Human error in manufacturing can lead to catastrophic and costly events, with reportedly 23% of unplanned downtime in manufacturing as a result of human error, more than most other industries. It’s getting higher. Adam Bennett, his manager of Enterprise Sales at Matroid, discusses how advances in AI like CV AI can greatly improve manufacturing processes.
As manufacturers face seemingly out-of-control obstacles such as inflation and supply and demand issues, reducing human error is one area where implementing computer vision artificial intelligence (CV AI) can improve.
And businesses are looking at the impact and effectiveness of AI on their bottom line.according to Recent research More than 80% of companies surveyed by Deloitte believe AI has and can have a “practical and measurable impact,” and almost 30% of companies surveyed believe AI is already making a difference to their organization. We believe that it is an asset of
Let’s take a look at what CV AI is and the manufacturing areas where CV AI can help companies reduce costs and avoid costly mistakes.
Read more: 6 Reasons Manufacturers Should Adopt Employee-Centered CSR Programs
What is computer vision AI?
CV AI leverages the latest deep learning technologies based on artificial neural networks such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN).
It is essentially a computer that processes and understands visual data. CV AI learns from collected visual data to provide predictive and actionable insights on images, videos, and live streams. Camera-independent CV AI detects defects, objects, anomalies, actions, and events and localizes these detections.
How can CV AI help the manufacturing industry?
The benefits of using CV AI in manufacturing are enormous and are not limited to assembly lines. Perform inventory tracking, collect data analytics, improve safety assessments, and strengthen security measures—all areas critical to the success of your manufacturing process.
But to understand the impact of CV AI, let’s see specifically how the process can be improved.
- detection: CV AI enables camera systems to detect and classify various objects such as shape, size, color, texture, defects, anomalies, people, actions and events down to the microscopic level. costly event.
- Deeper understanding: It’s no longer enough to detect pass/fail when inspecting things. CV AI can accurately label the type of detection, such as weld defects that may involve porosity, spatter, or burn-through. When welding professionals are notified of these detections, they or the machine can adjust automated operations more quickly instead of making adjustments many cycles later.
- collaboration: CV AI helps manufacturers get to the root cause of various challenges faster. Create cross-functional team collaboration by enabling key players to detect and manage defects in real time.
- protection of knowledge: Employee turnover is a concern, so CV AI learns and retains visual inspection requirements in complex production environments, similar to human QC inspectors. This eliminates the risk of valuable knowledge being leaked. Retaining that tribe’s knowledge also influences the onboarding of new recruits. This saves weeks or even months of training time.
Where does CV AI cut costs for manufacturers
How do these enhancements translate into cost savings results? CV AI has been proven to impact:
Reduce rework costs: CV AI will enable manufacturers to apply advanced inspections in areas of unstructured environments that lack digital traceability and were previously only inspectable by highly trained operators. . By inspecting critical quality control points, providing digital traceability, and allowing rework early in the process if necessary, CV AI has been shown to save millions of dollars in annual rework costs. It has been.
Improved efficiency: CV AI can go beyond traditional machine vision to do more than detect defects and objects. It can also detect people, their actions, and even events in images and videos. Manufacturers are benefiting greatly by leveraging CV AI as a continuous improvement tool to improve line balancing and labor utilization in manual assembly processes. Constant capture provides insight into anomalies and trends/patterns over the week, month or season. Firms better understand production costs, determine Kaizen, and report shared efficiency improvements of over 15%.
Saving scrap loss: Scrap in manufacturing is a serious and costly problem. Too many failed materials can negatively impact a company’s profit margins. Inspection and monitoring in production can reduce company scrap and save millions of dollars in normalized annual losses.
How to know if you need CV AI
To understand if CV AI can help your manufacturing process, you should ask yourself the following questions:
- Are the challenges faced in the manufacturing process visualized by some form of camera technology or spectrum providing images and video?
- QA/QC, manual labor, safety, security, etc. Which aspects of your operations can benefit from image or video detection and analysis?
- What kind of insights would you like to get from CV AI?
- What systems (machines, MES, or ERP) will CV AI be integrated into so that detection and analysis can take action?
- Do you have a one-off need or can it span multiple operations?
- Will this platform make it easier for SMEs to build their own detectors without being data scientists?
- If your current team member changes jobs, can other members, such as QC inspectors and industrial engineers, easily take over?
By looking at these areas of the manufacturing process, you can determine how and where CV AI is most beneficial.
Read more: How digital technology can improve productivity in manufacturing operations
where to start
If you have determined that your organization’s manufacturing processes can benefit from CV AI, there are simple steps you can take to get started with this technology that you should consider to make sure it’s right for your organization. is needed.
- Talk to a CV AI platform company that can identify your interest, application, and goals for using CV AI.
- Explore PoC trials to learn how technology can help and integrate it into your systems and operations.
- Enable cross-functional departments to complement their operations by allowing them to build, test, deploy, and manage pre-built custom detectors to suit their needs without being a data scientist with a degree. increase.
- Ensure the right deployment mode for your needs: cloud (public/private), on-premises, edge
- We make sure that the CV AI platform is camera technology agnostic and works with any technology. Application needs vary across operations and may require different imaging techniques and resolutions.
- Use applications that can be integrated into your current system such as PLC, SCADA, MES, WMS, ERP, database, security.
- Partner with proven talent on the track for deep learning AI. Industry-leading engineering delivers maximum benefits to manufacturers utilizing this technology.
What are some examples of how AI has significantly improved manufacturing processes? Share with us Facebook, twitterWhen LinkedIn.
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