MNO2602
Assignment 4 Semester 1 2025
Unique #:
Due Date: May 2025
Detailed solutions, explanations, workings
and references.
+27 81 278 3372
, QUESTION 1
1.1
Random variation (also called common cause variation) refers to the natural,
inherent fluctuations that occur in a process due to countless small, uncontrollable
factors. These variations are expected and typically fall within control limits. For
example, minor differences in temperature or material properties in a manufacturing
process can cause random variation. These do not signal a problem with the
process.
In contrast, nonrandom variation (or special cause variation) arises from identifiable
and controllable sources outside the normal process. These variations are not part of
the system’s natural fluctuation and usually indicate that something has changed or
gone wrong. Examples include equipment malfunction, human error, or defective raw
materials. Nonrandom variation causes data points to fall outside control limits or
display unusual patterns, signaling a need for corrective action.
In summary, random variation is expected and stable, while nonrandom variation is
unusual and requires investigation.
1.2
When using a process control chart, several nonrandom signals can indicate that the
process is out of control:
1. A single point outside the control limits: This is the most obvious signal of
nonrandom variation and suggests a significant shift in the process.
2. A run of seven or more points on one side of the centre line: This may
indicate a gradual drift in the process mean, caused by a systematic issue.
3. A trend of increasing or decreasing points: A continuous upward or
downward pattern suggests that the process is changing over time.
4. Cyclic patterns or regular repeating patterns: These may indicate external
influences such as temperature changes or shift-based performance issues.
5. Hugging the centre line or control limits: Unusually close clustering or
repeated touching of control limits can indicate measurement issues or
unnatural behaviour.
These signals help analysts identify when to investigate and correct a process.
Varsity Cube 2025 +27 81 278 3372
Assignment 4 Semester 1 2025
Unique #:
Due Date: May 2025
Detailed solutions, explanations, workings
and references.
+27 81 278 3372
, QUESTION 1
1.1
Random variation (also called common cause variation) refers to the natural,
inherent fluctuations that occur in a process due to countless small, uncontrollable
factors. These variations are expected and typically fall within control limits. For
example, minor differences in temperature or material properties in a manufacturing
process can cause random variation. These do not signal a problem with the
process.
In contrast, nonrandom variation (or special cause variation) arises from identifiable
and controllable sources outside the normal process. These variations are not part of
the system’s natural fluctuation and usually indicate that something has changed or
gone wrong. Examples include equipment malfunction, human error, or defective raw
materials. Nonrandom variation causes data points to fall outside control limits or
display unusual patterns, signaling a need for corrective action.
In summary, random variation is expected and stable, while nonrandom variation is
unusual and requires investigation.
1.2
When using a process control chart, several nonrandom signals can indicate that the
process is out of control:
1. A single point outside the control limits: This is the most obvious signal of
nonrandom variation and suggests a significant shift in the process.
2. A run of seven or more points on one side of the centre line: This may
indicate a gradual drift in the process mean, caused by a systematic issue.
3. A trend of increasing or decreasing points: A continuous upward or
downward pattern suggests that the process is changing over time.
4. Cyclic patterns or regular repeating patterns: These may indicate external
influences such as temperature changes or shift-based performance issues.
5. Hugging the centre line or control limits: Unusually close clustering or
repeated touching of control limits can indicate measurement issues or
unnatural behaviour.
These signals help analysts identify when to investigate and correct a process.
Varsity Cube 2025 +27 81 278 3372
