if you want to attend this on-demand webinar, you can go to: https://hubs.ly/H0p8fkQ0 Food manufacturers are tasked with not only creating but producing delicious, quality and consistent food and beverages. Quality is especially of the essence with consumable and drinkable goods as failure is not an option when it can lead to sick consumers. That's where data analysis with Minitab can help. You will learn how to select the right analytical tools and use them to solve your complex problems like: * Achieving consistency in your goods * Improving overall quality * Increasing efficiencies in your current production Tools and analyses that will be covered include control charts, capability analysis, hypothesis testing, and attribute agreement analysis.

1. Better process.
Better outcome.
Better product.
Using Minitab for superior quality
in food manufacturing

2. © 2019 Minitab, LLC.
• 20+ years applying and
teaching data analytics tools
to solve business problems
in manufacturing,
engineering, supply chain,
finance, human resources.
• Certified Lean Six Sigma
Master Black Belt.
• MS in ME and MBA from
Marquette University.
• ASQ, PMI, ASA
Meet the Presenter:
Antonio Vargas
Minitab Solutions Architect

3. © 2019 Minitab, LLC.
Menu
3
1. Appetizers
Minitab
Introductions
Industry Trends 2020
2. House Specials
Control Charts
Measurement System Analysis
Process Capability Analysis
3. Desserts
Questions
“To-go Box”

4. © 2019 Minitab, LLC.
4
Industry Trends 2020
• Customization and uniqueness.
• Inclusivity (including global foods,
dietary options, and socially
conducive ambience).
• Sustainability, transparency, and
ethical sourcing.
• Value for the dollar in food and
convenience.
Source:
Food & Beverage Industry Trends 2020
www.nestleprofessional.us/

5. © 2019 Minitab, LLC.
Control Charts
Problem
A coffee producer wants to determine if the storage
temperature of green coffee beans at its warehouse,
a critical factor in the process, is stable.
The recommended storage temperature, to ensure
quality consistency is between 68 °F and 77 °F.
Data set
StorageTemperature.MWX
Data collection
Food processing engineers record the temperature
of the warehouse over the course of a day.
Tools: I-MR Chart, Assistant

6. © 2019 Minitab, LLC.
What is a control chart?
It is a visual representation of a process behavior or voice of the process.
This tool helps in identifying trends and patterns in the data over time.
Useful to recognize “special causes” from “common causes” of variation.

7. © 2019 Minitab, LLC.
What control chart should I use?
What type of data am I looking at?
Do I want to measure the amount of
variation in the data?
How was the data collected, in
subgroups or individually?

8. © 2019 Minitab, LLC.
Results
The coffee beans look good, but is the
process in control?
What tests did the process fail?
Test Results for MR Chart of Temperature
TEST 1. One point more than 3.00 standard deviations from center line. Test
Failed at points: 9, 10, 37
TEST 2. 9 points in a row on same side of center line. Test Failed at points: 11,
12, 13, 14, 23, 24, 57
Test Results for I Chart of Temperature
TEST 5. 2 out of 3 points more than 2 standard deviations from center line (on
one side of CL). Test Failed at points: 56, 57
TEST 6. 4 out of 5 points more than 1 standard deviation from center line (on
one side of CL). Test Failed at points: 55, 56, 57
What corrective action do you recommend?

9. © 2019 Minitab, LLC.
Now, let’s use the Assistant

10. © 2019 Minitab, LLC.
Results

11. © 2019 Minitab, LLC.
Measurement System Analysis
Problem
Food technicians want to determine whether a
weight scale is contributing to the data variation
they see in a control chart and if they must take
corrective action before conducting a process
capability study. The lower specification limit is 100
gm and the upper specification limit is 110 gm.
Data set
WeightScale.MWX
Data collection
Three food technicians measure the weight of ten
randomly selected samples.
Tools: Gage R&R (Crossed)

12. © 2019 Minitab, LLC.
What is measurement system analysis (MSA)?
• Process variation can come from the measurement system (how we measure
things) or from the process itself (how we make or complete things).
• Effective process improvement is based on understanding where the data
variation is coming from.
• MSA methods assess the performance of a measurement system for a given
application.
• A measurement system consists of the equipment, people and methods involved
in measuring the quality of a process output.

13. © 2019 Minitab, LLC.
What type of analysis should I perform?
Overall, there are two types of analysis, depending on the data type:
• Gage Repeatability and Reproducibility (GR&R) for continuous data.
• Attribute Agreement Analysis for attribute data.
Sure these options will increase your appetite!

14. © 2019 Minitab, LLC.
Can I trust the measurement system?
Where is most of the observable
variation coming from?
What is the Repeatability? EV
What is the Reproducibility? AV
How do I address these issues?

15. © 2019 Minitab, LLC.
Now, using the Assistant

16. © 2019 Minitab, LLC.
Capability Analysis
Problem
Quality assurance inspectors need to check the
quality level of a gummy bears packing process
and improve it if necessary. The lower specification
limit is 3.6 oz and the upper specification limit is 3.7
oz.
Data set
PackingProcess.MPJ
Data collection
Five samples are randomly selected from 50
batches and the weight of each package is
measured.
Tools: Capability Analysis, Normality Test

17. © 2019 Minitab, LLC.
What is process capability analysis?
• This tool measures performance of a process with respect to customer
specifications.
• It measures how well a process complies to the voice of the customer.
• Provides a metric to identify process improvement opportunities and a reference
point to compare between before and after.

18. © 2019 Minitab, LLC.
First steps
How big is the sample size?
Is the process in control?
Does the data follow a normal
distribution?

19. © 2019 Minitab, LLC.
Let’s do the capability study
Pick from the Minitab menu:
• Stat/ Quality Tools/ Capability Analysis/ Normal
• Stat/ Quality Tools/ Capability Six Pack/ Normal
• Assistant/ Capability Analysis
A menu to appeal the most selective palate!

20. © 2019 Minitab, LLC.
Results
Cpk and Ppk are less than 1.33, we can conclude that this process is not capable.
The defect rate is 9.53%! We need to improve the customer experience…

21. © 2019 Minitab, LLC.
Visualizations
Descriptive
Means and
Variation
Diagnostic
Inferential
Statistics
Predictive
Regression
Logistic
No matter where you are on your analytical
journey, Minitab is here to help
21

22. © 2019 Minitab, LLC.
Our Approach: More Than Business Analytics…Solutions Analytics
Software
Services
Training
Learn first-hand by attending public or
customized trainings in your facilities
according to your requirements.
Statistical
Consulting
Personalized help with statistical
challenges from collecting the right data
to interpreting analysis more.
Support
Assistance with installation,
implementation, version updates and
license management.
Master statistics and
Minitab anywhere
with online training
Machine learning and
predictive analytics
software
Start, track, manage
and execute
improvement projects
with real-time
dashboards
Powerful statistical
software everyone
can use.
Data Analysis Predictive Modeling Visual Business Tools Project Oversight
2
2
Visual tools to
process and product
excellence.
Online Training
Solutions analytics is our integrated approach to providing software and services that enable organizations to make better decisions that drive business excellence.

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Looking for More on Food Manufacturing?
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A link to sign-up will be included in our post
webinar email or you can visit:
info.minitab.com/resources/ebook/
food-manufacturing

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Questions?
Please continue to write your questions
in the questions pane at any time.