Featured Product
This Week in Quality Digest Live
Lean Features
Sarah Burlingame
Coaching can keep management and employees on track
Michaël Bikard
Receiving outsized credit can encourage individuals to work together, even when it results in lower-quality output.
Rachel Gordon
New algorithm is accurate, efficient, and adaptable for complex, real-world assemblies
Sue Via
A lean management road map
Brian Brooks
We talk prevention, but do detection

More Features

Lean News
Quality doesn’t have to sacrifice efficiency
Weighing supply and customer satisfaction
Specifically designed for defense and aerospace CNC machining and manufacturing
From excess inventory and nonvalue work to $2 million in cost savings
Tactics aim to improve job quality and retain a high-performing workforce
Sept. 28–29, 2022, at the MassMutual Center in Springfield, MA
Enables system-level modeling with 2D and 3D visualization, reducing engineering effort, risk, and cost
It is a smart way to eliminate waste and maximize value
Simplified process focuses on the fundamentals every new ERP user needs

More News

Carly Barry


How Lean Six Sigma Students at Rose-Hulman Reduced Food Waste

Their project resulted in awareness of continuous muda

Published: Saturday, August 3, 2013 - 13:50

To promote ethical and moral responsibility in shaping its graduates, the Rose-Hulman Institute of Technology created a sustainability initiative to reduce its own environmental footprint.

As part of that team’s efforts, Six Sigma students at Rose-Hulman conducted a project to reduce food waste at the campus dining center. I got the opportunity to learn more by talking with project leader Diane Evans, Ph.D., a Six Sigma Black Belt and associate professor of mathematics at Rose-Hulman; and project team member, Neel Iyer, a mechanical engineering student.

Calculating average food waste per meal

According to a July 2012 paper in the Food Policy journal, food waste in the United States on the consumer level translated into almost 273 pounds per person in 2008. Evans’ students converted this number into pounds per day; to determine the amount of waste per meal, they divided the figure by 2.5 meals per day. They didn’t count breakfast as a full meal because it typically does not see as much waste as lunch or dinner. The students calculated the average food waste as 4.78 ounces per meal.

Using this number as a standard, the class set out to reduce the edible food waste per student by one ounce per meal during the lunch period. With this goal established, the class began by learning more about the current dining center processes and food waste at Rose-Hulman. “Our aim with this project was to reduce food waste using standardized quantitative process improvement techniques,” says Iyer. “Lean Six Sigma project tools make it easy to share the hard savings and prove results statistically, while also giving others a framework to replicate what we have done.”

Using lean Six Sigma tools in the cafeteria

The students used the define, measure, analyze, improve, and control (DMAIC) methodology to manage and complete the project. As part of the define phase, students developed process maps using the lean Six Sigma and quality improvement software, Quality Companion. The process maps helped them understand the current flow of students through the dining center, as well as where potential improvements could be made. In addition, they created a CT Tree, where critical-to-quality was at the top of the tree, to quantify the students’ expectations for their dining experience and to visually connect the students’ needs to the goals of the project. This tool allowed them to verify that sustainability issues were a key concern to students who wanted their school’s dining room to be environmentally friendly (see figure 1).

Figure 1: Fishbone or Cause & Effect diagram. Click here for larger image.

With the process defined and the key causes outlined, the project entered the “measure” phase. The students collected baseline food-waste data to establish the current capability of the process. They conducted a food audit to form their data set, during which class members stationed themselves at the food disposal area of the dining center. After students finished eating, class members collected their trays and scraped and dumped uneaten food and liquid into a bucket. Then the weight of the food waste was recorded. Using control charts, the students determined that the lunch-time waste process was “in control,” and that there were no unusual points or outliers.

The class chose to measure the capability of their process against the maximum national average waste per meal calculated earlier (4.78 ounces). They ran a capability study in Minitab Statistical Software, and viewed all aspects of the analysis on one chart with the Capability Sixpack (see figure 2). The study confirmed that Rose-Hulman had above-average food waste per person during lunch.

Figure 2: Recorded food waste Click here for larger image.

For each process input from the group’s current-state process map, the students constructed a cause-and-effect (C&E) matrix, with outputs based on those already listed in the CT Tree. The C&E matrix helped the students to determine likely relationships between process inputs and outputs, and conducting a failure mode and effects analysis (FMEA) gave them another tool to identify and prioritize the severity of potential causes of waste.

Now the project entered the “improve” phase. The students formed a list of recommended actions based on the variables they could control and the short time frame they had to complete the project. These actions focused on educating students about food waste using posters, demonstrations, and seminars at the dining center during lunch hours. They also suggested that dining room staff provide students with smaller serving utensils for condiments, pre-dish more foods, and limit how many glasses and bowls of food or drink students could take per tray.

Finding a ‘statistically significant’ difference in waste amounts

After the awareness campaign, the class performed a second food-waste audit to determine the post-improvement process capability. They were able to show that the process was still capable with respect to the national average, and after providing students with food waste education, they found the process capability had improved over the capability analysis conducted before the education intervention.

The students used box plots to compare food waste amounts before and after the educational campaign (see figure 3).

Figure 3: Comparison of food waste after improvement phase

Further analysis of food-waste data collected before and after the campaign revealed a statistically significant difference in waste amounts. The class’s data found an average reduction of 2.66 ounces of waste per person/meal (or 0.166 pounds per person/meal) after the campaign. Because the dining center typically serves about 875 students per day during lunch, the class estimated that the center could see a waste reduction of approximately 2,327.5 ounces, or 145.4 pounds during a single lunch period. Over the 50 lunch periods in a typical quarter at Rose-Hulman, a total of 7,270 pounds of food waste could be saved. And because food waste costs the dining center $1.60 per pound ($0.10 per ounce) on average, the class calculated a savings of $471.20 during just the two days they held the food waste campaign and collected data. If the campaign were run during an entire quarter, they estimated total savings of $11,781.

Although the improvement efforts were short-term, Evans and her class were proud to pass on their findings to Rose-Hulman’s administrators. “The administration is proud as well, and they are showcasing the results,” says Evans. “They see the value, and they’re encouraging follow-up projects from the Six Sigma students.”


About The Author

Carly Barry’s picture

Carly Barry

Carly Barry’s role at Minitab Inc., developer and provider of software and services for quality improvement and statistics education, is to collaborate with others to reveal the power of quality improvement and data analysis tools in all sorts of deliverable communications—from customer success stories to help resources. Her goal is to present statistics in a manner that can be easily related to real life. In an age where lean Six Sigma and other data-driven quality improvement projects can save companies millions, it pays to be knowledgeable about data analysis.


Waste-away rules-of-thumb?

According to unofficial sources, one third - thirty percent - of the food bought in the USA, and I would say western Countries, goes to waste. There is surely a chart-language or chart-alphabet that's become very common, but engaging students in projects to analyze food waste is really going a bridge too far. One just has to look at the waste bins when leaving home for work. Thank you.