The problem with traditional surveillance camera systems is that they are typically used only passively or reactively, i.e., video images are inconsistently viewed and—more often than not—after a safety, security, or quality-related event has taken place.

Five Ways Visual AI Increases Profitability in Manufacturing

Brian Kenneth Swain | Sparkcognition

In our recent webinar, Visual AI: Five Steps to Increase Profitability in Manufacturing, we highlight the impact of SparkCognition Visual AI Advisor on productivity and profitability in the manufacturing sector, focusing on the wide range of capabilities visual imaging technology brings to the manufacturing floor, including product quality assurance, worker safety, and security.

 

A new approach to overcome everyday business challenges

Leading the webinar, VP of Sales Cory Rhoads began by noting the various challenges facing businesses in general and stakeholders in particular, be they customers, employees, supervisors, shareholders, etc. These challenges include operational ones like productivity, equipment maintenance, cybersecurity, and health, safety, and environmental (HSE) issues affecting employees. And, of course, all these challenges must be addressed while keeping sight of requisite performance goals like revenue and profitability. Pointing out specific examples of costs associated with accidents and equipment failures, he cited over $500K in cost for every hour of equipment downtime, as well as $120K for each workplace accident.

Addressing these challenges has led to digital disruption in business—a wave of technology-driven activity that includes everything from robotics and big data to 3D printing, artificial intelligence (AI), and machine learning (ML). Rhoads used this context to segue into the Visual AI arena and discuss how the technology works, including the various applications that it makes possible, typically using camera infrastructure companies already have. In fact, there are more than one billion surveillance cameras in use around the world today, any one of which can readily provide imagery for use in a visual AI application.

 

How SparkCognition Visual AI Advisor proactively identifies problems

The problem with traditional surveillance camera systems is that they are typically used only passively or reactively, i.e., video images are inconsistently viewed and—more often than not—after a safety, security, or quality-related event has taken place. Even if they are monitored around the clock by safety personnel, studies show that humans typically lose more than half their ability to focus attention on a video feed after just 18 minutes.

Visual AI Advisor, by contrast, turns this approach on its head by proactively analyzing real-time video feeds and delivering alerts the moment problems begin to occur, be it a fire starting, an employee moving too close to equipment, or product quality on an assembly line suddenly becoming sub-par.

And Visual AI Advisor is more than just perpetually diligent. It is also eminently flexible in its range of applications. Regardless of whether monitoring activity in a warehouse, a factory assembly line, or a loading dock, and irrespective of video type (CCTV, drone, etc.), the system can deliver alerts not only on impending accidents or quality problems but also near misses that frequently go unreported, but which are indicative of future, more serious problems. By relying on visual technology to surveil activities automatically on a 24/7 basis, employees can instead focus on higher-value decisions and activities that drive greater profitability and productivity.

Focusing on the safety benefits of Visual AI Advisor, Rhoads said, “Not every incident is documented, and companies are only aware of how they’re doing safety-wise based on what gets reported. But imagine an environment where near misses are captured, and unsafe acts are alerted on all the time, regardless of whether or not a manager actually ever sees it happen.” Proactive safety enhancement can be provided by sending alerts to safety managers, wearables on a team member, or even to a first responder. In the case of quality problems, alerts can be provided to managers immediately before long runs of inferior products are manufactured, thus reducing waste and enhancing productivity. Whether talking about product quality or safety/security enhancement, Visual AI Advisor brings a new level of awareness and responsiveness that is simply not possible with manual human surveillance.

Explaining the frictionless path to deploying Visual AI Advisor, Rhoads noted, “With over 125 available use cases and our low-code/no-code environment, we’re able to get a new user up and running extremely quickly and with little to no data science expertise required on the client’s part, resulting in a near-immediate ROI.” Also, for organizations with privacy concerns, employee anonymization is easily achieved by blocking out team member faces, ID badges, etc.

 

Visual AI for the real world: Five keys to boosting profitability in manufacturing

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

  • Automatically alerting when employees come too close to rotating/heavy machinery or move beneath suspended loads—shutting down the machinery if appropriate.
  • Identifying cases in which vehicles and employees get too close together.
  • Flagging cases of poor quality control, e.g., under or over-cooked potato chips on an assembly line.
  • Identifying individuals who, for training or other reasons, are not authorized to be in certain areas of a facility.
  • Alerting employees (and their managers) when they improperly lift boxes or other objects, i.e., creating injury hazards to themselves.

 

Summarizing his remarks, Rhoads noted the five ways Visual AI Advisor can contribute to driving greater profitability in manufacturing:

  1. Augment human capital with real-time actionable insights.
  2. Avoid injuries, near-misses, and unsafe acts proactively.
  3. Automate asset and product inspection to increase quality, reliability, and efficiency.
  4. Redesign work areas to improve safety and efficiency.
  5. Enhance teamwork and training with unobtrusive monitoring and practical reporting.

 

Conventional thinking sometimes suggests that safety issues and product quality problems will inevitably happen—problems that have real quantifiable costs, both financial and human. But, with the current state of the art in artificial intelligence and machine learning, such events do not, in fact, need to happen. Visual AI Advisor is a practical and easy-to-deploy tool that helps prevent such occurrences by enabling managers to maintain awareness of hazards and problems and to take proactive action to mitigate adverse outcomes.

Watch the free webinar, Visual AI: Five Steps to Increase Profitability in Manufacturing, for more insights and real-world case studies. As always, we invite you to contact us with any questions or to schedule a demo for your organization.

 

The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow

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