Inline Quality Assurance is a manufacturing strategy that focuses on detecting quality-related issues at earlier stages of production. Companies in several industries use the inline quality assurance strategy to minimize the number of defective products delivered to customers. To implement this strategy, quality checkpoints must be put at the different manufacturing stages to identify any quality issues early in the manufacturing process.
Quality assessment at this checkpoint can be done manually or using advanced technology devices. At each quality checkpoint, at least one quality aspect is tested. Products that don’t have issues proceed to the next stage, and the defective ones are removed from the production line. This is done to ensure no value is added to a defective product.
Adding value to a defective product is one of the common sources of waste that companies using inline quality assurance want to eliminate. It should be noted that failures become more expensive to fix the closer the product gets to the end of the production line. Catching these failures early in the production process can save the company time and money that would be wasted fixing these failures at later stages.
Despite being a reliable method for detecting failures, inline quality assurance is not a perfect solution, especially if it is done manually by humans. Sometimes people at different quality checkpoints may not identify certain quality issues, especially if they have to handle thousands of products daily.
Digital solutions to fix challenges of inline quality assurance
The effectiveness of inline quality assurance has improved over the years, thanks to advancements in technologies like machine vision Internet of Things (IoT) and real-time cloud computing, which make detecting defects much more accurate. Manufacturers can now use IoT sensors and devices such as cameras, scales, and temperature and humidity sensors to detect all the quality-related issues at the different checkpoints.
Some automated manufacturing facilities can automatically remove certain products from the production line if the quality assessment devices identify any issues. Using digital solutions to detect quality issues also makes it easier to gather valuable data that can enable the relevant stakeholders to know the most common quality issues.
This data can also be used to improve the design of these products earlier on in the manufacturing cycle to eliminate the costs of having to fix the same defects in future products. Most of the modern digital inline quality assurance systems are connected to the cloud, making it possible for operators, managers, and other production stakeholders to monitor the quality assessment data remotely and in real-time.
Why inline quality assurance?
- To reduce the costs incurred in fixing defective products since errors can be detected earlier in the manufacturing process.
- Digital solutions for inline quality assurance make identifying and quantifying typical quality issues easy. These issues can then be fixed at the design level to avoid incurring more costs to solve the same problems.
- Reduces customer complaints since almost every defective product is removed from the production line, so no defective product will likely get into the hands of the customers.