I left off last with a post outlining how the Six Sigma students at Rose-Hulman were working on a project to reduce the amount of recycling thrown in the normal trash cans in all of the academic buildings at the institution.

Using the DMAIC methodology for completing improvement projects, they had already defined the problem at hand: how could the amount of recycling that’s thrown in the normal trash cans be reduced? They collected baseline data for the types of recyclables thrown into the trash, including their weights and frequencies. In order to brainstorm ideas to improve recycling efforts at Rose-Hulman and to determine causes for the lack of recycling in the first place, the students created fishbone diagrams.

## Implementing Improvements

The students then entered the ‘Improve’ phase of the project and formed a list of recommended actions based on the variables they could control to motivate recycling practices in a four-week time frame. The short time constraint was fixed due to the length of an academic quarter.

This list of actions included the following:

- Placing a recycling bin next to each and every trash can throughout the academic buildings, including classrooms.
- Constructing and displaying posters next to or on recycling bins indicating what items are recyclable and are not recyclable on campus:

- Informing campus about Rose-Hulman recycling policies, as well as the current percentage of recyclables on campus (by weight), determined during the Measure phase. (The information was shared with the entire campus via an email and an article in the school newspaper by Dr. Evans.)
- Encouraging good recycling habits through creative posters, contests, incentives, and using concepts related to “The Fun Theory.” Fun theory is used to change people’s behaviors through making activities fun. For example, the class discussed ways to make recycling bins produce amusing sounds when items are placed in it.

The students implemented many of these improvements and then gathered post-improvement data at the end of four weeks during four fixed collection periods.

## Analyzing Pre-Improvement vs. Post-Improvement Data

There were a total of 15 areas in the academic buildings where recycling data was collected. Fifteen student teams were assigned one of these areas for the entire project, collecting data during the pre- and post-improvement phases. There are a total of 60 data points for both phases.

The teams compared pre-improvement and post-improvement statistics for the percentage of recyclables in the trash with Minitab (using Stat > Basic Statistics > Display Descriptive Statistics in the software):

Some highlights of this analysis:

- The mean percentage of recyclables in trash decreased from 37% to 24%, which is a reduction of 35%.
- The median percentage of recyclables in trash decreased from 31% to 17%, which is a reduction of 45%.
- The total average weight of recyclables in trash over the baseline period (4 days) decreased from 84.3 pounds with a standard deviation of approximately 7.89 pounds to 45.9 pounds with a standard deviation of approximately 5.19 pounds during the improvement period, which is a reduction in the total average weight of 46%.
- The mean recyclable weight for all areas decreased from 1.405 pounds to 0.765 pounds, which is a reduction of 84%.

They were also able to view the improvements graphically with boxplots in Minitab:

*Boxplots of the percentage of recyclables during the four collection periods in the pre-improvement phase (left plot) and the four collection periods in the post-improvement phase (right plot).*

Although it is not apparent in these boxplots that the mean percentage of recyclables (the circles with the crossbars) has decreased in the improvement phase, it is obvious that the median percentage of recyclables (line within the boxplot) has decreased.

In addition, the students used Minitab plots to track changes in percentage of recyclables in the trash *per area*, both pre and post-improvement:

*Plot of the mean percentage of recyclables in the trash by academic building area for both pre and post-improvement phases. The mean is averaged over the four collection times in each phase.*

These plots helped the students to graphically see gaps between the percentages of recyclables collected pre and post-improvement by area. Given the location of each academic area, the changes between pre and post means were justifiable and informative.

And in order to statistically determine if the true mean percentage of recyclables post-improvement was significantly less than the true mean percentage of recyclables pre-improvement, the students ran a paired t-test for all 60 data points, pairing by area and day. See below for the Minitab output for this test:

With a t-test statistic of 4.66, it is evident that the recycling improvements made a difference! They ran a paired *t-*test since the pre and post recyclable percentages were linked by area and day. They did not need to check for normality of the paired differences since we had *n* = 60 data points.

After collecting baseline data, the students had created a Pareto Chart to display the type of trash (and recyclables) found in the regular trash cans. They also created a Pareto Chart for the post-improvement data—you can see both below to compare (pre-improvement – left, post-improvement – right):

Plastics were the most common recyclable item in the trash both pre- and post-improvement, and overall, besides the Java City coffee cups *increasing* *post*-improvement, the other categories saw a noticeable decrease post-improvement compared to pre-improvement.

To complete their pre- and post-improvement analysis, the students also ran a capability study in Minitab to determine the pre and post-improvement capability of recyclables in the trash. Post-improvement, both their Pp and Ppk values improved.

**R****esults**** and Future Improvement Efforts**

Of the 15 areas (Spring Quarter 2014) that collected pre-improvement and post-improvement data over the span of two four-day collection periods, only two areas had an increased percentage of recyclables in the trash after the improvements were made. These two areas had “special causes” associated, which can be explained.

One area with increased recyclables *after* improvements was the Moench Mailroom. The Moench Mailroom area is next to the campus mailroom where students pick up their daily mail, graded homework assignments, etc., in their mail slots. It was evident during post-improvement trash collection that a student had emptied an entire quarter’s worth of mail, including junk mail, magazines, and assignments, into the trash can by the mailroom. Since the student’s name was on the mail and assignments, it was clear that that the recyclables discarded in the trash was from this one student. He certainly threw off that area’s post-improvement data!

Although the improvement efforts were short-term, the students saw their efforts significantly decrease the percentage of recyclables being discarded in the normal trash cans at the academic buildings. At the beginning of Spring Quarter 2014, 36% of trash cans (by weight) were recyclable items. At the end of Spring Quarter 2014 after the improvement phase, 24% of trash cans (by weight) were recyclable items!

They were not only able to decrease the carbon footprint of their school and aid in their school’s sustainability program, but the increase in recycling also has the potential to create revenue for the school down the road (if they choose to recycle aluminum cans or sell paper, for example).

Dr. Evans and the students have shared their results with the campus community and plan to work with the administration to publish their results, which will hopefully highlight why these improvement efforts should stick around long-term. Way to go Dr. Evans and Rose-Hulman Six Sigma Students!

*Many thanks to Dr. Evans for her contributions to this post! *