SPC and manufacturing quality

Manufacturing processes typically define quality as conforming to a product specification. However, no two products are ever identical, because every manufacturing process can contain multiple sources of variability.

Statistical Process Control (SPC) is a method used to calculate and control the variability of quality in manufacturing processes by detecting defects as early as possible. Quality data in the form of product or process measurements or readings from machines or instrumentation is typically obtained in real-time

during the manufacturing process. The data collected for SPC is used to evaluate, monitor, and control the manufacturing process and ensure the highest quality product possible.

In many factories, the quality of a finished assembly or product is typically ensured by inspecting the product during the manufacturing process. Each product (or a sampling of products from a production lot) may be accepted or rejected according to how well the product meets the

design specification at the time of the sampling. In contrast, SPC

uses statistical tools to observe the performance of the manufacturing process in order to detect notable defects before they result in the production of a sub-standard product. Using Statistical Process Control, manufacturers can move from

a defect detection approach to

a defect prevention

 approach, reducing or even eliminating the need to rely exclusively on sampled inspection of products. Using SPC, you can increase productivity, reduce waste/scrap, and minimize the risk of producing and shipping non-conforming products. 

Benefits of using SPC

Using SPC in FactoryLogix to help control manufacturing quality provides multiple benefits including:

• Locate defect information quickly

• Filter data multiple ways to suit your specific manufacturing needs and quality standards

• Get focused, detailed data analysis quickly

• Use as an additional method of evaluating quality data

• Have greater visibility into your manufacturing operations