Failure in production is often fatal. Monitoring production processes solely by humans may result in errors being detected too late, or not being detected at all. Wherever humans are working in production, mistakes are inevitable: first humans can only focus on a few certain things. Especially for complex manufacturing processes, it can be hard to keep track of potential warning signs that forecast problems that could occur. Production workers may not diagnose the right problem due to a lack of knowledge or experience, even if they register potential warning signs.
The High Cost of Human Error in Manufacturing
A study performed by Vanson Bourne concludes that 23% of production losses and unplanned downtime in manufacturing are the result of human error. Experts named it the number one reason for production losses in manufacturing. Because of the variety of machinery and equipment that requires intervention and maintenance by service engineers and technicians, the manufacturing sector has higher levels of human error. As production gets more and more complex, error prediction and prevention become harder for humans. Various sensors can collect real-time measurement data to monitor factors relevant to maintenance, such as vibration or optical deviations.
AI’s Role in Improving Manufacturing Efficiency through Data Management
Even if humans capture this kind of data, they may have problems overlooking all the information. It can be hard to grasp all potential manufacturing problems or predict future failure implied by the data – simply because the Data can be overwhelming and patterns in the Date might be hard for humans to detect.AI can monitor a large amount of sensory input to cope with all the data collected by sensors relevant for maintenance. With all that information, it can identify the state of machinery and equipment for manufacturing and predict upcoming manufacturing problems. This way, AI can reduce the number of human errors in predicting what failure might occur and when it will happen – which also lowers maintenance costs. Its accuracy in interpreting the Data can help to improve the overall safety and efficiency of the manufacturing process.
The combination of NOVO AI’s sensory systems can help gather the information relevant to the maintenance of your production. Our AI-driven maintenance prediction can handle the amount of Data and monitor the condition of the manufacturing process, predict maintenance, detect production failure, and even forecast the exact time when those things will occur.
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