Statistical Process Control (SPC) is an essential methodology for monitoring and reducing variability in industrial production, ensuring high-quality products while minimizing defects. In this article, we explain what SPC is, how it works, its main benefits, and how to implement effective statistical process control using MES tools and software, optimizing efficiency, reducing waste, and improving customer satisfaction.
What is Statistical Process Control (SPC) in manufacturing?
Statistical Process Control is the application of statistical tools to monitor variation in a process or production method, detect deviations, and thus anticipate potential quality problems.
It is a proactive and preventive quality control strategy through which companies can ensure the stability of their industrial processes and meet customer specifications without inspecting 100% of production.
Companies implementing SPC take random samples from their production processes, which are then used to create control charts with an average or central line and upper and lower control limits, calculated from the set of obtained samples.
Thanks to these charts, companies can quickly and visually determine whether process variability is expected and caused by common causes (natural and consistent over time) or whether values have deviated from the average due to assignable causes (random and unpredictable), requiring corrective actions immediately.
Proven benefits of Statistical Process Control in a company
Applying Statistical Process Control tools allows manufacturing companies to gain competitive advantages such as:
- Reduction of defects and waste, minimizing rework costs.
- Compliance with quality standards without inspecting 100% of production.
- Higher operational efficiency, optimizing resources and improving productivity.
- Enhanced analytical capacity using statistical control charts and other monitoring tools.
- Promotion of continuous improvement methodologies, such as Six Sigma.
Which industries can benefit from SPC?
SPC is widely used in sectors where quality, precision, and efficiency are critical. Some industries that benefit most from its application include:
- Manufacturing: it allows for reducing defects, optimizing production, and improving operational efficiency.
- Automotive: it ensures consistency in the manufacturing of critical parts and components, preventing errors that could compromise safety.
- Food and beverage: it controls variability in ingredients and production processes to ensure the safety and quality of the final product.
- Electronics: it minimizes failures in the manufacturing of sensitive components and improves the reliability of devices.
- Aerospace: it maintains strict quality control to comply with demanding safety regulations.
- Metallurgy and steelmaking: it optimizes production and enhances material strength through precise control of variables in industrial processes.
In general, any sector aiming to minimize defects, reduce costs, and optimize production can benefit from implementing SPC.
How does Statistical Process Control work?
Companies implementing SPC take samples from their production processes and generate quality control charts to analyze process variability. These charts include:
- A central line (average).
- Upper and lower control limits calculated from the collected samples.
Depending on the observed variability, the data may indicate that the process is stable (expected variability) or that there are assignable causes requiring immediate action.
What are the main types of variability in a process?
There are two types of variability in a production process.
Common variability
The first type is common variability (or common cause). It is inherent to the process and results from normal, consistent factors over time, such as machinery wear, slight fluctuations in materials, or environmental conditions. This variability is predictable and usually remains within established control limits.
Special variability
The second type is special variability (or assignable cause). It occurs when an external or unexpected factor affects the process, generating significant deviations in production. It can result from equipment failures, human errors, changes in raw materials, or environmental disturbances. This type of variability must be identified and corrected immediately to avoid defects and production losses.
Main SPC tools and software for industry
To implement SPC, companies use various process control tools, such as:
- Process control charts, including I-MR, XBAR-R, and XBAR-S.
- Process capability indicators (Cp, Cpk, Pp, Ppk).
- Data collection methods with industrial statistical software.
- Sistemas de monitorización en tiempo real para la detección de desviaciones.
How we help at Mapex to implement Statistical Process Control
Mapex incorporates various tools for automatic or mechanical statistical process control. Our MES system can generate control charts to analyze both numerical quality control results collected via the MapexQM module and process variables obtained through the IIoT Platform.
Quality results can be taken with one or several samples. Depending on the number of samples, Mapex uses a specific type of control chart: I-MR for individual samples; XBAR-R for subgroups of 2–8 samples; and XBAR-S for subgroups with more than 8 samples.
In all cases, control limits are set to determine whether the process remains stable. Conditions or alarms can also be applied to detect unnatural process deviations in real time or retrospectively.
Mapex SPC tools are very useful in office environments, as they display Pp and Ppk indices, which measure long-term process performance across multiple production orders.
Operators can also access Mapex SPC analysis charts directly from plant screens, where the platform shows Cp and Cpk indices calculated from results recorded for the current production order.
Benefits of using software for Statistical Process Control
With this statistical analysis tool, the Mapex platform adopts a proactive role and can alert operators and plant managers when processes deviate from their natural variability.
Using software for Statistical Process Control optimizes the control process by automating data collection and analysis.
Some benefits of implementing SPC in industrial companies include:
- Increased productivity by making process behavior predictable.
- Improved quality by allowing corrective action before defects occur.
- Compliance with specifications and a higher ability to achieve elevated quality standards.
- Reduced production costs through less rework and waste.
- Increased operational efficiency.
- Better resource optimization.
- Enhanced analytical capacity within the company.
- Promotion of the Six Sigma continuous improvement methodology.
- Higher customer satisfaction and fewer complaints.
Statistical Process Control is a key methodology to ensure quality in industrial production. Through statistical process analysis and control charts, companies can detect deviations in time and minimize defects.
Discover how Mapex MES can help you implement Statistical Process Control and reduce defects in your factory. Request a free demo today.
