The image recognition function of artificial intelligence (AI) is becoming more and more powerful. Face recognition, license plate recognition, and object recognition are not uncommon. In the fields of smart manufacturing and warehousing logistics, more and more manufacturers are beginning to introduce AI technology into more special applications.
More and more manufacturers are beginning to introduce AI technology into more special applications, such as analyzing the work rhythm and production capacity of production line employees, identifying defective or defective products, and using the identification of product outer boxes to speed up inventory and inspection procedures, they have significantly improved productivity from AI computer vision and data management. Introduce AI into the management of the work progress of the employees on the production line, grasp the actual working conditions of the production line in real-time, identify the number of production objects at each workstation, understand the working rhythm and cycle operation time of each operator, and digitize and analyze the images. After formulating the standard production procedure, if there is any discrepancy in the operation sequence, the AI system will immediately identify and issue a warning, to reduce errors and time-consuming manual quality inspection processes, improve productivity and optimize the production process, and even actively provide information through AI. Production scheduling recommendations for manufacturers.
What is Artificial Intelligence (AI)?
Artificial intelligence is the electricity of the new era, and there will be no modern industry in the future that has nothing to do with artificial intelligence. Artificial intelligence (AI) has illuminated the prospect of a new generation of technology. Since then, people have quickly used huge amounts of data to analyze and carry out machine learning to point to the best decision-making.
- Project: Accurately forecast and plan to complete the best production plan.
- Produce: Maintain high-quality, high-efficiency production processes.
- Promote: Accurate target sales and market analysis.
- Provide: Improve customer satisfaction and drive sustainable operation.
Has Artificial Intelligence been Used and Changed Life Scenarios?
The application of artificial intelligence is still booming, and the business model is gradually maturing. Now it has practiced and changed our lives through digital services.
- Artificial intelligence AI and smart medical applications:
In the medical and health industry, AI technology has begun to assist clinical decision-making and disease judgment and has further entered the fields of preventive medicine and precision medicine. In addition to reducing the workload of medical care and reducing the error rate, it also overcomes medical challenges that humans cannot solve.
- Artificial intelligence AI and smart transportation applications:
Artificial intelligence can enhance the integration of information such as vehicle identification, signal management, and traffic safety management through image recognition technology. At present, the application of artificial intelligence in Taiwan's transportation has developed into areas such as self-driving cars, traffic flow calculations, road safety warnings, and road network optimization.
- Artificial intelligence AI and other smart industry applications:
In daily life, the voice recognition function used by smart speakers and AI assistants in mobile phones is common. Video and audio algorithms are recommended for you in video streaming. AI customer service recognizes customer thoughts and proposes personalized responses, etc. AI artificial intelligence applications have long been ubiquitous, and continue to improve your quality of life.
In-depth Visual Identification, Master Production Line Labor Data:
At first, it started from the application of AI imaging in smart cities, but later some manufacturers reported that there was a great demand in the production process, and began to introduce AI depth recognition and insights into it. Through behavior recognition, the working status of operators on the production line can be quickly analyzed. The pick-and-place action that occurs in most manufacturing industries, or the analysis of how long a process takes to complete. In addition to finding out the bottleneck site on the production line, if the time is too long, you can also find out the root cause of the problem and seek improvement in time. It can also be connected to the ERP system to analyze the production efficiency of each order. Introduced in labor-intensive production processes, labor costs can be significantly reduced after finding production bottlenecks through data mining through AI images.
Accurate Screening with AI Quality Control Testing:
In the past, the link of product quality control inspection that relied heavily on manual work is now beginning to rely on AI image recognition technology to complete the automated inspection process. Takes AI and deep learning as the core deeply cultivates intelligent image analysis technology and applies it to the application of smart factories and industry 4.0. It helps factories improve the yield rate of quality inspection through Automated Optical Inspection (AOI) technology, which can reduce more than 70% screening rate, while greatly reducing labor costs and improving quality inspection efficiency. In the past, defect detection and quality control operations were mostly done manually. When employees concentrate on visual inspection work for a long time, the efficiency will inevitably decrease, resulting in a situation that affects the quality inspection yield. Although some industries such as the semiconductor industry have used optical inspection for quality inspection, 91ÊÓƵ¹ÙÍøever, it does not have deep learning capabilities through traditional algorithms, and the accuracy is not high, and the industry often spends extra manpower on manual second screening, making manpower and maintenance costs high. AI deep learning technology can be used to assist in product defect detection. Compared with the current naked eye judgment, the efficiency is low and the error rate is high. Through AI optical detection, it can be easily identified, and at the same time, the defect detection status can be recorded in real-time, effectively improving production yield.
AI Shipment Inspection, the Accuracy Rate is as high as 99%:
In addition to helping to improve the manual operation process of the production line, AI image recognition technology is also helpful for the inspection of logistics goods. Using AI to replace the traditional manual barcode scanning or RFID inspection can shorten the inspection time of products. Originally, it may take 5-10 minutes to inspect a batch of products, but it only takes 10-15 seconds to compare with AI image features. Moreover, it can achieve a recognition rate of 99%, which reduces the probability of wrong goods.
Through AI algorithm and analysis, let AI learns to recognize the shape, color, font, and other characteristics of each box of goods. In this way, when the pallet passes by the camera, it can be checked whether all items on the pallet are consistent, saving a lot of time and cost for manual inspection. As the penetration rate of e-commerce and online shopping is getting higher and higher, consumers pay more and more attention to the speed of shipment, brand owners, e-commerce platforms, warehousing industries, and logistics systems. All have to face the challenges of fast shipments and the pressure of logistics, such as the delivery of wrong goods, loss of goods, etc., which will damage the brand reputation and customer satisfaction, and even increase the cost of round-trip logistics. Therefore, under the premise of pursuing efficiency and avoiding errors, more and more manufacturers will adopt shipping video inspection software. If it can be combined with an AI image recognition function, it will add an inspection program and improve the accuracy of shipments.
