The Internet of Things (IoT) has the potential to become a critical component of manufacturing quality control. Nevertheless, it is currently in the early stages of adoption. As business leaders contemplate integrating it into their facility’s quality control processes, what is the potential return on investment?
The Benefits of Using Industrial IoT in Quality Control
IoT is changing how manufacturers control quality. By using smart sensors, it helps find and fix problems faster. This improves the testing process and keeps machines running smoothly. With IoT, manufacturers can catch defects early and avoid costly mistakes. Below, we have listed 10 benefits of IoT in improving quality control in manufacturing.
1) Increases Testing Frequency
Manufacturers often perform quality control checks either randomly or at specific intervals. While this approach can be useful, it sometimes allows defects to go unnoticed, which can harm both customer satisfaction and brand image.
By integrating IoT sensors into the production process, facility managers can boost the frequency of these tests, addressing this challenge. Sensors like pressure, optical, and chemical types can quickly assess entire batches to ensure their dimensions, weight, and color meet the required specifications.
Do you know? The Impact of IoT on Business Efficiency
2) Enables Preventive Maintenance
What happens if quality control equipment fails? In manufacturing, unplanned downtime can be costly. While production may technically continue during system failures, it would likely lead to a rise in customer complaints afterward.
Similarly, if a machine on the production line malfunctions, it may continue running unnoticed, resulting in an entire batch of defective products. IoT-driven preventive maintenance can help prevent such quality control issues in manufacturing.
3) Improves Inspection Accuracy
Digitalization has considerably improved the industrial industry. Technology has increased productivity by 40% in the last two decades. While business leaders may be hesitant to incorporate artificial intelligence into their IoT strategy, it could be worth the effort.
When combined with AI, IoT technology has the potential to augment manual work and decision making. A machine learning system placed into a production line sensor can use the data it collects in real-time to inspect more items than a human ever could.
4) Detects Defects
Internet-connected computer vision systems can spot faults in real-time and automate inspections. They can check a product’s weight, dimensions, and integrity when combined with sensors. They may send images to a worker’s station if they detect an anomaly, allowing for fast corrective action.
5) Improves decision-making.
The longer manufacturers use IoT technology, the larger their dataset will be. They can compare their previous information with the data points they record in real-time for enhanced visibility into their quality control procedures.
Over time, they will be able to determine 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 actions.
Quality control is meticulously documented, and business leaders generally consult these records before deciding whether to adjust manufacturing lines. Realistically, the time between receiving and acting on data might impair their efficiency and fault rate.
IoT and AI can automate human administrative duties in quality control by initiating a post-analysis response. They can automatically initiate corrective and preventive action if they detect a measurement that exceeds a predefined threshold.
Instead of waiting weeks or months to execute changes, this technology can make modest tweaks in real time as it collects fresh data. This dynamic decision-making process can significantly improve manufacturers’ flexibility.
Also See! The Role of IoT in Industrial Automation in 2024
7) Identifies Human Error
Wearables that are connected to the internet can track the movements and locations of workers, boosting production line visibility and defect traceability. Management can use these data-driven insights to identify cases where human error is the primary cause of anomalies and inefficiency.
By 2024, there were about 18.8 billion IoT connections globally. This technology has grown so common and accessible that investing in wearables for a full workforce would not be prohibitively expensive, especially for smaller businesses.
8) Improves Defect Traceability
By combining interconnected technology with solutions such as radio-frequency identification tags or QR codes, every part can be traced. This manner, corporate leaders can correlate every IoT-generated data point to an actual machine or product. Since some flaws take time to manifest, these documents would be critical for compliance and quality assurance.
9) Makes Tests Exhaustive
Most facilities install quality control technology at specific points along the production line. However, even those with various systems across the raw materials and final inspection processes miss out on key insights because they don’t have entire visibility.
Embedding IoT sensors throughout the production line allows manufacturers to continuously check products rather than examining them at different stages, making inspections more thorough. This allows them to determine when anything has a flaw.
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 complete quality control because it provides them a novel advantage
Looking for? Top IoT Solutions for Industrial Safety
10) Proactively prevents faults.
Many faults aren’t evident. Sometimes, a subtle design fault causes to abnormalities and failures. Because manufacturers use those specifications as a baseline for everything they make, they may unintentionally produce defective batches and struggle to identify the root cause.
When combined with computer vision technology or AI, IoT sensors can identify potential issues early in prototyping. This approach, decision-makers can eliminate everything leading to early failure or raise the risks of faults without wasting time or money.
Final Say
By incorporating IoT into existing quality control processes, manufacturers may effectively limit defects, decrease waste, and enhance customer satisfaction. Furthermore, the integration of AI into these systems has the potential to significantly reduce labor costs and greatly enhance efficiency.
