select and apply the proper forecasting tool to generate useful models for a variety of data sets.
  3. Utilize a variety of forecasting tools to solve engineering problems with a focus on financial applications.
  4. Judge the effectiveness of forecasting models and assess model adequacy.
  5. Evaluate the risks in a forecasting model and develop plans to deal with this uncertainty.
  6. Explain the best way to organize a forecasting process for a variety of business applications.
  7. Utilize SQL based software to import, manage, and explore data.

EIND 477  Applied Statistical Quality Control: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 or EGEN 350 or consent of instructor. (Sp) Introduction to statistical methods for quality control and improvement, including statistical modeling and inferences, control charts, process and measurement system capability analysis, and engineering process control. This course extensively utilizes computer programming to enable students to implement quality control techniques in a production environment

View Course Outcomes:

  1. Critique various approaches to quality control and improvement.
  2. Acquire and work with data in order to solve quality problems.
  3. Solve quality control and improvement problems using various statistical methods.
  4. Apply control charts and other tools to ensure that improvements are maintained.
  5. Use computer programming to do analytical and descriptive statistics in quality control and improvement problems.

EIND 490R  Undergrad Research: 1-6 Credits (1-6 Other)

PREREQUISITE: Junior standing, consent of instructor, and approval of certifying officer. (F, Sp, Su) Directed undergraduate research/creative activity which may culminate in a research paper, journal article, or undergraduate thesis. Course will address responsible conduct of research. May be repeated
Repeatable up to 6 credits.

View Course Outcomes:

  1. Independent Study

EIND 491  Special Topics: 1-4 Credits (1 Lec)

PREREQUISITE: Course prerequisites as determined for each offering. On demand. Courses not required in any curriculum for which there is a particular one-time need, or given on a trial basis to determine acceptability and demand before requesting a regular course number
Repeatable up to 12 credits.

EIND 492  Independent Study: 1-6 Credits (1-6 Other)

PREREQUISITE: Junior standing, consent of instructor, and approval of department head or director. (F, Sp, Su) Directed research and study on an individual basis
Repeatable up to 6 credits.

View Course Outcomes:

  1. Independent Study

EIND 499R  Industrial Engineering Design Capstone: 3 Credits (1 Lec, 2 Other)

PREREQUISITE: EGEN 310R, EGEN 325, EIND 434 and EIND 442
COREQUISITE: EIND 458. (Sp) Second course in senior capstone sequence. An open-ended team design project emphasizing the application of industrial engineering tools and knowledge to create engineered solutions for real business needs or opportunities. Experiential learning, oral and written communication and project management emphasized
.

View Course Outcomes:

  1. Act as thinkers and problem solvers to construct and execute an appropriate research process in order to solve an open-ended problem in the Industrial and Management Systems Engineering domain and meet a set of client needs.
  2. Integrate tools and concepts from multiple industrial and management systems arenas, and apply them to a real-world situation.
  3. Develop and deliver new knowledge to clients that improves their business operations or systems.
  4. Contribute as a citizen by demonstrating skills in interacting professionally with clients and team members through improved understanding of teamwork and collaboration.
  5. Demonstrate effective communication skills with clients, team members, and the general public.
  6. Apply project planning, tracking and control concepts and tools to a live project, and actively manage it.

EIND 500  Engineering Organizational Change and Innovation: 3 Credits (1 Lec, 2 Other)

PREREQUISITE: EIND 300 or EIND 574 or consent of instructor. (F) Advanced topics in organizational change and innovation from an engineering perspective. Emphasis placed on understanding the need for change, systems thinking, the role of culture and leadership, and ethical approaches to change. The differing role of employees and management in innovation and implementing engineering process improvement are examined

View Course Outcomes:

  1. Understand the principles of systems thinking and apply them to problems of organizational change.
  2. Understand and use Senge’s System Archetypes to problems of organizational change and innovation.
  3. Identify the elements that drive needs for organizational change and engineering’s role in change.
  4. Understand how to plan for organizational change in a variety of circumstances.
  5. Successfully analyze organizational cases to identify needs for change and apply principles of change management to develop change plans for engineering and technical organizations.
  6. Identify ways to understand and measure organizational culture
  7. Identify ways to work with elements of organizational culture to ensure that change is maintained.
  8. Identify the role of engineers in organizational innovation and how innovation is an impetus for change.
  9. Effectively apply course concepts in oral and written communications.

EIND 506  Healthcare Delivery Systems: 3 Credits (3 Lec)

PREREQUISITE: EIND 458 or NRSG 604 or consent of instructor. (Offered Fall, even years.) Offered Spring, even years. This interdisciplinary course targets nursing students pursuing certification as a Clinical Nurse Leader and Industrial Engineering students who intend to work in the healthcare sector. Students will learn strategies for analyzing and improving processes, coordinating interdisciplinary healthcare teams, enhancing healthcare quality management, and reducing health risk through medical error elimination

View Course Outcomes:

  1. Examine the roles of the Clinical Nurse Leader, Doctor of Nursing Practice and Industrial Engineer as each relates to organizational leadership, effective advocacy, and the delivery and integration of care.
  2. Evaluate core hospital systems which drive the quality, timeliness, and cost of care using systems engineering concepts and tools.
  3. Examine issues related to coordinating and leading healthcare teams in collaborative problem solving.
  4. Assess internal and external forces including cultural factors that affect healthcare delivery across various settings.
  5. Compare quality, risk management, and patient safety strategies among select client populations.

EIND 509  Systems Simulation: 3 Credits (3 Lec)

PREREQUISITE: CSCI 127 and EIND 354; or consent of instructor. () Offered Fall, odd years. Systems exhibiting randomness are modeled and statistically analyzed using a state-of-the-art simulation language. Graphical model animation, and advanced output analysis are emphasized. Applications include improvement of existing and design of new production and service systems

View Course Outcomes:

  1. Students will know: Applications and limitations of discrete event simulation.
  2. Mechanisms used for simulation state description, time advance and event scheduling.
  3. Designing and programming simulation models using a simulation language.
  4. Selecting an appropriate distribution for sample data and calculation of goodness of fit.
  5. Identification and correction of errors in simulation models.
    Analysis of simulation output data and calculation of confidence intervals on system performance.
  6. Statistical comparisons of multiple systems.
  7. Design of experiments using simulation.

EIND 510  Usability and Inclusive Design: 3 Credits (3 Lec)

PREREQUISITE: EIND 410 or EGEN 310R or consent of instructor. () Offered Fall, odd years. Explores usability engineering and usability testing in the design of human centered systems. Focus is given to the inclusive design process for developing systems to meet the needs of all users and improve social justice

View Course Outcomes:

  1. Apply usability engineering principles to the design process.
  2. Identify opportunities for usability engineering to improve the design process.
  3. Compose solutions to design problems using the tools and methods of usability engineering.
  4. Evaluate usability engineering applications across a range of product, service and system domains.

EIND 511  Advanced Human Factors: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 or EGEN 350 or consent of instructor. () Offered Spring, even years. Advanced methods applied to areas where human factors and ergonomics are critical to diverse user groups with technology and service-based systems. This seminar-based course will use case studies to examine application areas such as healthcare, aviation and transportation

View Course Outcomes:

  1. Identify the activities and deliverables expected within each phase of the product development process to include pertinent regulatory standards.
  2. Demonstrate early exploratory design methods teams utilize to identify critical user needs that filter into product requirements and design specifications.
  3. Create usability testing protocols with end users that enhance understanding of design issues. Focus on outlining options for understanding usability issues, empirical and analytical methods of usability inspection, and validation testing and best practices.
  4. Apply usability heuristics and best practice design principles to guide product development that is inherently usable and safe to use.
  5. Justify the cost of Human Factors Engineering activities through return-on-investment analysis. Understand the importance of human factors during the product development lifecycle and demonstrate cost savings.
  6. Demonstrate use of advanced human factors and statistical software tools.

EIND 513  Human Factors in Complex Systems: 3 Credits (3 Lec)

PREREQUISITE: EIND 313 or EIND 413 or consent of instructor. (Offered Spring, odd years.) Offered Spring, odd years. Focus on advanced topics in human factors engineering related to the origins of human error as causes of failure in safety-critical systems. This seminar-based course includes lab demonstrations of human cognitive functions and case studies of human error in safety critical systems

View Course Outcomes:

  1. Identify the common sources of human error in safety-critical systems.
  2. Redesign systems to be less susceptible to human error.

EIND 514  Occupational Biomechanics: 3 Credits (3 Lec)

PREREQUISITE: Knowledge of statistics (t-tests, ANOVA, regression, design of experiments); EIND 413 or consent of instructor. () Course is offered on demand. Topics relate to occupational biomechanics and bioinstrumentation application, focused on designing for the health and safety at work. Topics include the skeletal system, physiology, fatigue assessment, stress response, psychometrics, biomechanics, work design assessments and implementation of ergonomics programs

View Course Outcomes:

  1. Understand occupational biomechanics and bioinstrumentation application, focused on designing for the health and safety at work. Topics include the skeletal system, physiology, fatigue assessment, stress response, psychometrics, biomechanics, work design assessments and implementation of ergonomics programs.

EIND 525  Multi-Criteria Decision Making and Optimization: 3 Credits (3 Lec)

PREREQUISITE: EIND 364. (Fall, even years) Offered Fall, even years. Theory, methods and applications pertinent to decision making with multiple attributes and/or multiple objectives. Special emphasis is given to multi-attribute utility theory, goal programming, and multiple criteria optimization decision-making in modern manufacturing and service systems and in design decision-making to support competitive priorities of an enterprise

View Course Outcomes:

  1. Demonstrate a mastery of skills and knowledge of various multi-criteria analysis, decision making and optimization methods.
  2. Critically apply theories, methodologies and knowledge of multiple-criteria decision making methods to support optimized decision making in modern manufacturing and service systems and in design decision making.
  3. Analyze and evaluate literature relevant to multi-criteria decision making and optimization methods.
  4. Pursue research of significance in the multi-criteria decision making modeling, optimization, analytics, and applications.
  5. Apply research theories, methodologies, and disciplinary knowledge to address fundamental questions through a research project.

EIND 554  DOE for Engineers: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 or consent of instructor. () Offered Spring, odd years. Statistical analysis for managerial decision-making applied to engineering problems. Single and multi-factor ANOVA, randomized complete and fractional factorial designs with blocking and confounding. Introductions to nested and split-plot designs, multiple regression and response surface designs. -

View Course Outcomes:

  1. Explain how to decompose a real world problem and develop a list of data needed\\nto solve that problem.
  2. Plan how to acquire and work with data in order to solve engineering problems.
  3. Plan how to solve engineering problems utilizing single factor experiments.
  4. Identify critical factors in system performance utilizing various DOE techniques.
  5. Recommend specific ways to improve processes through application of multifactor factorial experiments.
  6. Recommend efficient ways to reduce data needs in engineering problem solving through application of fractional factorial and other experimental designs.
  7. Explain how response surface techniques and other advanced DOE related tools can aid in process optimization.

EIND 557  Regression & Multivar Analysis: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 or consent of instructor. () Offered Spring, even years. Advanced topics in applied statistics for engineers. Topics include regression techniques: ANOVA, simple linear regression. multiple linear regression, and variable selection procedures; and multivariate analysis techniques: principal components, factor analysis, canonical correlation analysis, and clustering methods. Statistical analysis for managerial decision-making as applied to engineering problems. This course is co-convened with EIND 457

View Course Outcomes:

  1. Develop and analyze single variable regression models.
  2. Develop and analyze multiple variable regression models.
  3. Conduct and analyze single factor experiments using ANOVA techniques.
  4. Apply and analyze multivariate techniques such as factor analysis, principal components, and clustering methods.

EIND 558  Manage Forecast & Dec Analysis: 3 Credits (3 Lec)

PREREQUISITE: EIND 354 or EIND 457. () Fall, even years. Time series analysis through classical approaches including regression, smoothing models, and advanced time series models. Technical applications emphasized in concepts, tools, and methods. Includes investigations into financial and dependent data. Approaches designed for managers to test real applications for making decisions

View Course Outcomes:

  1. Describe how forecasting tools are used to solve engineering problems in the financial and big data domains.
  2. Select and apply the proper forecasting tool to generate useful models for a variety of data sets.
  3. Utilize a variety of forecasting tools to solve engineering problems with a focus on financial applications.
  4. Judge the effectiveness of forecasting models and assess model adequacy.
  5. Evaluate the risks in a forecasting model and develop plans to deal with this uncertainty.
  6. Explain the best way to organize a forecasting process for a variety of business applications.
  7. Utilize SQL based software to import, manage, and explore data.

EIND 574  Management Engineering Systems: 3 Credits (3 Lec)

PREREQUISITE: EIND 300 or EIND 500 or consent of instructor. () Offered Spring, odd years. Explores various facets of designing effective organizational and management systems. Topics include: classical and open system organization theory, socio-technical systems theory, congruence, technology and innovation management, knowledge management, and continuous improvement in organizations. Students complete an independent research project

View Course Outcomes:

  1. Develop a working knowledge of central issues in managing technology\\norganizations.
  2. Gain in-depth knowledge in an area of interest related to technology management.
  3. Improve professional presentation, technical writing, and critical evaluation skills.

EIND 575  Research or Prof Paper/Project: 1-6 Credits (1-6 Other)

PREREQUISITE: Graduate standing. (F, Sp, Su) A research or professional paper or project dealing with a topic in the field. The topic must have been mutually agreed upon by the student, major advisor, and graduate committee
Repeatable up to 6 credits.

View Course Outcomes:

  1. Act as a thinker and problem solver to construct and execute an appropriate process in order to solve an open-ended problem in the Industrial and Management Systems domain and meet a set of client needs.
  2. Integrate tools and concepts from multiple industrial and management systems arenas, and apply them to a real-world situation.
  3. Develop and deliver new knowledge to clients that improves their business operations or systems.
  4. Contribute as a citizen by demonstrating skills in interacting professionally with clients.
  5. Demonstrate effective communication skills with clients and faculty advisor.
  6. Apply project planning, tracking and control concepts and tools to a live project, and actively manage it.

EIND 589  Graduate Consultation: 1-3 Credits (1-3 Other)

PREREQUISITE: Master's standing and approval of the Dean of Graduate Studies. (F, Sp, Su) (F,S,SU) This course may be used only by students who have completed all of their coursework (and thesis if on a thesis plan) but who need additional faculty or staff time or help
Repeatable up to 3 credits.

View Course Outcomes:

  1. Graduate consultation.

EIND 590  Master's Thesis: 1-10 Credits (1-10 Other)

PREREQUISITE: Master's standing; consent of instructor. (F, Sp, Su) Master's Thesis
Repeatable up to 99 credits.

View Course Outcomes:

  1. Master's Thesis

EIND 591  Special Topics: 1-4 Credits (1 Lec)

PREREQUISITE: Upper division courses and others as determined for each offering. On demand. Courses not required in any curriculum for which there is a particular one- time need, or given on a trial basis to determine acceptability and demand before requesting a regular course number
Repeatable up to 12 credits.

EIND 592  Independent Study: 1-3 Credits (1-3 Other)

PREREQUISITE: Graduate standing, consent of instructor, approval of department head or director. (F, Sp, Su) Directed research and study on an individual basis
Repeatable up to 6 credits.

View Course Outcomes:

  1. Independent Study

EIND 598  Internship: 1-6 Credits (1-6 Other)

PREREQUISITE: Graduate standing, consent of instructor and approval of graduate program coordinator. (F, Sp, Su) An individualized assignment arranged with an agency, business or other organization to provide guided experience in the field
Repeatable up to 12 credits.

View Course Outcomes:

  1. Internship: Student learning outcomes vary.

EIND 690  Doctoral Thesis: 1-10 Credits (1-10 Other)

PREREQUISITE: Doctoral standing; consent of instructor. (F, Sp, Su) Doctoral Thesis
Repeatable up to 99 credits.

View Course Outcomes:

  1. Doctoral Thesis