If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
From food to cars to complex manufacturing machinery, quality is a top concern of manufacturers. Factors such as safety, efficiency, and reliability affect product quality and ultimately influence customer satisfaction. Sourcing, design, testing, and inspection all play a crucial role in ensuring products meet the bar when it comes to quality. Product inspections at early stages in the production cycle help reduce risks and cost. While inspections can be conducted at any point throughout the production process, the goal is to identify, contain and resolve issues as quickly as possible.
Few areas of industrial technology today remain untouched by artificial intelligence (AI). Fromcontrollersto ERP tofood safetyandrobots, AI is changing the technologies we use to run manufacturing and processing facilities in subtle and not-so-subtle ways. One application with a big potential to benefit from AI is quality control software. The use of smart cameras and related AI-enabled software are helping manufacturers achieve improved quality inspection at speeds, latency, and costs beyond the capabilities of human inspectors. And the timing of the arrival of these smart camera technologies is fortuitous, give the social distancing requirements of COVID-19.
SICK has launched a suite of Deep Learning apps and services to simplify machine vision quality inspection for challenging components, assemblies, surfaces or food produce, especially those that have previously defied automation and remained distinguishable only by human inspection. SICK Deep Learning reduces set-up time and cost by enabling Artificial Intelligence image classification to run directly onboard SICK smart devices. With Deep Learning, programmable SICK devices take decisions automatically using specially-optimised neural networks and run inspections that would have previously been extremely challenging or simply impossible to achieve in high-speed automated processes across many different industries. Developed with user-simplicity at their core, SICK's Deep Learning products cater for a wide range of needs and skill levels. The Deep Learning Starter App is designed for easy-set up by entry-level users, while the ready-to-use Intelligent Inspection Sensor App provides quick and easy integration with a large set of configurable machine vision tools.
Following the devastating Black Summer bushfires, New South Wales National Parks and Wildlife has been using drones to assist with post-fire recovery. Speaking as part of the digital DroneDeploy Conference this week, NSW National Parks and Wildlife chief remote pilot Gareth Pickford explained that using drones to assist various stakeholders within the NSW government to assess the damage caused by bushfires last summer is a cost-effective and efficient way to collect data. "The types of data that we actually were planning on getting out in the field was around fire severity areas that were affected by fires, not just in local parks that are open to tourism, but also wilderness areas, which are natural habitats to certain species that may have been affected by fire," he said. "We wanted to understand how much they were going to be affected by the fire, and its post-effects." Some of the specific activities that the drones were used for included ecology assessments, which are live snapshots and maps of different terrains across the state; multispectral mapping to examine the types of vegetation that either survived or were destroyed; archeological analysis of historical sites; and evening thermal scanning to assess the animal population in certain areas, particularly in remaining vegetation patches.
Few areas of industrial technology today remain untouched by artificial intelligence (AI). From controllers to ERP to food safety and robots, AI is changing the technologies we use to run manufacturing and processing facilities in subtle and not-so-subtle ways. One application with a big potential to benefit from AI is quality control software. The use of smart cameras and related AI-enabled software are helping manufacturers achieve improved quality inspection at speeds, latency, and costs beyond the capabilities of human inspectors. And the timing of the arrival of these smart camera technologies is fortuitous, give the social distancing requirements of COVID-19.
Engineering giant Rolls-Royce has made an ethical artificial intelligence (AI) 'breakthrough', which it believes could contribute to gaining society's trust in the technology on the path to'Industry 5.0'. The firm has unveiled a workable, peer-reviewed AI ethics framework, which is a method that any organization can use to ensure the decisions it takes to use AI in critical and non-critical applications are ethical. The framework, which has been reviewed by several big tech firms -- as well as experts in the automotive, pharmaceutical, academic, and government sectors -- will be published under Creative Commons license this year. The framework includes a step-by-step process for ensuring the outcomes of AI algorithms can be trusted. A five-layer checking system focuses on the outputs of algorithms, not the algorithms themselves, which are constantly changing.
Drone startup Skydio today announced the U.S. Federal Aviation Administration (FAA) has granted the North Carolina Department of Transportation (NCDOT) statewide approval to fly Skydio drones beyond visual line of sight to inspect bridges. Skydio, which describes the waiver as the first of its kind, says the NCDOT will be able to conduct maintenance activities without the use of visual observers like trained pilots or staff. A recent study by the American Association of State Highway and Transportation Officials found that taxpayer cost per bridge inspection can be reduced 75% by switching from traditional methods to drones. The Minnesota Department of Transportation found that using drones for bridge inspection offsets some or all of the costs, depending on the bridge configuration and location, with a trial of drone-assisted inspections saving an average of 40% over traditional methods and providing ostensibly superior data and reporting. Going forward, the NCDOT's inspectors can send Skydio 2 drones to inspect critical structures below bridges in North Carolina instead of conducting rappels or using "snooper trucks."
A study by McKinsey & Company found that AI-driven quality testing can increase productivity by up to 50% and defect detection rates by up to 90% compared to human inspection. Though machines with automated optical inspection (AOI), powered by machine vision, have replaced most of the manual processes in the modern assembly line, quality control still remains a huge and costly challenge. The European Commission claims that in some industries 50% of production can be abandoned due to defects, and the defect rate can reach up to 90% in complex production environments. The critical limitation with machine learning AOI systems is in disclosing surface defects where even a slight variant (often invisible to the human eye) can hamper the entire production run and render hundreds to thousands of products useless before the defect is discovered. The economic impact can be devastating.
RAILWAY AGE, SEPTEMBER 2020 ISSUE: Whether it's the track structure or the equipment that operates on it, there are many things that the naked eye cannot readily see. Increasingly, machine vision technology is becoming the best way to identify potential flaws before they lead to failures. "The various machine vision technologies deployed detect thousands of conditions each year that could potentially lead to accidents," says Robert Coakley, Director of Business Development, ENSCO Rail. Compared to manual visual inspections, he says, autonomous machine vision offers advantages of speed, reduced track occupancy, inspection frequency and consistency. The equipment is installed on revenue service trains, can perform inspections at track speed and does not require the additional occupancy of a hi-rail vehicle.