PowerArena uncovers human factors causing production line bottlenecks, boosting productivity and quality

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Dave Chu, PowerArena marketing director

Raising productivity and quality is the top priority when manufacturers of all sectors endeavor to boost revenue and competitiveness. To manufacturers, whether in traditional manufacturing or high-tech industries, the most effective way to raise productivity is to constantly look for bottlenecks in the production process, find the causes, and resolve them. By harnessing the power of data, manufacturers can get to the root of the bottleneck and figure out a solution. PowerArena, a startup specializing in deep learning, has developed core algorithms, coupled with big data analytics and prediction, to digitize and visualize human factors that may have been difficult to detect in the past and thereby help manufacturers enhance their overall equipment effectiveness (OEE).

According to PowerArena marketing director Dave Chu, humans are still essential workers in manufacturing today, especially on assembly lines. Despite the transition to data-driven decision-making, the complexity of sorting and tracking the massive and intricate process line data makes it challenging for manufacturers to improve production quality and efficiency. It is particularly difficult to quantify the human factors entangled in the data. AI is the solution to these problems.

Human factor data are gathered from workers performing tasks on the assembly line. Chu commented that with the rapidly increasing IoT popularity, manufacturers are able to collect complete production equipment data. However, they still have difficulty uncovering the underlying cause of the bottleneck on the process line and in the human workflow. For example, if a process step of a PCB assembly station taking too long is found to be the main reason affecting the station's productivity, current IoT systems can only collect data from the entire station with no detailed information for the managers to make decisions and improve the efficiency.

Leveraging AI technologies, PowerArena's solution analyzes the workers' movements captured on surveillance cameras commonly found on factory floors and then helps factory managers identify factors hindering productivity such as overly complex procedures and unhandy tools. It also makes use of the factory's existing mechanisms to help resolve the bottleneck and subsequently connects to the backend ERP system to do the production efficiency analysis for every work order to thereby raise productivity.

Not only can PowerArena's solution raise productivity, the same implementations can also be used to improve quality. For example, a Taiwan-based motorcycle manufacturer recently adopted PowerArena's AI system to monitor whether its production equipment thoroughly lubricates the gears and exactly completes each procedure to guarantee its products are of consistent quality and up to standard. If any step or task is not performed exactly according to the SOP, the system will raise an alert to the workstation manager. PowerArena's solution will help the manufacturer uphold its brand reputation and lower future repair and maintenance costs, enabling a win-win situation for the manufacturer and motorcycle buyers.

Chu added that manufacturing industries have been able to boost production efficiency thanks to rapid advances of technologies and process techniques. However, after they have increased productivity and quality to a certain level, it becomes significantly more challenging and costly to keep raising the bar. PowerArena's solution makes use of AI to find the human factors in the details and clearly identify the problems so as to effectively bring production line output and quality to a new level.

To support manufacturers' edge computing needs, PowerArena's AI system is based on an on-premise cloud hybrid architecture, combining the strength of Amazon Web Services (AWS), which includes Amazon Route 53 and AWS Fargate for enhanced system performance. Amazon Route 53 is primarily used for domain name system (DNS) routing. AWS Fargate is used for building container images. Those are ways of optimizing cross-department collaborations within an organization while satisfying manufacturers' requirements on confidentiality and instantaneity.

PowerArena's AI-enabled smart manufacturing solution is a powerful tool for production line engineers. It has been adopted by multiple Taiwan-based heavyweight manufacturers, including Lite-On, Wistron, and Delta Electronics, to largely boost their productivity and quality. Chu noted that in line with the AI in manufacturing trend, PowerArena will continue to strengthen its system performance to help users uncover human factors in the details and optimize the value of assembly line workers.

In comparison to traditional management, AI vision enables accuracy, proactivity and instantaneity while eliminating human errors and data gaps

In comparison to traditional management, AI vision enables accuracy, proactivity and instantaneity while eliminating human errors and data gaps
Photo: PowerArena