Engineering design is the process of creating solutions to satisfy certain requirements given all the constraints. This course will focus on the decision-making process that affects various stages of design, including resource allocation, scheduling, facilities management, material procurement, inspection, and quality control. You will be introduced to the basic theoretical framework and several practical tools you can use to support decision making in the future. The first two units provide an overview of engineering design process and theories and methods for making decisions, including Analytic Hierarchy Process, Lean Six Sigma, and Quality Function Deployment. In Unit 3, you will learn about the basic principles of computerized decision support systems. Unit 4 discusses several advanced mathematical methods used for support decision making, including linear and dynamic programming, decision tree, and Bayesian inference.
Upon successful completion of this course, the student will be able to:
- Make decisions given one or more design constraints.
- Explain and use different techniques such as Pugh Method, Quality Function Deployment, Decision Matrix, and Analytic Hierarchy Processto obtain inputs from key stakeholders.
- Explain the principles of and apply methods and tools such as Lean Six Sigma to address variability, quality, and uncertainty.
- Use mathematical tools such as linear programming, dynamic programming, probability analysis, and decision tree in decision making.
- Use decision support systems (DSS) in application to solve complex engineering design problems under conflicting objectives and uncertainty.
- Evaluate the implications of economic considerations on design decisions.
More info: http://www.saylor.org/courses/me402/