Redefining Quality Control with AI-powered Visual Inspection for Manufacturing

Emerging technology — from the introduction of assembly lines to the Internet of Things — has always defined manufacturing.

With the creation of computers and early automation came traditional machine vision, in which machines analyze photos of parts and components for defects based on a set of human-defined rules. While it reduces human error, traditional machine vision lacks the capacity to solve for pain points like complex defects and changing environments.

Today, more sophisticated artificial intelligence (AI), including machine learning (ML) and deep learning (DL), allows manufacturers to use AI-powered visual inspection to enhance quality and reduce costs. But even now, only 5% of manufacturing companies have a clearly defined strategy for implementing AI.

Companies need strategies to overcome challenges in visual inspection, which still relies heavily on human inspectors or inflexible rules-based machine vision. The cost of sending defective pieces to customers — both in reputation and in recalls — isn’t sustainable in a competitive global environment.

The right AI platforms offer tools that can enhance quality control and cut costs — after users tackle key obstacles.

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Accelerate AI Adoption

Landing AI’s industrial AI platform consists of a suite of interconnected tools that enables you to build, deploy, manage and scale AI solutions for visual inspection in an end-to-end workflow.

Designed from the bottom up to enable manufacturers to take projects from concepts to scalable solutions with speed, LandingLens minimizes customization and scaling challenges. While AI models are unique, leveraging universal tools can expedite complex projects. Built for evolving data, LandingLens is comprised of a suite of tools to automate machine learning for industrial vision.

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2020 Global AI-Powered Vision Inspection Enabling Technology Leadership Award

As the AI tide takes over all industries, Landing AI’s most innovative, effective, and easy-to-use AI-powered vision inspection platform enables manufacturers to achieve high-quality output. Landing AI offers immense value to its customers through its robust and adaptive AI algorithms, which is constantly improved by some of the best technical minds in the industry and seamlessly updated at the customer site through the cloud. The visionary leadership of Dr. Andrew Ng, the highly driven techno-commercial team, strong vision inspection domain knowledge, and resilience toward ensuring customer success well position Landing AI to remain a market leader in this space.

With its strong overall performance, Landing AI has earned Frost & Sullivan’s 2020 Enabling Technology Leadership Award in the global AI-powered vision inspection industry.

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2020 State of AI-Based Machine Vision

Of the many use cases in manufacturing, visual inspection—a task that involves using human eye or machine vision to verify if a product is free of defects or if parts are correctly assembled—is well-suited for AI. According to a study by McKinsey & Company, AI-powered quality inspection can increase productivity by up to 50% and defect detection rates by up to 90% compared to manual inspection.

Given these benefits, have businesses started using AI in visual inspections? If so, what is the level of adoption, and what are the challenges? These questions and more drove Landing AI, an industrial AI company, and the Association for Advancing Automation to launch this survey on the state of AI-based machine vision.

The survey polled 110 companies from the manufacturing and machine vision industry with both multiple and single choice questions. Respondents who took the survey perform a variety of roles and include C-suite executives, automation engineers and plant managers. One main takeaway is that businesses have high confidence in the effectiveness of AI, and a growing number of companies are already using deep learning-based machine vision for automated visual inspection.

In this report, we will highlight four key findings, detail those discoveries, and provide analysis.

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Whitepaper: Process Orchestration as the Pathway to Customer Experience Innovation

There is plenty of talk about the need to deliver a differentiating experience for both customers and employees. Enterprise leaders now understand the criticality of the experience in their bids to win over expectant customers and to attract and retain employees. But how can technology play a part and make an impact?

This Intellyx whitepaper highlights how businesses can better link and coordinate a vast collection of technologies, processes and people to drive winning customer and employee experiences.

The whitepaper: Process Orchestration as the Pathway to Customer Experience Innovation uncovers:

  • Ways enterprise leaders can get “past the glass” to create genuinely immersive and integrated experiences
  • How to tame the complexity of multiple technologies, processes and people and operationalize
  • How to connect across and through the enterprise with automation

Download the Intellyx Whitepaper: Process Orchestration as the Pathway to Customer Experience Innovation for free today.

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eBook: Disrupting the Legal Industry

How 5 Legal Organizations Drive Process Excellence

Technology is disrupting the legal industry. In a business where time literally is money, companies embracing technology and automation will thrive—while those that don’t, will continue to struggle. This eBook highlights five legal case studies that demonstrate the real-world value of process automation.

Download the eBook to learn how each of these organizations leverage technology to solve their unique business problems, as well as ten best practices you can use to transform your legal processes.

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Infographic—Top 6 Processes All Legal Teams Should Automate

Learn why all legal teams should be automating these key processes

Technology is changing the legal profession. If your company is not looking at automating these six core legal processes, you can be sure your competitors are. Additionally, client’s expectations for an efficient, streamlined process continues to increase.

This short infographic outlines six core processes every legal team should be automating and helps you understand the reasons for automating those processes.

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Transformative Automation: Balancing Power and Simplicity

In a post-pandemic world, businesses are still struggling how to automate complex and mission-critical processes. Companies know they need transformative automation—but how and where to start? It is the “how” that continues to challenge most businesses. The digital “visionaries” like Netflix, Amazon, Apple, Google, and Facebook, have all achieved incredible outcomes— So, how can you?

IDC Research explores how a modern approach to business automation can enable businesses of all kinds to grasp the nettle of transformation and work within their constraints to execute at scale.

In a recent report, Transformative Automation: Balancing Power and Simplicity, IDC Research uncovers:

  • The weakest links in a business for delivering transformation and how to overcome the challenges
  • What the key obstacles are for better enterprise decision making
  • How to drive change in digital products, services, experiences and processes
  • What you need to create a new business automation toolkit

Download the IDC Research Infobrief: Transformative Automation: Balancing Power and Simplicity for free today.

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The Power and Peril of Microsoft 365

The adoption of Microsoft 365 brings a mixture of power and peril. Organizations looking solely at the strong benefits of Microsoft 365 may not recognize some of the risks that the suite introduces. This document provides a brief overview of some of the issues organizations should be aware of when adopting Microsoft 365.

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Automating Information Management

The exponential growth of data is driving efforts to reduce redundant, obsolete, or trivial data, also known as ROT. Nyxeia products simplify ROT reduction, with a single interface that scans documents across the network. Using natural language processing (NLP), text pattern matching, and context matching, Nyxeia analyzes metadata as well as document text to identify duplicates, saving valuable time, money, and tedious manual effort.

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Machine Learning and Natural Language Processing

Governing terabytes or even petabytes of data requires automatic classification. Discover uses artificial intelligence to enhance metadata, create structured information out of unstructured data, and rapidly tag and classify millions of documents automatically, wherever they live. This enables organizations to mitigate risk, enhance efficiency, and lower IT costs.

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Open Source Security And Risk Analysis Report

Synopsys helps development teams build secure, high-quality software, minimizing risks while maximizing speed and productivity. Synopsys, a recognized leader in application security, provides static analysis, software composition analysis, and dynamic analysis solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open source components, and application behavior.

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Navigating the Open Source Risk Landscape

Open source use isn’t risky, but unmanaged use of open source is.

Open source software forms the backbone of nearly every application in every industry. Chances are that includes the applications your company develops as well. If you can’t produce an accurate inventory of the licenses, versions, and patch status of the open source components in your applications, it’s time to assess your open source management policies.

This paper provides insights and recommendations to help organizations and their development and IT teams better manage the open source risk landscape. It covers:

  • Open source license risk and the need to identify and catalog open source licenses
  • Security risk that comes with open source use and inadequate vulnerability management
  • Operational open source risk, version control, and the dangers of using inactive components

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The DIY Guide to Open Source Vulnerability Management

According to SAP, more than 80% of all cyber attacks are happening on the application layer,1 specifically targeting software applications rather than the network.

Hackers take the easiest path when determining exploits and choose applications that offer the best attack surface opportunities. Those opportunities are generally created by unpatched or outdated software.

For example, Heartbleed, a dangerous security flaw, critically exposes OpenSSL, an open source project used in hundreds of thousands of applications that need to secure communications over computer networks against eavesdropping. Yet 56% of all OpenSSL versions that Cisco Security Research examined in its 2015 security report2 were still vulnerable to Heartbleed, more than two years after the Heartbleed vulnerability was first disclosed and a patched version issued.

This illustrates the difficulty organizations have in inventorying and managing open source components rather than a lack of security diligence. Without a comprehensive list of open source components in use, it is nearly impossible for any organization to identify specific applications that use vulnerable components.

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