Online Master of Engineering Management

The objective of this course is to teach engineers the management skills they will need to be effective throughout their careers.It introduces the ways in which management principles are applied in the kinds of work students are most likely to encounter.Also included are aspects of globalization, including how culture changes engineering management.

This course is designed to help you develop the ability to think critically as a professional communicator.Learning to ask appropriate questions will enable you to understand, develop, and produce effective communication using the following elements of thought: purpose, basic concepts, information sources and needs, underlying assumptions, inferences/conclusions, implications/consequences, and points of view.Significant ethics discussions are included throughout this course.

This course is intended to prepare engineering management students to design statistically valid experiments and to analyze the results. Topics include basic probability theory, confidence intervals, hypothesis testing, regression, and analysis of variance.

This course introduces students to information systems within and across organizations.Information systems provide a primary source of information for management.Students learn about the phases of design and implementation of information systems, as well as methods for keeping abreast of fast-paced changes in the IT world.

This course integrates project management processes, knowledge areas and techniques defined in the Project Management Body of Knowledge (PMBOK) to describe the organizing, initiating, planning and performing of projects. Each PM uses many tools and understandings that come from quality, communications, and leadership principles. Project planning software and network scheduling techniques such as PERT and CPM are included, and students apply their knowledge to a real-world project of their selection.

Principles and techniques of accounting, finance, performance measures and decision-making are examined and applied in the engineering management context. Methods of cost accounting are presented, compared and used. Relationships between cost, volume and profit are illustrated, and related parameters are calculated. Budgets for production, direct labor, manufacturing and other functions are prepared. Performance measures are analyzed and applied. Differential analysis techniques are used to support engineering management decisions. Financial statements and statements of cash flows are examined and interpreted to assess the financial health of engineering organization

This course presents an introduction to the Six Sigma DMAIC problem-solving methodology, including examples in a wide range of organizations.Topics include tools and techniques for product and process improvement, and the application of basic and advanced statistics to problem solving.

This course focuses on the concepts, philosophies and frameworks of quality management; incorporating quality into strategic planning; leadership, process measurement and management; continuous quality improvement and ISO 9000. Contributions by major figures in the quality movement, such as Deming, Juran, Taguchi, and others are discussed.

This course presents methods and procedures for storing and retrieving manufacturing data in large computerized databases.It also covers the entity relationship modeling of database systems using common notation. Topics include database design, normalization, and SQL. Students will build a database using MS Access as a project.

This course focuses on the study of those parts of the legal system that relate to engineering.Topics include domestic and international environments of intellectual property policy (including patents, trademarks, copyrights, and trade secrets); torts and various sources of personal, facility, products, and enterprise liability; contracts and issues arising from various types of contractual relationships; and aspects of administrative law (dealing with agencies) and employment law.

In this course students learn modern methods for data analysis and predictive analytics. Students gain the knowledge to develop advanced queries and apply statistical methods and machine learning to analyze the data and make predictions in the engineering management context.

The objective of this course is for students to learn tools for applying lean thinking, lean principles and lean methods in manufacturing and service systems. Students will learn basic methods of the lean production, such as value-stream mapping, 5(6)-S, continuous flow, Kanban, SMED, A3, continuous improvement. The methods will be learned by practicing them in group discussions and in projects. Upon completion of the course, students will possess skills to apply lean methods in their working environments.

This course will provide information, experiences and skill development to aid the student in creating an inventory of leadership knowledge for lifelong development of effective leadership abilities. Students will accomplish this through selected readings, supplemental videos, interviews of experienced leaders, reflections and discussions to explore, develop, and reinforce leadership development.

Students are required to work on a project of their choice in this capstone course. Though not mandatory, they are encouraged to select a real-world engineering problem they are facing in their job. Students will report on their project problems, solutions, analyses, results, discussions, and conclusions.