This resource is explicitly designed to build towards this science and engineering practice.
Comments about Including the Science and Engineering Practice
A Pugh Matrix provides for weighting of the design criteria. There are several ways to do that. In this article the author suggests applying a multiplier from 1 to 5 to each criteria/constraint factor (see pg. 9. This weighting results in setting up priorities for which criteria are the most important in the design, and the designs best addressing those criteria thus receive more points. As another way to prioritize, instead of scoring each proposed on each design criteria with a ++, +, Same, -, or --, students (or the class or group) could give each design a numerical score. So, if an important criterion is safety, each design could be given a score from 1 to 5 on safety. Being out of 5 possible points shows it's an important criterion. If a less important criterion is cost, each design could be given a score from 1 to 3 points on cost, so with less possible points attributed for cost to the overall score, it would not be as prioritized. While prioritizing criteria and reviewing design performance in relation to these criteria are part of the Pugh Matrix process, optimization encompasses a bit more. In a lesson it will be important to emphasize the process of testing, revising and re-testing that would feed into the review of the performance of different designs in relation to criteria. The optimization process should likely also include selecting elements of various designs based on which better addresses different criteria and constraints. In the end, the design chosen may not be the one suggested by the Pugh Matrix due to other factors that come into play, such as a client just liking a design better. Notably, this article doesn’t address making tradeoffs, testing, revising, and retesting within the optimization process. Teachers should explicitly connect the Pugh Matrix process to results of testing competing design solutions, including test results as one of the design parameters incorporated in the matrix as appropriate. As solutions are revised and retested, new results would likewise be incorporated into this matrix. Tradeoffs will often come into play as a design is selected that scores well on some design criteria but not as well on others. A Pugh Matrix can thus inform reasoning for making tradeoffs.
This resource is explicitly designed to build towards this science and engineering practice.
Comments about Including the Science and Engineering Practice
The foundation for using a Pugh Matrix is to specify the criteria for a successful solution. This article does not emphasize the use of constraints in this process; however, whether or not a design meets necessary constraints might not always have a definite yes/no answer and could be weighted as well in this decision making process. This article doesn't come out and specify the use of this process for “real-world” problems because it's written for engineers and for educators who are going through actual design work related to real problems.