Design Decisions in Engineering (saylor.org)

Offered by Saylor.org,
Design Decisions in Engineering (saylor.org)

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.

Please note: this legacy course does not offer a certificate and may contain broken links and outdated information. Although archived, it is open for learning without registration or enrollment.
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.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Engineering Mechanics (Coursera) Coursera
Georgia Institute of Technology

Introduction to Engineering Mechanics (Coursera)

This course is an introduction to learning and applying the principles required to solve engineering mechanics problems. Concepts will be applied in this course from previous courses you have taken in basic math and physics. The course addresses the modeling and analysis of static equilibrium problems with an emphasis on real world engineering applications and problem solving.

Jun 1st 2026
5-12 Weeks
Engineering of Structures: Tension (Coursera) Coursera
Dartmouth College

Engineering of Structures: Tension (Coursera)

This course deals with tension. Tension is one of the easiest forces to understand. It is a pulling force. When we tend to pull an object, it is in tension. Different elements that resist tension in buildings are ropes, cables, and funicular forms. You will study different structures and identify what role tension plays in their designs. The first module explores tension and its importance in building structures.

Jun 8th 2026
3 Weeks
Measurement & Experimentation Laboratory (saylor.org) Saylor Academy
Saylor.org

Measurement & Experimentation Laboratory (saylor.org)

This course will serve as your introduction to working in an engineering laboratory. You will learn to gather, analyze, interpret, and explain physical measurements for simple engineering systems in which only a few factors need be considered. This experience will be crucial to your success in analyzing more complicated systems in subsequent coursework and in the practice of mechanical engineering.

Legacy Course
Self-Paced
Numerical Methods for Engineers (saylor.org) Saylor Academy
Saylor.org

Numerical Methods for Engineers (saylor.org)

Numerical methods have been used to solve mathematical expressions of engineering and scientific problems for at least 4000 years. Such methods apply numerical approximation in order to convert continuous mathematical problems (for example, determining the mechanical stress throughout a loaded truss) into systems of discrete equations that can be solved with sufficient accuracy by machine. This course will provide you with an introduction to several of those numerical methods which you may then find opportunity to practice later in the curriculum.

Legacy Course
Self-Paced
Introduction to Physical Chemistry (Coursera) Coursera
University of Manchester

Introduction to Physical Chemistry (Coursera)

Chemical reactions underpin the production of pretty much everything in our modern world. But, what is the driving force behind reactions? Why do some reactions occur over geological time scales whilst others are so fast that we need femtosecond-pulsed lasers to study them? Ultimately, what is going on at the atomic level? Discover the answers to such fundamental questions and more on this course in introductory physical chemistry.

Jun 1st 2026
5-12 Weeks
Self Awareness and the Effective Leader (Coursera) Coursera
Rice University

Self Awareness and the Effective Leader (Coursera)

Part of being an effective leader is learning how to play to your strengths and overcome characteristics that don't lend to good leadership practices. During the course, you will examine your own strengths and learn ways to use them in a leadership role. Learn to manage stress and solve problems creatively. Throughout the course, you will also build a tool kit of useful techniques that you can begin using right away in your engineering career.

Jun 8th 2026
5-12 Weeks
Quantitative Formal Modeling and Worst-Case Performance Analysis (Coursera) Coursera
EIT Digital

Quantitative Formal Modeling and Worst-Case Performance Analysis (Coursera)

Welcome to Quantitative Formal Modeling and Worst-Case Performance Analysis. In this course, you will learn about modeling and solving performance problems in a fashion popular in theoretical computer science, and generally train your abstract thinking skills. After finishing this course, you have learned to think about the behavior of systems in terms of token production and consumption, and you are able to formalize this thinking mathematically in terms of prefix orders and counting functions. You have learned about Petri-nets, about timing, and about scheduling of token consumption/production systems, and for the special class of Petri-nets known as single-rate dataflow graphs, you will know how to perform a worst-case analysis of basic performance metrics, like throughput, latency and buffering.

Jun 1st 2026
4 Weeks
Exploring Light: Hands-on Activities and Strategies for Teachers (Coursera) Coursera
Exploratorium

Exploring Light: Hands-on Activities and Strategies for Teachers (Coursera)

This is an Exploratorium teacher professional development course taught by Teacher Institute staff, open to any science teacher (particularly middle or high school level) and science enthusiast. This is a hands-on workshop that explores topics and strategies teachers can use to help their students become active investigators of light.

Jun 14th 2026
4 Weeks
Sistemas Digitales: De las puertas lógicas al procesador (Coursera) Coursera
Universitat Autònoma de Barcelona

Sistemas Digitales: De las puertas lógicas al procesador (Coursera)

En este curso aprenderemos los fundamentos del diseño de los circuitos digitales actuales, siguiendo una orientación eminentemente práctica. A diferencia de otros cursos más "clásicos" de Circuitos Digitales, nuestro interés se centrará más en el Sistema que en la Electrónica que lo sustenta. Este enfoque nos permitirá sentar las bases del diseño de Sistemas Digitales complejos.

Jun 8th 2026
5-12 Weeks
Engineering Practices for Building Quality Software (Coursera) Coursera
University of Minnesota

Engineering Practices for Building Quality Software (Coursera)

Agile embraces change which means that team should be able to effectively make changes to the system as team learns about users and market. To be good at effectively making changes to the system, teams need to have engineering rigor and excellence else embracing change becomes very painful and expensive. In this course, you will learn about engineering practices and processes that agile and traditional teams use to make sure the team is prepared for change. In additional, you will also learn about practices, techniques and processes that can help team build high quality software. You will also learn how to calculate a variety of quantitative metrics related to software quality.

Jun 8th 2026
4 Weeks