Quality Management 011 Lecture Slides.pdf

Quantifying Process Variations

1. Week Eleven:
Quantifying Process Variations
QUALITY MANAGEMENT
DR EBENEZER ODURO ANTIRI

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•Process variation (also known as process variance or process variability) can
be defined as the numerical value indicating how far processes vary from
their expected performance.
•This is a leading cause of quality issues in production and transactional
processes.
•Many times, product quality issues are not identified until it has turned into a
large-scale disaster.
•Now, leadership must identify the source of the problem and take the needed
steps to prevent the problem from reoccurring. If there is too much process
variation, identifying areas for improvement becomes challenging.
Process Variation
Q U A N T I F Y I N G P R O C E S S V A R I A T I O N S

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•Some level of variance in manufacturing processes is inevitable.
•The primary question is whether the inputs that cause the variation
are controlled and predicted.
•If you understand this variation, can account for it in the output, or
work around it, then we can handle the situation.
•However, having a general knowledge of process variation and the
types can provide a solid foundation for improvement.
Process Variation
Q U A N T I F Y I N G P R O C E S S V A R I A T I O N S

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•Generally, there are two types of process variations:
1.Common cause variation
2.Special cause variation
Types of Process variation
P R O C E S S V A R I A T I O N S

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•Common cause variation, also referred to as “noise” results from
things that may or may not be known.
•The causes for this variance are usually quantifiable and natural in
the system.
•Common cause variation usually lies within three standard deviations
from the mean where 99.73% of values are expected to be found.
Common cause variation
T Y P E S O F P R O C E S S V A R I A T I O N

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•Special cause variation refers to unexpected things that affect a
process.
•These variations were not observed, are unusual and non-
quantifiable.
•These sporadic causes are the result of a change introduced in the
process resulting in a problem.
•Things can get more challenging when special cause variation is
introduced because they occur out of the blue.
•This failure can be corrected by making changes in the methods,
material, or processes.
Special cause variation
T Y P E S O F P R O C E S S V A R I A T I O N

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Process Variation in Manufacturing
•An example of common cause variation in a manufacturing process is
an oven or finishing range with a thermostat that allows the
temperature to slightly drift up and down but remain within the
control limits.
Types of Process Variation
T Y P E S O F P R O C E S S V A R I A T I O N

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•Special cause variation in a manufacturing environment may include
environment, materials, manpower, technology, equipment, and
many more.
•Utilizing the same manufacturing example as earlier of an oven or
finishing range with a thermostat, if that thermostat “fails” resulting
in a rapid spike or drop in temperature, this would result in the
manufacturing process being out of control and a special cause
variation.
Types of Process Variation
T Y P E S O F P R O C E S S V A R I A T I O N

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Process variation can help direct where to work and drive continuous
improvement.
Identifying, characterizing, quantifying, and reducing variation can
enhance financial performance, reduce operating costs, and improve
customer satisfaction.
We should be continually monitoring for sources of variation and
aggressively working to reduce variation with the knowledge that this
will improve overall performance.
The Benefit of Understanding Process Variation
P R O C E S S V A R I A T I O N

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•For some organizations, business processes vary by geography, by
industry, or due to legal requirements.
•And yet, good business practice dictates that process standardization
can increase efficiency, clarify expectations and optimize
productivity.
•While standardized processes have been proven to save time and
minimize errors, sometimes a cookie-cutter approach to the
execution of tasks can cause more problems than it solves.
Ways to manage Process Variations
P R O C E S S V A R I A T I O N

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1.Create high-level standard processes: Standard processes are
defined only at a high level and are not functional as practical
guidance.
2.Create mega-processes: Often encountered during change initiatives
and in technical teams, this scenario involves the meticulous,
detailed documenting of every possible process variation. Due to the
complexity of the documentation, this system often fails.
Pitfalls to avoid in managing Process Variations
P R O C E S S V A R I A T I O N

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3.Create individual process variations: In more mature organizations,
management often allows this approach, which leads to siloed
processes and process sprawl. It compromises the organization’s
ability to change and complicates administration.
Clearly, these three methods fail to deliver the efficiency, productivity
and visibility organizations are looking to achieve with process
standardization.
Pitfalls to avoid in managing Process Variations
P R O C E S S V A R I A T I O N

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1.Create a global standard process as a foundation for all variations.
With a centralized governance team that consists of global process
owners, you can use global processes as benchmarks against which
the variations can be measured.
2.Establish local variations where necessary. Local process variations
can be created by process variant experts, who must ensure their
differences are highlighted against the standard processes.
3.Ensure all process variations are visible. All variations on every
Ways to effectively manage process variations
P R O C E S S V A R I A T I O N

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3.Ensure all process variations are visible. All variations on every
process need to be carefully reviewed and compared to standard
processes.
4.Make sure teams have easy access to the relevant variations.
Leverage a platform that automatically routes teams to those
process variations that apply to their business unit, location or other
characteristic.
Ways to effectively manage process variations
P R O C E S S V A R I A T I O N

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5.Notify owners of process variations or changes to the standard
processes. They can review the changes and either incorporate them
into their specific variations or reverse them and keep their
variations unchanged.
6.Implement global reporting. Global process owners can review and
consequently reject or approve variations.
7.Gather and analyze cost and time data. With this information, you
can compare the effectiveness of process variations against
standard processes, and determine their efficiency.
Ways to effectively manage process variations
P R O C E S S V A R I A T I O N

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•Every establishment collects copious amounts of data on systems
and processes daily.
•This data then informs decisions across all areas of the company,
including hiring, equipment needs, and even environmental
elements.
•With so many critical factors at stake, it’s imperative that data
collection is reliable.
•The only way to know this is to use a measurement system.
Measurement System Analysis
P R O C E S S V A R I A T I O N

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•Measurement systems are a group of related measures that help
companies quantify various characteristics of a process to assess the
characteristic’s accuracy.
•While many companies are quick to put measurement systems in
place, many struggle to keep up with them, rendering them obsolete
after too many years of neglect.
•This begs the question: How does a company know that the collected
data is reliable?
•This is why we need measurement system analysis.
Measurement System
P R O C E S S V A R I A T I O N

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•Measurement systems are a group of related measures that help
companies quantify various characteristics of a process to assess the
characteristic’s accuracy.
•While many companies are quick to put measurement systems in
place, many struggle to keep up with them, rendering them obsolete
after too many years of neglect.
•This begs the question: How does a company know that the collected
data is reliable?
•This is why we need measurement system analysis.
Measurement Systems
P R O C E S S V A R I A T I O N

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•Measurement System Analysis (MSA) is used to determine the
suitability of a measurement system for use.
•It is crucial to have a well-functioning measurement system so that
the data collected is accurate and precise.
•MSA is a process used to evaluate the suitability of a measuring
system for use.
•MSA is used to identify and quantify the sources of variation in a
measuring system.
Measurement System Analysis
P R O C E S S V A R I A T I O N

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•The first thing a measurement system analysis seeks to define is
whether the correct measurement is being used for the
measurement system.
•This is followed quickly by the assessment of the measuring device.
Many times, measuring tools such as gages and fixtures wear down
or break, rendering them less effective. The MSA will determine if a
measuring tool or device needs to be calibrated, replaced, or
updated.
Measurement Systems Analysis Fundamentals.
P R O C E S S V A R I A T I O N

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•The measurement system analysis will also assess the personnel’s
ability to effectively execute the measurement system instructions
and any environmental factors that might affect the process.
•Any variations in the operation process could result in skewed
results, potentially leading to flawed products.
•The MSA’s goal is to identify these variations and prevent this from
happening.
•Finally, the measurement system analysis will calculate all this
variation to determine if the current measurement system needs an
overhaul.
Measurement Systems Analysis Fundamentals.
P R O C E S S V A R I A T I O N

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•While there are many tools and techniques that can be used to
complete an MSA, such as calibration studies or destructive testing
analyses, we’re going to explore the procedure for a Gage R&R.
Measurement Systems Analysis Case Study
P R O C E S S V A R I A T I O N

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•A software program at a thermal control company is programmed to
cut a piece of metal to 12 inches. This piece of metal will eventually
become a housing for a thermal control, so it’s imperative that the
first piece of metal measure accurately each time. As part of this
company’s quality control, they’ve created a measurement system in
which line operators randomly pull pieces of metal off the line to
measure them with a digital length gauge. This helps to ensure the
machine’s ability to accurately cut the metal.
Measurement Systems Analysis Case Study
P R O C E S S V A R I A T I O N

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•But how do these operators know that they can rely on their digital
length gauge? In this case, the company decides to perform a Gage
Repeatability and Reproducibility Study (Gage R&R).
Step 1: Determine Type of Data Collection
•In this case, the manufacturing company wants to know if there is
any variation in each piece of metal’s measurements.
•This is called variable data, which means the potential exists to have
measurements that vary between samples.
Measurement Systems Analysis Case Study
P R O C E S S V A R I A T I O N

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Step 2: Sample Collection and Operator Selection
•The next step is to collect a random sampling of the sheet metal
during any given production run.
•It’s important to obtain at least 10 samples.
•Once the samples have been randomly chosen, recruit three
operators who routinely complete the measurement system process.
•The sampled sheet metal pieces are labeled with their appropriate
lengths without the operators being aware of these labels.
Measurement Systems Analysis Case Study
P R O C E S S V A R I A T I O N

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Step 3: Measurement Process
For this example, the random sampling includes 10 samples of sheet
metal casings. Each operator will measure the sample casings and
record their data. Each operator will measure the same random
sampling of ten sheet metal casings three times, for a total of thirty
measurements. Lastly, the study organizer will rearrange the sample
set between each operator to remove any potential bias.
Measurement Systems Analysis Case Study
P R O C E S S V A R I A T I O N

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Step 4: Calculations
•Once the operators have completed all three rounds of measurement, the
study organizer will compare each set of measurements to three evaluation
areas.
•First, the organizer will compare each measurement to a master value.
•Second, the organizer will compare each operator’s measurements across all
three rounds, essentially comparing each operator to themselves.
•This is called ‘within’ variation.
•Last, the organizer will compare each operator’s measurements to the other
appraiser’s measurements. This is called ‘among’ variation.
Measurement Systems Analysis Case Study
P R O C E S S V A R I A T I O N

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•It’s not enough to have a measurement system if it’s never properly analyzed
and calibrated.
•Without a strong MSA, the quality of products will suffer, harming customer
loyalty.
•When a robust MSA in the six sigma program is properly utilized, problems
are easier to detect, and waste is easier to eliminate.
•They possess the acumen to wield MSA as a transformative tool.
•Through meticulous analysis and calibration, aSix Sigma Black Belt's
expertise ensures the accuracy and reliability of measurements,
safeguarding product quality and fortifying customer loyalty.
MSA in Quality Management
P R O C E S S V A R I A T I O N

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•Measurement System Error is a type of statistical error that occurs when the
measuring device used to obtain a measurement is inaccurate.
•This can happen for various reasons, but it is often because the measuring
device needs to be properly calibrated or the person using it needs to be
adequately trained.
•Measurement System Error can also occur when the measuring device is not
properly maintained or when the measurement conditions are not ideal.
•Systematic errors are caused by a flaw in the design of the measurement
system and can often be corrected if the defect is known.
Measurement System Error
P R O C E S S V A R I A T I O N

30. Any questions?
Thanks!
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