Wednesday, October 11, 2017

63s Analytics


Waste

The data we are looking to aim for would be product waste, waste management, and waste management efficiency. Knowing the layout and operation at 63s, we see that trying to discover the consumer perspective on the leftover food that is discarded and how it is discarded from this food resource on campus.




Strategy

Waste food will be collected instead of taking to kitchen cleaners, will be emptied into bucket and weighed to see the amount of food wasted over the course of an hour. Data will be collected periodically every 5 minutes. We will be collecting data on weight of the food, used plates, and people over time.



9 comments:

  1. Good start but you are missing steps 3-5 on your blog, as well as the hypothetical plot from step 2.

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  2. Do you think if you conducted this trial on a different day the results would be any different? (ie. different food that people may not like as much might produce more waste)

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    Replies
    1. I think definitely on a friday night if we did this experiment there would be less food waste because 63's is usually always empty on friday nights and the mahogany room is not open so there is less room to sit.

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  3. What days do you think that are most waste heavy.

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    Replies
    1. I'd say Mon-Thurs around dinnertime would have the most waste by far

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  4. was there anyone who took 2 plates?

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    Replies
    1. Yes, a good amount of people took two plates and they usually had more food waste.

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  5. did you notice many people going up more than once or was it pretty much different people every time?

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    Replies
    1. Pretty much all different people. The people who could have come up twice saved all their plates and cups and brought all their stuff up at once. However, there were a couple of people who came up twice but none came up three times.

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course outline

Course as is week 1-5 3d printing week 6 Engineering as a whole week 7-8 analytics week 9-12 LEGO week 13-14 Christmas lights week 15 ...