Everything you need to know about Generative AI in Manufacturing

Quality Control in Manufacturing

Glossary post
Quality control is an essential step in any kind of manufacturing facility. You must ensure that completed products meet expectations no matter what you’re producing, whether electronic components or baked goods. This means the result is free from flaws and functions as expected.
Glossary post

What is manufacturing quality control?

Quality control is an essential step in any kind of manufacturing facility. You must ensure that completed products meet expectations no matter what you’re producing, whether electronic components or baked goods. This means the result is free from flaws and functions as expected.

In a bakery producing hot dog buns, the buns must all be about the same size and shape and should have about the same flavor from day to day; they should also remain fresh until the sell-by date stamped on the packaging. 

Quality control failures could lead to loss of customers and reputation—priceless assets you might never gain back. And in a worst-case scenario, such as in pharmaceuticals or automotive equipment, product flaws could endanger lives. 

So it’s no surprise that quality control is a significant part of the manufacturing process. But it can also introduce many problems and slow down production. Today, AI and automation are available to help improve manufacturing quality control.

What you need to know about manufacturing quality control

Quality control and quality assurance are very commonly confused terms. Quality control generally refers to the practical, hands-on aspects of an organization’s overall approach to quality assurance. Thus, quality assurance is a goal, while quality control is a means of achieving that goal.

Here’s an example:

  • Quality assurance might dictate that you should put together a procedure manual for each machine or station and create a log to document its repair history.
  • Quality control would then find practical ways to visually inspect that station and test its output.

While the ultimate goal of quality assurance and quality control is reducing defects, it’s essential to realize that you’ll never get that defect rate down to zero… so that’s not the goal. Instead, quality control in manufacturing focuses on continuous improvement along several dimensions:

  • Reducing the overall percentage of defects
  • Catching defects and production problems earlier in the process
  • Benchmarking quality against competitors
  • Reducing complaints and returns from customers

By improving manufacturing quality control, you reduce waste, eliminate employee rework and frustration, and all associated costs. Perhaps more importantly, you reduce the chance of faulty products reaching customers—leading to support calls, lawsuits, and even recalls.

How can you ensure manufacturing quality control?

When it comes to factory quality control, there are many things organizations can do to ensure the results are as good as possible, including:

  • Hiring suitable staff with appropriate experience
  • Providing all staff with training in their job function
  • Defining internal product and process quality standards
  • Adopting industry standards and/or regulations (e.g., HACCP for food safety)
  • Implementing in-house communication and documentation to ensure standards are met
  • Testing finished products to ensure they meet standards (final-product inspection)

In many organizations, however, the burden of manufacturing quality control rests on product testing. 

Obviously, testing stations are an important step! However, since testing often occurs at the end of the manufacturing process, this can create problems. 

Slow manual processes rely on expert personnel and create bottlenecks. But the solution to this—speeding things along by testing only a small sample—means that these manufacturing quality control systems are probably missing many flawed products.

When you find problems, it’s too late to fix things. This also translates into greater potential financial loss due to additional raw materials and rework costs than if the problem had been caught earlier. And when you’re finding out about issues long after the fact, you can’t react soon enough—for instance, if a machine has drifted out of alignment over time.

But there is a better way to detect problems earlier in the manufacturing process using advances in artificial intelligence.

How process tuning time optimization can improve manufacturing quality control

Process tuning time optimization uses artificial intelligence (AI) to analyze data such as performance indicators coming off your production line. This live data helps you pinpoint trouble spots fast and deliver calibration vectors directly to the production floor in real-time. 

Using AI for manufacturing quality control delivers deeper insights so you can act proactively to eliminate problems before they happen—before products are finished, or defective products reach customers.

Data-driven, AI-fueled insights let you…

  • Cut the time and resources needed for calibration
  • Discover bottlenecks and resolve them quickly
  • Identify potential product issues without being slowed down by quality control

Vanti is a leader in scalable AI designed for manufacturing. Our platform gives you fine-tuned process calibration powered by machine learning to help you speed up throughput and reduce defects—and it scales easily across all your production lines.

Best of all, Vanti starts working within hours, with zero R&D effort and zero downtime, all from an easy-to-use dashboard. 

Let Vanti help you stay ahead of manufacturing quality control with process tuning time optimization custom-tailored to your manufacturing environment.