10 Ways IoT Improves Quality Control in Manufacturing
The Internet of Things (IoT) could become a fundamental aspect of manufacturing quality control. However, it is still in the early adoption stage. As some business leaders consider incorporating it into their facility’s quality control processes, how well will their decision pay off?
1. Increases Testing Frequency
Manufacturers often conduct final quality control tests randomly or at preset intervals. Although this method is helpful, it lets defects slip through unnoticed — which isn’t good for customer satisfaction or brand reputation.
Incorporating IoT sensors into the production line lets facility administrators increase their testing frequency, mitigating these issues. Pressure, optical, and chemical sensors can quickly test entire batches to ensure their dimensions, weight, and color match the specs.
2. Enables Preventive Maintenance
What happens when quality control equipment breaks down? In manufacturing, unexpected downtime is costly. While manufacturers could technically keep producing parts despite systems being down, they’d likely experience a surge in customer complaints afterward.
Alternatively, if a machine on the production line malfunctions, it would keep operating until someone notices it — meaning an entire batch of products could be defective. Preventive maintenance driven by IoT technology could solve this issue of quality control in manufacturing.
An IoT sensor attached to manufacturing equipment can monitor unusual vibrations, temperatures, and leaks. As a result, it can detect issues long before they become critical. Experts say companies should aim for 80%-85% planned maintenance because it’s so effective.
3. Improves Inspection Accuracy
Digitalization has significantly benefited the manufacturing industry. Technology has increased its productivity by 40% over the past two decades. While business leaders may hesitate to incorporate artificial intelligence into their IoT strategy, it may be worth the effort.
IoT technology can supplement manual labor and decision-making when paired with AI. A machine learning system incorporated into a production line sensor can use the data it collects in real-time to inspect more products than a human ever could.
4. Detects Defects
Internet-connected computer vision systems can identify defects in real-time and automate inspections. They can check a product’s weight, dimensions, and integrity when combined with sensors. They can send images to a worker’s station if they detect an anomaly, enabling immediate corrective action.
5. Enhances Decision-Making
The longer manufacturers have IoT technology implemented, the larger their dataset will be. They can compare their historical information with the data points they capture in real-time for better visibility into their quality control processes.
In time, they can pinpoint how, when, and where product defects occur. This precision is part of why the global market for industrial IoT will be worth $22.3 billion by 2025, up from $2.5 billion in 2020 — a 792% increase in just five years.
6. Automates Corrective Action
Quality control is strictly documented, and business leaders typically use those records to make decisions about production line changes. Realistically, the delay between receiving and acting on data can affect their efficiency and defect rate.
IoT and AI can streamline manual administrative tasks related to quality control by automatically triggering a post-analysis response. They can automatically prompt corrective and preventive action if they detect a measurement passing a predefined threshold.
Instead of waiting weeks or months to implement changes, this technology can make minor, real-time adjustments as it captures new data. This dynamic decision-making process can substantially increase manufacturers’ flexibility.
7. Identifies Human Error
Internet-connected wearables can track workers’ movements and locations, improving production line visibility and defect traceability. Management can use these data-driven insights to uncover instances when human error is the root cause of abnormalities and inefficiencies.
Globally, there were over 15 billion IoT connections in 2023. This technology has become so prevalent and accessible that investing in wearables for an entire team wouldn’t be a budget-breaking investment — even for smaller companies.
8. Strengthens Defect Traceability
Pairing interconnected technology with solutions like radio-frequency identification tags or QR codes makes every part traceable. This way, business leaders can connect every IoT-generated data point to an exact machine or product. Since some faults take a while to manifest, these documents would be vital for compliance and quality assurance.
9. Makes Tests Exhaustive
Most facilities place quality control technology at specific points along the production line. However, even those with multiple systems throughout the raw materials and final inspection stages miss out on critical insights because they don’t have total visibility.
Embedding IoT sensors throughout the production line lets manufacturers continuously check products instead of examining them at various stages, making inspections exhaustive. This way, they can identify the moment something develops a defect.
About 86% of senior executives in manufacturing believe smart factory solutions will be the main drivers of competitiveness by 2030. They’d likely prefer this comprehensive quality control because it gives them a novel advantage.
10. Proactively Prevents Faults
Many faults aren’t visible. Sometimes, a hidden design flaw contributes to abnormalities and failures. Since manufacturers use those specs as the baseline for everything they produce, they may unknowingly make entire batches defective and struggle to find the root cause.
When combined with computer vision technology or AI, IoT sensors can identify potential issues early in prototyping. This way, decision-makers can eliminate anything contributing to premature failure or increase the chances of defects without wasting time or money.
The Benefits of Using Industrial IoT in Quality Control
Manufacturers that use IoT for quality control could minimize defects, reduce waste, and improve customer satisfaction. Implementing AI into these systems could reduce labor expenses and substantially improve efficiency.