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Process
Variation
UNDERSTANDING THE PROCESS VARIATION
What is a “Process”?
A process is a set of steps used to accomplish a specific target. Once a process has been defined, it is
preferred that these steps be carried out to guarantee a repeatable result, irrespective of who or
when the actions are completed. We won't be able to get the same results if we don't understand
how something was done or how we got there. When it comes to operations involving products and
clients, consistency is essential!
Process Variation
Process variation is the numerical value used to describe the degree of variation within a group.
V= SD 2
Process variation occurs when manufacturing procedures deviate from a predetermined standard.
This is one of the main reasons for quality problems in manufacturing processes. Problems with
product quality are frequently not discovered until they have developed into major catastrophes.
When the issue has been located, management must take the necessary actions to stop it from
happening again. Finding areas for improvement might be difficult when there is too much process
variation.
Process Variation
It is unavoidable for production processes to vary to some extent. Whether the inputs that create the
fluctuation are predictable and under control is the main issue. You can manage the situation if you
understand this variation, can take it into account in the result, or can find a workaround. Yet, having
a general understanding of the types of process variation can lay a strong foundation for
development.
Types of
Process
Variation
Usually there are two types of
Process Variation:
1- Common causes
2- Special causes
Common Cause Variation
Noise, or common cause variation, is the outcome of factors that are either known or unknown. This
variance's causes are typically quantifiable and inherent to the system. 99.73% of values are predicted to be
be found within three standard deviations (+/- 3 s) of the mean, which is where common cause variation
typically occurs. If you are plotting on a control chart, a few random points that fall within the control limit
will show this variance.
A statistically stable process results from the impact that common cause variation has on the process
outputs being predictable and controllable.
You will need to adjust something fundamentally if you want to get rid of this prevalent cause variation.
An example of common cause variation in a manufacturing process is an oven with a thermostat
that allows the temperature to slightly float up and down but remain within the control limits.
Common Cause Variation
An example of common cause variation in a manufacturing process is an oven with a
thermostat that allows the temperature to slightly float up and down but remain within the
control limits.
Other examples of common causes of variation are:
◦ poor product design, poor process design, unfit operation, unsuitable machine, untrained operators,
inherent variability in incoming materials/goods from supplier, lack of adequate supervision skills,
poor lighting, poor temperature and humidity, vibration of machines, etc.
Special Cause Variation
Unexpected events that impact a process are referred to as special cause variation. These changes are
unusual, weren't seen, and can't be measured. These sporadic causes are the outcome of a procedure
modification that caused a problem.
The introduction of particular cause variation can make things more difficult because they happen
unexpectedly.
Modifying the procedures, materials, methods or tools will solve this problem.
Utilizing the same manufacturing example as earlier of an oven 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.
Special Cause Variation
When a control chart shows special cause variation, a
process is said to be out-of-control or unstable.
Common types of special cause variation signals
include:
• A point outside of the upper control limit or lower
control limit,
• A trend: 6 or 7 points increasing or decreasing,
• A cycle or repeating pattern,
• A run: 8 or more points on either side of the average.
The benefits of understanding PV
Process variation can help prioritize tasks and support continuous improvement. Financial
performance, operations costs, and customer satisfaction can all be improved by identifying, defining,
quantifying, and minimizing variation. With the understanding that reducing variation will increase
overall performance, you should be vigilantly looking for causes of variation and actively working to
reduce it.
How to Find the Cause of Variation
You’ve found any significant variation in your process. However, you haven’t found what its cause
might be. Therefore, you need to find the source.
You can use a methodology like Six Sigma DMAIC, use a multi-vari chart (Excel or Minitab) to
identify the source of variation.
How to Find and Reduce Hidden Causes of Variation
DMAIC methodology is the Six Sigma standard for identifying a process’s variation, analyzing the
root cause, prioritizing the most advantageous way to remove a given variation, and testing the
fix. The tools you would use depend on the kind of variation and the situation.
For a smaller, shorter cycle methodology, you could try Lean tools like Kaizen.

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Process Variation - Definition - Understanding the Process Variation.pptx

  • 2. What is a “Process”? A process is a set of steps used to accomplish a specific target. Once a process has been defined, it is preferred that these steps be carried out to guarantee a repeatable result, irrespective of who or when the actions are completed. We won't be able to get the same results if we don't understand how something was done or how we got there. When it comes to operations involving products and clients, consistency is essential!
  • 3. Process Variation Process variation is the numerical value used to describe the degree of variation within a group. V= SD 2 Process variation occurs when manufacturing procedures deviate from a predetermined standard. This is one of the main reasons for quality problems in manufacturing processes. Problems with product quality are frequently not discovered until they have developed into major catastrophes. When the issue has been located, management must take the necessary actions to stop it from happening again. Finding areas for improvement might be difficult when there is too much process variation.
  • 4. Process Variation It is unavoidable for production processes to vary to some extent. Whether the inputs that create the fluctuation are predictable and under control is the main issue. You can manage the situation if you understand this variation, can take it into account in the result, or can find a workaround. Yet, having a general understanding of the types of process variation can lay a strong foundation for development.
  • 5. Types of Process Variation Usually there are two types of Process Variation: 1- Common causes 2- Special causes
  • 6. Common Cause Variation Noise, or common cause variation, is the outcome of factors that are either known or unknown. This variance's causes are typically quantifiable and inherent to the system. 99.73% of values are predicted to be be found within three standard deviations (+/- 3 s) of the mean, which is where common cause variation typically occurs. If you are plotting on a control chart, a few random points that fall within the control limit will show this variance. A statistically stable process results from the impact that common cause variation has on the process outputs being predictable and controllable. You will need to adjust something fundamentally if you want to get rid of this prevalent cause variation. An example of common cause variation in a manufacturing process is an oven with a thermostat that allows the temperature to slightly float up and down but remain within the control limits.
  • 7. Common Cause Variation An example of common cause variation in a manufacturing process is an oven with a thermostat that allows the temperature to slightly float up and down but remain within the control limits. Other examples of common causes of variation are: ◦ poor product design, poor process design, unfit operation, unsuitable machine, untrained operators, inherent variability in incoming materials/goods from supplier, lack of adequate supervision skills, poor lighting, poor temperature and humidity, vibration of machines, etc.
  • 8. Special Cause Variation Unexpected events that impact a process are referred to as special cause variation. These changes are unusual, weren't seen, and can't be measured. These sporadic causes are the outcome of a procedure modification that caused a problem. The introduction of particular cause variation can make things more difficult because they happen unexpectedly. Modifying the procedures, materials, methods or tools will solve this problem. Utilizing the same manufacturing example as earlier of an oven 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.
  • 9. Special Cause Variation When a control chart shows special cause variation, a process is said to be out-of-control or unstable. Common types of special cause variation signals include: • A point outside of the upper control limit or lower control limit, • A trend: 6 or 7 points increasing or decreasing, • A cycle or repeating pattern, • A run: 8 or more points on either side of the average.
  • 10. The benefits of understanding PV Process variation can help prioritize tasks and support continuous improvement. Financial performance, operations costs, and customer satisfaction can all be improved by identifying, defining, quantifying, and minimizing variation. With the understanding that reducing variation will increase overall performance, you should be vigilantly looking for causes of variation and actively working to reduce it.
  • 11. How to Find the Cause of Variation You’ve found any significant variation in your process. However, you haven’t found what its cause might be. Therefore, you need to find the source. You can use a methodology like Six Sigma DMAIC, use a multi-vari chart (Excel or Minitab) to identify the source of variation. How to Find and Reduce Hidden Causes of Variation DMAIC methodology is the Six Sigma standard for identifying a process’s variation, analyzing the root cause, prioritizing the most advantageous way to remove a given variation, and testing the fix. The tools you would use depend on the kind of variation and the situation. For a smaller, shorter cycle methodology, you could try Lean tools like Kaizen.