The Internet of Things (IoT) has the potential to become a fundamental aspect of quality control in manufacturing. However, it is still in the early stages of adoption. How much will it pay off when some business leaders consider incorporating it into their factory's quality control processes?
1. Increase testing frequency
Manufacturers typically conduct final quality control tests randomly or at preset intervals. While this method is useful, it allows defects to be overlooked—which is detrimental to customer satisfaction or brand reputation.
Integrating IoT sensors into the production line allows facility managers to increase testing frequency, thereby mitigating these issues. Pressure, optical, and chemical sensors can quickly test entire batches to ensure their size, weight, and color meet specifications.
2. Implement preventative maintenance
What happens when quality control equipment malfunctions? In manufacturing, unexpected downtime is costly. While manufacturers may technically continue producing parts during a system outage, they may subsequently face a surge in customer complaints.
Alternatively, if a machine on the production line malfunctions, it will continue to run until someone notices it—meaning the entire batch of products could be defective. Preventative maintenance driven by IoT technology can address quality control issues in manufacturing.
IoT sensors connected to manufacturing equipment can monitor abnormal vibrations, temperatures, and leaks. Therefore, they can detect problems before they become serious. Experts say companies should aim for 80-85% planned maintenance, as it is highly effective.
3. Improve inspection accuracy
Digitalization has greatly benefited the manufacturing industry. Over the past two decades, technology has increased manufacturing productivity by 40%. While business leaders may be reluctant to incorporate artificial intelligence into their IoT strategies, it could be worthwhile.
The combination of IoT technology and artificial intelligence can supplement manual labor and decision-making. Machine learning systems integrated into sensors on the production line can inspect more products than humans can using data collected in real time.
4. Defect detection
Networked computer vision systems can identify and automatically inspect defects in real time. When used in conjunction with sensors, they can check the weight, dimensions, and integrity of products. If an anomaly is detected, they can send images to workers' workstations for immediate corrective action.
5. Enhance decision-making capabilities
The longer manufacturers implement IoT technology, the larger their datasets become. They can compare historical information with data points captured in real time to better understand their quality control processes.
Over time, they can pinpoint exactly how, when, and where product defects occur. This precision is one of the reasons why the global Industrial Internet of Things (IIoT) market is projected to reach $22.3 billion by 2025, up from $2.5 billion in 2020—a 792% increase in just five years.
6. Automatically execute corrective actions
Quality control is meticulously documented, and business leaders typically use these records to make decisions regarding production line changes. In reality, the delay between receiving data and acting upon it can impact efficiency and defect rates.
The Internet of Things (IoT) and artificial intelligence (AI) can streamline manual management tasks related to quality control by automatically triggering post-analysis responses. If they detect that a measurement exceeds a predefined threshold, they can automatically prompt corrective and preventative actions.
This technology eliminates the need to wait weeks or months to implement changes, allowing for small, real-time adjustments as new data is captured. This dynamic decision-making process can significantly improve manufacturers' flexibility.
7. Identifying human error
Connected wearable devices can track worker movement and location, improving production line visibility and defect traceability. Management can leverage these data-driven insights to identify situations where human error is the root cause of anomalies and inefficiencies.
In 2023, there were over 15 billion IoT connections globally. The technology has become so ubiquitous and widespread that investing in wearable devices for the entire team wouldn't be an overspending investment—even for smaller companies.
8. Enhance defect traceability
Combining connectivity technologies with solutions such as RFID tags or QR codes enables traceability of every component. This allows business leaders to connect every data point generated by the Internet of Things (IoT) to a specific machine or product. Since some faults take time to manifest, this documentation is crucial for compliance and quality assurance.
9. To make the test comprehensive and thorough.
Most factories place quality control technologies at specific points on the production line. However, even those factories with multiple systems at the raw material and final inspection stages can miss crucial insights due to a lack of complete visibility.
By embedding IoT sensors throughout the production line, manufacturers can continuously inspect products, rather than inspecting them at each stage, making inspections thorough and comprehensive. This allows them to identify when defects occur.
Approximately 86% of manufacturing executives believe that smart factory solutions will become a major driver of competitiveness by 2030. They are likely to prefer this comprehensive quality control approach because it provides them with a new competitive advantage.
10. Proactively prevent faults
Many failures are invisible. Sometimes, hidden design flaws can lead to anomalies and malfunctions. Because manufacturers use these specifications as a benchmark for producing all their products, they may unknowingly introduce defects into entire batches, making it difficult to pinpoint the root cause.
When combined with computer vision or artificial intelligence, IoT sensors can identify potential problems early in the prototyping process. This allows decision-makers to eliminate any factors that could lead to premature failure or increase the likelihood of defects, without wasting time and money.
Benefits of using Industrial IoT in quality control
Manufacturers using the Internet of Things (IoT) for quality control can minimize defects, reduce waste, and increase customer satisfaction. Implementing artificial intelligence in these systems can reduce labor costs and significantly improve efficiency.
