Five ways visual AI can improve manufacturing industry profitability

The problem with traditional surveillance camera systems today is that they are often only used passively, that is, people are not consistent in viewing video images, and often in safety, security or following a quality-related event. SparkCognition, a provider of artificial intelligence (AI) software solutions, was highlighted in a recent webinar hosted by manufacturing industry players titled "Visual AI: Five Steps to Improve Manufacturing Profitability." The Impact of Visual AI Consultants on Manufacturing Productivity and Profitability focuses on the wide range of capabilities that visual imaging technology brings to the manufacturing shop floor, including product quality assurance, worker safety and safety protection.

New Ways to Overcome Daily Business Challenges

While hosting the webinar, Cory Rhoads, Vice President of Sales at SparkCognition, began by pointing out the various challenges faced by businesses, especially stakeholders, whether Customers, employees, supervisors or shareholders. These include operational challenges such as productivity, equipment maintenance, cybersecurity and health, safety and environment (HSE) issues affecting employees. Of course, all of these challenges must be addressed while achieving necessary performance targets such as revenue and profitability. He pointed to specific examples of costs associated with accidents and equipment failure, citing equipment downtime costs of more than $500,000 per hour and workplace accidents costing $120,000 per hour.

Addressing these challenges has led to digital disruption in business – a lot of activity driven by new technologies, including everything from robotics and big data to 3D printing, artificial intelligence (AI) and machine learning (ML). Rhoads uses this background to get into the field of visual artificial intelligence and discusses how the technology works, including the variety of applications it enables, often using camera infrastructure that enterprises already have. In fact, there are more than 1 billion surveillance cameras in use around the world today, any one of which can easily provide images for visual AI applications.

How Visual AI Proactively Identifies Issues

The problem with traditional surveillance camera systems is that they are often only used passively, that is, after a safety, security, or quality-related incident occurs, the video Viewing of images is not consistent, and often isn't. Research shows that people typically lose more than half of their attention after 18 minutes of watching a video, even with security personnel monitoring around the clock.

In contrast, VisualAIAdvisor technology revolutionizes this approach by proactively analyzing real-time video feeds and sending alerts when problems start to occur, whether it's a fire, an employee getting too close to equipment, or an assembly line The product quality suddenly dropped.

VisualAIAdvisor is not only always diligent, but its scope of application is also very flexible. Whether its monitoring activity is in a warehouse, factory assembly line or loading dock, and regardless of the type of video (CCTV, drones, etc.), the system can not only alert on impending accidents or quality issues, but also on incidents that often go unreported. The near-misses raised alarms, but were a sign of more serious problems to come. By relying on visualization technology to automatically monitor activities around the clock, employees can focus on higher-value decisions and activities, thereby increasing profitability and productivity.

When talking about the safety benefits of VisualAIAdvisor, Rhoads said: “Not every incident is recorded, manufacturers only know how they operate safely based on reports. But imagine in such an environment , even the smallest of errors will be caught, and unsafe behavior will be constantly reminded, regardless of whether managers actually see it happening.” Proactive safety enhancements can be made available through wearable devices to safety managers and team members. devices and even send alerts to first responders to provide. In the event of quality issues, managers can be alerted immediately before poor quality products are produced for a long time, reducing waste and increasing productivity. Whether talking about product quality or safety/security enhancements, VisualAIAdvisor brings a new level of awareness and responsiveness that cannot be achieved with manual monitoring.

In explaining the frictionless path to deploying VisualAIAdvisor, Rhoads noted: “With over 125 available use cases and a low-code/no-code environment, we are able to get new users up and running very quickly, and clients are virtually No data science expertise is required, resulting in near-instant ROI.” Additionally, for organizations with privacy concerns, it’s easy to anonymize employees by masking team members’ faces, ID badges, etc.

Real-World Visual AI: Five Keys to Improving Manufacturing Profitability

Rhoads went on to detail several real-world use cases, including:

• Automatically sound an alarm when an employee moves too close to rotating/heavy machinery or under suspended load, and shut down the machinery where appropriate.

•Identify situations where vehicles and employees are too close together.

•Flag instances of poor quality control, such as undercooked or overcooked potato chips on the assembly line.

•Identify persons who do not have access to specific areas of the facility due to training or other reasons.

•Alert employees when there is a risk of injury when lifting boxes or other objects.

Rhoads pointed out five ways that VisualAIAdvisor can drive manufacturing to improve profitability:

(1) Enhance human capital with real-time actionable insights.

(2) Proactively avoid injuries, near misses and unsafe behaviors.

(3) Automate asset and product inspections to improve quality, reliability and efficiency.

(4) Redesign the work area to improve safety and efficiency.

(5) Enhance teamwork and training through unobtrusive monitoring and practical reporting.

Conventional thinking sometimes assumes that safety issues and product quality problems will inevitably occur and that these problems have real quantifiable costs, including financial and human costs. However, with the current technological level of artificial intelligence and machine learning, such an event does not actually need to happen. VisualAIAdvisor is a practical and easy-to-deploy tool that helps prevent such incidents from occurring by enabling managers to remain aware of hazards and issues and take proactive actions to mitigate adverse consequences.

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