Assignable variation is a concept widely used in quality control, manufacturing, and statistical process management. It refers to variation in a process that can be traced to a specific cause, rather than being random or inherent to the system. Understanding assignable variation is crucial for businesses and engineers because it helps identify problems that can be corrected to improve efficiency, reduce waste, and maintain consistent product quality. In this topic, we will discuss what assignable variation is, provide examples, explain how it differs from common cause variation, and explore practical ways to manage it in industrial and everyday contexts.
What is Assignable Variation?
Assignable variation, also known as special cause variation, occurs when there is an identifiable factor affecting the process that causes deviation from expected results. Unlike common cause variation, which is natural and random within a process, assignable variation arises from specific, often controllable events. For example, a sudden malfunction in a machine or an operator’s mistake can lead to assignable variation. Detecting these variations quickly allows organizations to take corrective action and prevent defects or inconsistencies in production.
Characteristics of Assignable Variation
Assignable variation has several characteristics that distinguish it from normal or common variation
- It is caused by a specific, identifiable factor.
- It is often irregular and not part of the regular process pattern.
- It can usually be corrected once the cause is identified.
- It can lead to significant deviations from the expected quality or performance standards.
Examples of Assignable Variation
Understanding assignable variation becomes easier when looking at practical examples across different industries and everyday situations. Here are several examples
Manufacturing
- A sudden defect in a batch of products caused by a misaligned machine component.
- Variation in product weight due to a faulty scale used in packaging.
- Defective materials from a supplier leading to inconsistent quality.
- Operator error during assembly that results in non-standard dimensions.
Healthcare
- An unexpected spike in patient wait times caused by equipment failure in a hospital.
- Errors in medication dosage due to miscommunication among staff.
- Variation in laboratory test results caused by malfunctioning diagnostic machines.
Service Industry
- Customer complaints arising from a temporary software glitch in an online ordering system.
- Variation in service speed due to a temporary shortage of staff during peak hours.
- Incorrect billing caused by a programming error in a point-of-sale system.
Difference Between Assignable Variation and Common Cause Variation
It is important to distinguish assignable variation from common cause variation, as the approach to managing each is different. Common cause variation is inherent to the process and occurs naturally. For example, minor differences in temperature or machine wear can lead to slight, predictable variations in output. Assignable variation, however, is irregular and caused by a specific factor. Correcting common cause variation usually requires process improvement, while assignable variation can often be fixed by addressing the root cause directly.
Examples Highlighting the Difference
- Common cause A bakery consistently produces cookies that vary slightly in size due to small differences in dough portioning.
- Assignable cause A batch of cookies is burnt because the oven temperature was accidentally set too high.
- Common cause Slight variation in the thickness of a metal sheet due to normal machine wear.
- Assignable cause A metal sheet is too thin because a sensor on the rolling machine was miscalibrated.
How to Detect Assignable Variation
Detecting assignable variation requires careful monitoring of processes and data collection. Statistical tools like control charts, process capability analysis, and run charts are commonly used. When data points fall outside the control limits or show a non-random pattern, it indicates assignable variation. Once identified, further investigation is necessary to pinpoint the specific cause and implement corrective measures.
Steps to Address Assignable Variation
Addressing assignable variation involves several key steps
- Identify the variation through monitoring and data collection.
- Analyze the process to find the root cause of the variation.
- Take corrective action to eliminate or reduce the cause.
- Monitor the process to ensure the variation has been controlled.
- Implement preventive measures to avoid recurrence in the future.
Benefits of Managing Assignable Variation
Effectively managing assignable variation has numerous benefits for businesses and organizations
- Improved product quality and consistency, leading to higher customer satisfaction.
- Reduced waste and lower production costs.
- Increased process efficiency by quickly addressing irregularities.
- Enhanced ability to predict outcomes and maintain standards.
- Stronger decision-making based on accurate data and root cause analysis.
Examples of Corrective Actions
Here are some practical examples of actions taken to correct assignable variation
- Replacing a malfunctioning machine part that caused product defects.
- Re-training employees after repeated human errors are detected.
- Changing a supplier when raw materials consistently cause product inconsistencies.
- Updating software systems to fix bugs that lead to process irregularities.
- Implementing additional inspections to catch anomalies before products reach customers.
Assignable variation is an essential concept in quality management and process control. It represents deviations in a process caused by specific, identifiable factors that can be corrected. By understanding and identifying assignable variation, organizations can improve product quality, reduce waste, and maintain consistent performance. Using examples from manufacturing, healthcare, and service industries helps illustrate how assignable variation occurs in real-world scenarios. Detecting and addressing these variations using statistical tools and root cause analysis ensures processes remain efficient and predictable. Mastering the concept of assignable variation is crucial for engineers, managers, and quality control professionals seeking to enhance productivity and maintain high standards in their operations.