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AutomationVision & Sensors

Vision & Sensors | Automation

Why Automation Misses Its Full Potential for Quality—and How to Fix It

Many manufacturers miss out on automation’s potential for improving quality. To achieve these gains, quality must be prioritized from the business case to sourcing and implementation.

By Mikkel Viager
Engineers training and having a discussion in a robot development plant.

Image Source: cofotoisme / iStock / Getty Images Plus

November 21, 2024

Manufacturing has come a long way in improving product quality, but many companies are still missing out on one huge opportunity—automation. While most people recognize that automating processes can lead to fewer human errors and more consistent output, many manufacturers aren’t taking full advantage of how much it can actually improve their quality performance.

Through our consulting work helping manufacturers gain clarity on their automation potential, we’ve seen that automation can, on average, reduce around 50-75% of quality issues depending on the industry. The potential is real, but businesses often struggle to unlock it for several reasons.

The Potential is There, But Not Always Realized

The good news is that manufacturers are well aware of this potential. Our data shows that in 2024, improving quality was listed as a key objective in 38.6% of the automation projects we tracked globally through our procurement platform—making it one of the top priorities, right behind boosting productivity and increasing capacity. But even though companies are setting out with quality in mind, they don’t always achieve the results they’re hoping for.

READ MORE

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  • Collaborative Robots Emerge as Viable Automation Options for SMEs

So why does this happen? One reason is that the path from recognizing the need for quality improvements to actually implementing effective solutions is tricky. While automating a process can solve some quality issues, if it’s not done right, it can also introduce new problems.

Removing Human Oversight Can Create New Issues

Automation can free the human element from certain manufacturing tasks, and that’s usually a good thing when it comes to cutting down on inconsistencies and fatigue. However, the downside is that you also lose a pair of eyes that might catch defects before they become a major issue.

If you automate a process without putting proper quality checks in place, you run the risk of replicating the same mistake over and over again. That’s where automated quality control systems come into play—whether it’s sensors, cameras, or other inspection tools that can detect when something goes wrong. Without these in place, manufacturers might not notice a problem until it’s too late, and thousands of defective products have already been produced.

Why Quality Improvements Get Downplayed: The Challenge of Quantifying Costs

One of the challenges we’ve seen is that many companies don’t have an overview of the cost of quality issues. It’s tough to put a number on things like rework, scrap, customer complaints, and warranty claims, even though these can eat into a company’s profits more than they realize. Research suggests that poor quality are typically costing companies around 15-20% of their sales revenue.

Because it’s hard to pin down these costs, they often get left out of business cases for automation projects. Instead, companies tend to focus on more easily measurable benefits like boosting productivity. But if you don’t take the time to accurately calculate the costs of poor quality, you’re missing out on a major part of the potential savings that automation can deliver.

We help companies integrate these costs into their business cases and have found that by doing so, quality improvements become a central part of the overall goal, leading to projects that reduce both defects and unnecessary costs.

Sourcing and Implementation: Where Quality Gains Are Won (or Lost)

Even when manufacturers know how much they could save by reducing quality issues, the next challenge is translating these goals into the sourcing and implementation of a solution. It’s not enough to just buy a robot and expect it to magically improve quality—you need to make sure that your quality goals are built into the project from day one.

That means being clear in your requirement specifications. If your goal is to reduce scrap by 60%, the requirements you give to vendors when you’re sourcing your solution must support this goal. We’ve seen too many projects fall short because quality wasn’t prioritized in the early stages, leaving manufacturers with automation that improves efficiency but doesn’t tackle their quality issues.

Setting the right goals and expectations for quality improvements with suppliers upfront also makes it easier to hold them accountable after implementation. However, it’s also crucial to provide enough flexibility for vendors to propose the most cost-effective solutions while keeping them accountable to your quality goals. Specifying too many features or having too high quality goals may just as well make solutions unnecessarily complex or costly. Striking this balance when sourcing automation solutions can be tricky, but is well worth it. In our experience, the difference between a poorly or correctly scoped project can be several hundred percent in solution costs. Knowing the automation market’s sweet spot–or consulting with someone who does–is key to getting the most “quality for money.”

The Takeaway: Quality Needs to Be Prioritized Throughout the Whole Journey

Automation offers huge potential to improve quality in manufacturing, but it doesn’t happen automatically. To really capitalize on it, companies need to make quality a key focus throughout the entire process—from building the business case to sourcing and implementation. By taking the time – or getting help – to quantify the true cost of quality issues and embedding those goals into every stage of the automation project, manufacturers can unlock significant savings and improve their products.

KEYWORDS: machine vision manufacturing metrology robotics robotics integration

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Mikkel viager

Mikkel Viager is a robotic engineer and principal advisor at HowToRobot—a global, vendor-independent advisory company that helps manufacturers succeed with robotics and automation. With over a decade of experience across various industries, Mikkel is known for his pragmatic and impartial approach to automation and is a frequent speaker on the topic.

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