Quality Control Chart with Runs Rules

Runs Rules-Based Control Charts: A Simpler Way to Ensure Quality

Mira Elwood in Tech & Innovation September 2025 • 5 min read.

"Learn how to use runs rules with control charts for effective quality control, even when you don't know all the details."

Imagine you're running a small business that produces organic skincare products. Every batch needs to be just right to maintain your brand's reputation and keep customers happy. But sometimes, things go wrong. Maybe the consistency is off, or the scent isn't quite perfect. That's where control charts come in. These charts help you visually track your production process and spot when something is out of the ordinary. But what if you don't know exactly what 'normal' looks like? What if you're still learning the ropes and figuring out the ideal parameters for your products? That's where runs rules-based control charts can be a game-changer.

Traditional control charts often rely on having precise knowledge of your process parameters, like the average weight of a product or the standard deviation of its purity. However, in many real-world situations, this information isn't readily available. You might be dealing with a new process, changing raw materials, or simply lacking the resources to conduct extensive data analysis. In these cases, estimating the parameters becomes necessary, but it can also introduce additional uncertainty and affect the reliability of your control chart.

This article will guide you through a simpler approach to quality control using runs rules-based control charts. We'll break down the key concepts, explain how to construct and evaluate these charts, and show you how they can help you identify and address potential problems, even when you're operating with limited information. By the end, you'll have a practical understanding of how to use runs rules to maintain consistent quality in your processes, regardless of the challenges you face.

What Are Runs Rules and Why Are They Important?

Runs rules, also known as sensitizing rules, are extra decision rules used alongside the basic one-point decision rule in Shewhart control charts. The one-point rule simply flags a process as out-of-control if a single data point falls outside the control limits. Runs rules, on the other hand, look for patterns or trends in the data, making them more sensitive to small-to-moderate shifts that might otherwise go unnoticed.

Think of it like this: imagine you're monitoring the temperature of a greenhouse. A one-point rule would alert you if the temperature suddenly spiked to a dangerously high level. But runs rules would also detect if the temperature gradually increased over several days, indicating a potential problem with the ventilation system.

Here are some common examples of runs rules:

Two out of three consecutive points fall beyond the 2-sigma limits: This rule suggests that a sustained shift is occurring, even if individual points aren't extreme enough to trigger the one-point rule.
Four out of five consecutive points fall more than one standard deviation away from the center line: This indicates a potential trend or bias in the process.
Eight consecutive points fall on one side of the center line: This rule is highly sensitive to even small shifts in the process average.

By incorporating runs rules, you can significantly improve the sensitivity of your control chart and detect subtle changes that could lead to quality issues. This proactive approach allows you to address problems early on, preventing them from escalating and impacting your final product or service.

Taking Control of Quality

By understanding and applying runs rules-based control charts, businesses of all sizes can take proactive steps to maintain consistent quality and prevent costly problems. Whether you're a small skincare business just starting out or a large manufacturing facility with complex processes, these tools provide a simple yet powerful way to monitor your operations, identify potential issues, and ensure that your products and services consistently meet the highest standards.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1002/qre.2423, Alternate LINK

Title: On Efficient Construction And Evaluation Of Runs Rules-Based Control Chart For Known And Unknown Parameters Under Different Distributions

Subject: Management Science and Operations Research

Journal: Quality and Reliability Engineering International

Publisher: Wiley

Authors: Rashid Mehmood, Muhammed Hisyam Lee, Shahzad Hussain, Muhammad Riaz

Published: 2018-11-08

Everything You Need To Know

What are runs rules in the context of control charts, and how do they enhance quality control?

Runs rules, also known as sensitizing rules, are supplementary decision rules used alongside the basic one-point decision rule in Shewhart control charts. While the one-point rule identifies when a single data point falls outside control limits, runs rules detect patterns or trends in data. This enhances quality control by making the chart more sensitive to small-to-moderate shifts that might otherwise go unnoticed, enabling earlier detection and correction of process variations.

How do runs rules-based control charts address the challenge of limited process knowledge, particularly when precise process parameters are unknown?

Runs rules-based control charts are valuable when precise process parameters like average weight or standard deviation are not readily available. In situations where estimating parameters introduces uncertainty, runs rules offer a simpler approach. They focus on identifying patterns and trends in the data rather than relying on precise parameter estimates. This makes them useful for new processes, changing raw materials, or when resources for extensive data analysis are limited. However, if you have no data you cannot apply Runs Rules.

Could you provide some examples of common runs rules and explain how they work to identify process variations?

Certainly. Common examples of runs rules include 'Two out of three consecutive points fall beyond the 2-sigma limits,' which indicates a sustained shift; 'Four out of five consecutive points fall more than one standard deviation away from the center line,' signaling a potential trend or bias; and 'Eight consecutive points fall on one side of the center line,' which is highly sensitive to even small shifts in the process average. These rules identify process variations by looking for specific patterns and trends, allowing you to detect and address issues before they escalate.

What are the benefits of incorporating runs rules into control charts, and how does this proactive approach impact the final product or service?

Incorporating runs rules significantly improves the sensitivity of control charts, enabling the detection of subtle changes that could lead to quality issues. This proactive approach allows businesses to address problems early on, preventing them from escalating and impacting the final product or service. By understanding and applying runs rules-based control charts, businesses can maintain consistent quality and prevent costly problems.

How can runs rules be applied specifically in a small business context, such as producing organic skincare products, to maintain consistent quality?

In a small business producing organic skincare products, runs rules can be applied to monitor various aspects of the production process, such as the consistency, scent, or color of each batch. For example, if four out of five consecutive batches have a scent that is slightly off, this would trigger investigation under runs rules, even if no single batch is drastically out of specification. This allows for early detection and correction of potential issues. By using runs rules-based control charts, the business can ensure that their products consistently meet the highest standards, maintaining their brand's reputation and customer satisfaction. The type of control chart can vary (X-bar, Individuals, etc) depending on the type of data you are collecting.