MATLS 3J03 - Statistical Methods for Materials Engineers - Design of Experiments - Materials Science or Chemistry - Statistics Assessment Answer

Assessment Task:

MATLS3J03: Statistical Methods for Materials Engineers Assessment Answer

Intention
This DOE (design of experiments) mini-project gives you an opportunity to learn about designed experiments in a more hands-on manner. The project is not long, and should not be elaborate. You only have a few weeks to plan your experiments, perform them and then analyze the data. Some examples are given below, but you are free to choose any topic like optimizing a favourite recipe or dessert, a hobby or sport, or it could be related to work from another course project.

The intention is that you discover for yourself how important the following topics are in DOE. Once you have decided on a system to investigate you will be faced with questions such as:

• Which variables should we use?

• What range should these variables cover?

• How do we measure these variables (especially the response/y variable)?

• What other variability is in the system, is it measurable, and is it controllable?

• Choosing the type of experimental design (full factorial, fractional factorial), confounding pattern, and handling constraints.

• How many experiments should be run, are replicates and/or center points possible, and how to randomize the runs.

• Understand what George Box means when he says: "the best time to run an experiment is after the experiment". These are issues that are not easily reproduced or understood from assignment questions and exams.

Project topics
You might be passionate about a hobby, or cooking, or sports, or a research area, etc., so coming up with a system to investigate shouldn't be a problem. However, some systems are too complex for the short time you have available, and you might have to cut back to something simpler. Below are some ideas that you can think about and modify, but please work on anything you are interested in, or anything you have ever wondered about. Don't pick a project below that "looks easy": the “easy” ones are deceptive.

• Yield of stovetop popcorn or microwave popcorn

• Rise height of bread

• Algae growth in an aquarium

• Fuel efficiency (gas mileage) of a car

• The perfect meringue from egg-whites

• Taste of pancakes (average of tasters)

• Time taken to do 4 runs on a half-pipe

• Factors related to seed germination and growth (e.g. does Miracle-Gro work?)

• Taste of home-made yogurt

• Best-tasting drink (I take no responsibility for the results of this experiment!)

• Taste of preparing prepackaged foods

• Foam produced when pouring (soft) drinks into a glass

• Strength of wood glue bond

• Stain removal from clothes

• Flight time of a paper plane

• Shot distance of tabletop hockey puck

• Factors related to paper towel absorbency, cost, softness, strength

• Burst time of soap bubbles

• Bounce height of tennis balls or golf balls

If you want a topic more specific to Materials Science or Chemistry, you might choose to use a lab from another course, or maybe one of your other courses overlaps in some way. You may even have an industrial partner from a co-op with whom you can work (be very careful as time constraints are usually too difficult to achieve).
Note that topics involving cooking and baking can be the most complex due to raw material variability and subjectivity of the outcome variable(s). However, if this is an area that you/your group are interested in, please try the following:

• Replace subjective measurements of taste with something more measurable, e.g. height of muffin, diameter of cookie, pH, or similar.

• Use recipes that are based on weight; recipes and cookbooks that are based on volume for dry ingredients (cups and teaspoons) are inherently flawed and will introduce disturbances (error).

• Some y-variables such as "doneness" or "time to cook" or "firmness" are extremely subjective and hard to measure; there are ways around it in professional laboratories, but you won't have access to this sort of equipment.

• Professional taste-testers are trained for months; rather than just a taste number between 0 and 10, break it down into components: acidity, sweetness, mouth feel (texture), crispiness, ''etc'', and add up the values to get a composite taste score.

• Rather than just using average taste score as your response, also analyze the standard deviation of your taster's scores, to find the most robust, and pleasing recipe combination.

Finally, the system under investigation can be anything; however, you cannot merely copy-paste a problem that you found in a book, technical journal, website, a previous student’s experiment, or some other resource. You must be able to prove you planned and performed the experiment yourself; this means that you cannot re-use experimental data from a previous course project. If you are going to investigate a relatively simple system, such as dissolving salt in water, then ensure that your project is at the level of a 3 rd year university project, is comprehensive, and covers many factors. In general the number of experiments, the cost, and the complexity of the experiments should be inversely proportional to the duration of each experiment. If you have any ethical doubts (e.g. experiments on animals or people, or experiments with drugs and controlled substances) then choose another system.

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