7 Basics that Define Variation & Process Capability in 6 Sigma

7 Basics that Define Variation & Process Capability in 6 Sigma


Six Sigma has evolved as an effective approach for quality management and process optimisation. The notions of variation and process capacity are critical to its success since they play a critical role in finding and removing faults, decreasing waste, and improving overall performance. To fully realize the benefits of Six Sigma, it is critical to understand the principles of identifying variation and process capacity.

This article will look at seven essentials that serve as the foundation for this knowledge. Practitioners who understand these fundamentals may successfully identify sources of variation, assess process performance, and lead continuous improvement activities.

1. Defining Variation 

The variability in outputs that happen organically during any process is referred to as variation. In Six Sigma, it is critical to understand the two forms of variation: common cause and special cause. Common cause variation, often known as random variation, results from intrinsic elements in a process. Special cause variation, on the other hand, is erratic and originates from identified causes that exist outside of the process's normal functioning.

Six Sigma practitioners can assess whether an observed outcome is attributable to intrinsic process variability or particular reasons requiring attention by distinguishing between these two forms of variation.

2. Sources of Variation 

It is critical to understand the sources of variation in order to successfully manage it. People, methods, materials, machines, and the environment (PMMME) are the five most prevalent sources of process variation. People represent the human component of the process, which includes training, skill levels, and individual performance. Methods include the standardised methods and protocols that are used. Materials are the resources that are utilised, such as raw materials, components, and supplies. Machines are the equipment, tools, and technology that are used in the process. Finally, the physical variables such as temperature, humidity, and illumination are part of the environment. Six Sigma practitioners may prioritise improvement efforts and execute targeted solutions to minimise or eliminate the identified sources of variation by fully examining these sources of variation.

3. Process Capability 

The capacity of a process is a measure of how effectively it can satisfy client expectations within acceptable boundaries. It is defined by the intrinsic variance of the process and its closeness to the desired target value. Two main indices are widely used to measure process capability: Cp and Cpk.

When only common cause variation is present, CP is a measure of the process's potential capacity. It compares the dispersion of the process output to the specification limits, indicating the possibility of faults. CPK, on the other hand, takes into account both common and special cause variation and evaluates how effectively the process is currently working. It takes into consideration any variation from the goal value as well as the dispersion of the process output. Understanding these process capability indices is vital for evaluating the effectiveness of improvement initiatives and establishing realistic performance goals.

4. Defining Tolerance Limits

Tolerance limits are the acceptable boundaries within which a product or service must conform to meet customer expectations. Determining these limits requires careful consideration of customer requirements, industry standards, and regulatory guidelines. Tolerance limits provide a reference for assessing process capability and identifying opportunities for improvement.

It is essential to strike a balance when defining tolerance limits. Overly rigid limits can be unrealistic and lead to unnecessary costs, while loose limits may result in poor quality and customer dissatisfaction. Through careful analysis and collaboration between stakeholders, appropriate tolerance limits can be established, ensuring a process's output consistently meets customer expectations.

5. Measurement Systems Analysis 

Accurate and reliable data is paramount in assessing process performance and making informed decisions. Measurement Systems Analysis (MSA) is a systematic approach to evaluate the reliability, accuracy, and precision of measurement systems used in Six Sigma projects. By conducting MSA, practitioners can ensure that the data collected is trustworthy and suitable for analysis.

MSA involves various techniques, such as gauge repeatability and reproducibility studies, to assess the consistency and agreement between multiple appraisers and measurement devices. It helps identify any sources of error or bias in the measurement process, allowing for appropriate adjustments or improvements. By incorporating MSA into the Six Sigma methodology, organizations can have confidence in the data-driven decisions made during process improvement initiatives.

6. Statistical Process Control (SPC) 

Statistical Process Control (SPC) is a key tool in managing variation and ensuring process stability. SPC involves the use of statistical techniques to monitor and control processes, enabling timely identification of variations that exceed acceptable limits.Control charts, a common SPC tool, visually display process data over time, highlighting trends, shifts, and abnormal patterns. By establishing control limits based on process performance data, practitioners can distinguish between random variation and significant deviations that require intervention. SPC facilitates proactive problem-solving, reducing the likelihood of defects and process failures. By implementing SPC, organizations can achieve process stability, maintain consistency, and meet customer requirements consistently.

7. Continuous Improvement and Lean Six Sigma 

Continuous improvement is a fundamental principle within the Six Sigma philosophy. It emphasizes the ongoing effort to identify and eliminate waste, improve efficiency, and enhance customer satisfaction. Lean Six Sigma combines the principles of Six Sigma and Lean methodologies, integrating the reduction of process variation with the elimination of non-value-added activities.

By embracing continuous improvement practices and Lean Six Sigma principles, organizations can foster a culture of relentless pursuit of excellence. Through tools such as DMAIC (Define, Measure, Analyze, Improve, Control) and Kaizen events, teams can systematically address process variation, enhance process capability, and drive sustainable improvements.


Understanding the principles of Six Sigma variation definition and process capability is critical for attaining operational excellence and customer satisfaction. Practitioners may discover areas for improvement and execute focused solutions by understanding the various forms and causes of variance. Process capability indices give useful insights into the performance of a process and help to lead improvement initiatives. Tolerance limits guarantee that the process output meets customer expectations while minimising needless expenditures. Measurement Systems Analysis (MSA), Statistical Process Control (SPC), and continuous improvement approaches such as Lean Six Sigma further boost process performance, stability, and efficiency. By mastering these seven basics, organizations can realise the full potential of Six Sigma, reduce errors, and constantly improve their processes. Embracing these principles develops a culture of data-driven decision-making and allows teams to achieve large and lasting gains in quality and customer happiness.

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