December 6, 2018  -  No. 096

In This Issue 
Rolls-Royce Selects Uptake's Industrial AI Software to Maximize Availability of its Trent Engine Fleet 
New passenger scanner uses space technology to speed up airport security 
More than an auto-pilot, AI charts its course in aviation 
NATS and McLaren Deloitte to partner on aviation technology 
Aeronautical university to help plan Atlantic County aviation academy 
Exclusive with IATA: adapting VR and AR technology in training 
Enter Air Entrusts Magnetic MRO with Nineteen Boeing 737NG PBH Support 
Entering the Cloud-Based Era of Aviation Maintenance 
CISF to deploy robotic canines at Indian airports 
SpaceX Launches Its 20th Rocket Of The Year, But Doesn't Quite Make The Landing 

Rolls-Royce Selects Uptake's Industrial AI Software to Maximize Availability of its Trent Engine Fleet

CHICAGO - DECEMBER 4, 2018 - Industrial AI and IoT software leader, Uptake, and Rolls-Royce, one of the world's leading industrial technology companies, have joined forces to extend Rolls-Royce's digital ecosystem. Complimenting the company's in-house data science expertise in its R2 Data Labs, an acceleration hub for data innovation, Uptake will demonstrate how its capabilities can help Rolls-Royce implement a data-science-first approach to optimizing the performance of its Trent engine fleet, the market-leading engine family for widebody aircraft. 

Rolls-Royce's TotalCare® service enables customers to maximize the availability of their engines while allowing Rolls-Royce to focus on the most efficient management of the fleet. Working with Uptake to analyze a number of disparate datasets will arm Rolls-Royce with new insights to deliver on its TotalCare® promise to airlines around the world by improving the uptime and availability of their Trent engine fleet. 

"We've been applying analytics as a key part of our TotalCare® services strategy for many years and are always looking to advance our digital approach to improve the quality and value of our services," said Tom Palmer, senior vice president of services for Rolls-Royce's Civil Aerospace business. "With industrial AI and machine learning techniques, we can increase the uptime of our engines and help customers extend the life and value of their critical assets."

"Industrial businesses have an incredible advantage given the massive amount of asset data they have at their fingertips," said Nick Farrant, senior vice president of portfolio and industries for Uptake. "When you take a digitally driven company like Rolls-Royce that continuously raises the bar for customer excellence, and help them put their data to work, the outcomes are undisputable. We are delighted to be working with Rolls-Royce to apply fresh thinking and new technologies to help drive their business, and their customers' businesses, forward."

Built on a foundation of data science and machine learning, Uptake develops solutions that help industrial companies digitally transform their business. The company's latest release of its Asset Performance Management application, Uptake APM, incorporatesthe Asset Strategy Library (ASL), the world's most comprehensive database of industrial content including equipment types, failure mechanisms and maintenance tasks. This rich combination of deep operational and equipment knowledge with predictive analytics provides unparalleled visibility into, and insights surrounding, the entire asset environment, whether assets are connected or not.

Uptake APM is built on top of our industrial AI and IoT platform. This enables companies to put powerful AI and machine learning to work, using our pre-trained data science models and industry-specific content to turn mountains of data into actionable insights that drive financial outcomes.
Learn more at www.uptake.com.

ABOUT UPTAKE
As a leading provider of artificial intelligence and IoT software for industrial companies, Uptake combines data analytics and machine learning with deep industry knowledge to unlock the power of data for the global industrial sector. Headquartered in Chicago, with offices in Silicon Valley, Toronto and Dubai, Uptake works with industrial customers of all sizes across the globe to use software and data to reimagine their industry.

https://www.aviationpros.com/press_release/12438406/rolls-royce-selects-uptakes-industrial-ai-software-to-maximize-availability-of-its-trent-engine-fleet


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New passenger scanner uses space technology to speed up airport security

A super-sensitive passenger scanner that reveals hidden security threats is being trialled at Cardiff Airport in the UK. 

The walk-through scanner, which uses space technology to image human body heat, is the result of a collaboration between Sequestim Ltd. and Cardiff University scientists.

Computer learning allows the scanner to distinguish between threats and non-threats but without the need for passengers to keep still or remove outer clothing.

Globally, around 12 million passengers travel by plane every day on 120,000 flights.

The technology has the potential to cut queues at airport terminals as it screens people on the move. It will also impact on the effectiveness of security and help keep passengers safe.

"Passenger numbers are expected to double in 20 years, putting airport security facilities under immense pressure," said Ken Wood, Sales and Marketing Director of Sequestim Ltd, a joint venture between Cardiff University and QMC Instruments Ltd.

"Our scanner combines a number of world-leading technologies developed by our team here in the UK. It uses the human body as a source of "light", in contrast with existing scanners which process reflected and scattered millimetre-waves while the passenger is required to strike a pose."  
 
 
Airport Scanner


"Our system only needs a few seconds to do its work. Passengers walking normally through security would no longer need to take off coats and jackets, or remove personal items such as phones."
The trial takes place privately, by invitation only, from 4 to 7 December 2018 and will not affect passenger journeys.

The project is one of eight to receive some of the £1.8m funding made available by the UK Government earlier this year through a Defence and Security Accelerator themed competition. Part of the five year Future Aviation Security Solutions (FASS) programme, the multimillion-pound initiative seeks innovative ideas such as this new passenger scanner to help strengthen aviation security.

Originally built to study the furthest reaches of the universe, the technology used is so sensitive it could see a 100W light bulb at a distance of 500,000 miles (twice the distance to the Moon.)

The scanner quickly "learns" the difference between items that can and cannot be taken onto an aircraft, reducing the risk of false alarms which inconvenience passengers and slow down screening.
"The detector technology was originally developed to study the most distant astronomical phenomena. For example, we study how stars are born from gigantic clouds of gas and dust," explained Mr Wood.

"It detects millimetre-waves, which are just like visible light but at a wavelength more than one thousand times longer. The ability of the scanner to reveal hidden objects has also attracted interest from Border Force, responsible for the UK's frontline border control operations at air, sea and rail ports.

The airport trial aims to prove that passive terahertz imaging is robust, versatile, fast and convenient.

UK Aviation Minister Liz Sugg said: "We have a proud history of innovation here in the UK and passenger safety across all modes of transport remains an important priority for the government. The Future Aviation Security Solutions programme demonstrates our support for pioneering projects that can help to reduce security threats in airports. I am pleased to see that the funding awarded to Sequestim has helped the team take space technology and trial it as part of a new passenger screening system at Cardiff Airport."

Cardiff Airport was bought by Welsh Government for £52m in 2013. Nearly 1.5m passengers passed through the airport in 2017. The trial of the passenger scanner in December represents a first for Wales, and a local collaboration with enormous impact potential.

First Minister of Wales, Carwyn Jones, said: "Welsh Government and Cardiff Airport are delighted to be hosting the proof-of-concept trial of Sequestim's innovative technology. This cutting-edge security camera not only promises a huge improvement in our experience of air travel, but also brings with it the prospect of job creation as Sequestim aims to manufacture future scanners here in Wales."

The purpose of the trial is for key members of industry, the Centre for the Protection of National Infrastructure, the Civil Aviation Authority and other government bodies including BorderForce to see the technology in action.
 
https://phys.org/news/2018-12-passenger-scanner-space-technology-airport.html


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More than an auto-pilot, AI charts its course in aviation
 
Ask anyone what they think of when the words "artificial intelligence" and aviation are combined, and it's likely the first things they'll mention are drones. But autonomous aircraft are only a fraction of the impact that advances in machine learning and other artificial intelligence (AI) technologies will have in aviation-the technologies' reach could encompass nearly every aspect of the industry. Aircraft manufacturers and airlines are investing significant resources in AI technologies in applications that span from the flightdeck to the customer's experience.

Automated systems have been part of commercial aviation for years. Thanks to the adoption of "fly-by-wire" controls and automated flight systems, machine learning and AI technology are moving into a crew-member role in the cockpit. Rather than simply reducing the workload on pilots, these systems are on the verge of becoming what amounts to another co-pilot. For example, systems originally developed for unmanned aerial vehicle (UAV) safety-such as Automatic Dependent Surveillance Broadcast (ADS-B) for traffic situational awareness-have migrated into manned aircraft cockpits. And emerging systems like the Maneuvering Characteristics Augmentation System (MCAS) are being developed to increase safety when there's a need to compensate for aircraft handling characteristics. They use sensor data to adjust the control surfaces of an aircraft automatically, based on flight conditions.

But machine-learning systems are only as good as the data they get. There is inherent risk in handing off more of what humans do in a high-risk environment to ML or AI that few people understand. While the final investigation of the recent crash of Lion Air 610 is still underway, the details revealed so far are a strong warning of the risks of handing off too much control to autonomous systems. While catastrophic aviation accidents seldom happen as a result of a single mistake (and this was no exception), the MCAS sensors failed, maintenance failed to fully correct the issue, and the pilots had not been fully trained and informed on the function and use of the MCAS.

The lesson, reinforced at a tragic cost of 189 lives, is that the aviation industry will have to fold data quality and the care and feeding of ML and AI systems into the safety culture that commercial aviation is already renowned for. As machine learning and AI transform the role of pilots, those technologies need to be as thoroughly tested as their human counterparts and deemed at least as competent.

Beyond the auto-pilot 
Major aircraft manufacturers such as Airbus are already phasing in AI. According to Airbus Vice President for AI Adam Bonnifield, the company has been working on these technologies for a long time. "Airbus is not that unfamiliar with these technologies because of our background in aviation and building systems that essentially solve some problems in autonomy," he told Ars.

There's plenty of data to tap regarding machine learning aboard the modern airliner: the A350 XWB, Airbus' twin-engine wide-body aircraft introduced in 2015, has some 50,000 sensors and collects 2.5 terabytes of data daily. And AI can make use of that data in a number of ways. Airbus is working on projects that reduce the cognitive load (and the resulting cognitive fatigue) on pilots, as well as the number of pilots required to be at the controls. This means the crew can spend more time handling the overall strategy and mission of a flight and less time dealing with all the small sub-problems of piloting an aircraft.

Bonnifield explained that, while many people view autonomy in aircraft as "a binary"-either an airplane is autonomous or it isn't-he feels differently. "It's more of a spectrum," he said, "where we take some of the small problems of flying a plane and try to use AI to solve them."

One example of this is an option available on Airbus aircraft called runway overrun protection. ROPS is software that calculates aircraft approach speed and weight, and it compares the resulting physics model with the published runway length and current local weather on approach. If it detects an unsafe situation, it broadcasts the message "Runway too short!" ROPS also calculates optimal approach glide-slopes, or trajectories, for a landing approach, and it helps with taxiing, takeoff, and other aspects of flight.

Another area of AI focus at Airbus is building autonomous vehicles and air taxis designed to transport people inside urban areas. And AI could potentially be used in a passenger plane when the pilots are rendered unconscious from a fall in cabin pressure. It can add up factors and make better decisions faster under high-pressure situations than humans given the right data, creating a potential increase in safety.

Simplifying communications 
Air Traffic Control (ATC) communications is a critical aspect of all flights. In the European airspace, much conversation happens in heavily accented English, making it difficult for pilots and controllers to understand each other. Pilots need to listen for their tail/flight number to be called for clearances, directional instructions, and traffic alerts, often under challenging instrument meteorological conditions (IMC) when they can't see out of the cockpit. Airbus directed AI at this problem as part of a public contest in the company's AI Gym-a program in which Airbus seeks outside partners to assist in developing breakthrough AI systems.

Cleaning up air traffic conversations is difficult for machine-learning algorithms to parse, because ATC audio is noisy, and the conversation is rapid-fire and full of what Airbus described as "domain-specific vocabulary." The goal of AI Gym was to provide full transcription of ATC audio, as well as extract aircraft call signs from audio for conversation tracking and alerting.

"We opened it up to a broad community of different businesses, consulting firms, startups, and research groups to collaborate with us," said Bonnifield. The competition closed in October 2018, and Airbus has already begun work to convert the results into a product.

The AI Gym program has allowed Airbus to attack a number of other potential uses for AI by leveraging outside expertise. "We have these interesting problems and use cases that are largely unexplored and unsolved," Bonnifield said. "Partly because of the fact that the space is so new, we're living at this very immature inflection point of the technology where there's a lot of experimentation happening and even some terrific open source technology."

Through the program, Airbus is working with "all the usual suspects," Bonnifield said; the projects are all performed under non-disclosure agreements. The anonymity of the NDA can be a good thing, he suggested, because not every effort is successful-and failures aren't advertised. While "the usual suspects" in machine learning might often be expected to be the companies to come up with the highest-performing solution, Bonnifield said he discovered that most of the time the best solutions come from tiny startups.

Often, research teams with only a few people are able to produce the best solution. Bonnifield said he believed this is probably unique to the AI space. Airbus' big challenge is how to bring these small teams at the tip of the innovation spear along and give them an easy way to collaborate. That has required Airbus to change the way it works with outsiders. "Some of the startups have never done an RFP [Request for Proposals response] before," Bonnifield explained.

Getting to business 
When it comes to flight-safety issues, airlines rely heavily on their equipment manufacturers (such as Airbus and Boeing). But airlines aren't just counting on AI to assist on the flight deck. Machine learning and AI are being called upon in the back office to help airlines in their battle to streamline ground operations and to create the best customer experience by making travel as painless and seamless as possible.

United Airlines Vice President of Digital Products and Analytics Praveen Sharma said that United is investing in all available new technology to use machine learning with the backend data it gathers from customers, maintenance logs, employee duty logs, and in-flight progressive data to improve all aspects of its business.

In September, United and Palantir Technologies announced a long-term relationship to deploy Palantir Foundry to accelerate enterprise-wide data initiatives across a range of critical business units as the airline's central platform. According to Sharma, "One challenge... we are trying to solve is how to bring this vast amount of data from various parts of the company on different platforms onto a single platform... [that] we can leverage for our machine learning and AI model." The two companies have been working on a wide range of projects for the past year to do this.

Palantir partnered with Airbus to create Skywise, an aviation data-analytics platform that Airbus provides to smaller airlines as a subscription service that would include tools to help reduce unplanned maintenance on aircraft. GE has also tried to turn aircraft sensor data into a machine-learning-based service to drive predictive maintenance of the company's jet engines.

United and its regional carrier, United Express, operate about 4,600 flights a day to 357 airports across five continents. Last year, the companies operated more than 1.6 million flights carrying more than 148 million customers. When unforeseen maintenance issues do occur or other operational issues get in the way, United is using machine learning to help swap out aircraft. This isn't as simple as one might expect; the system must take into account all of the variables required for assigning a crew (such as rest time and appropriate crew aircraft certifications), aircraft fuel and operations limitations, and aircraft seating capacity. "These are complicated decisions that often must be calculated and decided in a 25-minute timeframe based on the limited amount of data available at that time," Sharma explained.

Beyond maintenance 
But United's use of machine learning and AI goes far beyond managing maintenance and aircraft schedules. It also taps into customer data. Using the data gleaned from each passenger interaction, United is applying AI and machine learning to streamline its customers' experience based on their data-and tuning offers to match their profiles.

United's machine-learning algorithms take 150 different customer and flight data points and, in real time, decide which particular product to put in front of a customer at the purchase or check-in point. The engine takes into account things like passengers' previous purchases, preferences, destinations, and activities. Customers' interactions move through United's real-time decision engine, up and running since 2014, which gives them various product options to improve their travel experience. Options include flight choice, seat upgrades, mileage purchase, or the ability to jump to the front of the line with Priority Access.

To drive what gets offered up to each customer, Sharma said that United uses a prediction model based on a Bayesian inference model. "It decides not just what offer to give," Sharma explained, "but what image to put in front of the customer and what tagline to use."

Sharma said that the application of machine learning is paying off. Based on measurements collected by United, customers aren't having to hunt for things they want to purchase or for desired experiences.

Other airlines are embracing AI in other forms to take the pain out of travel (and to reduce the workload on airline employees). Facial-recognition technology is now showing up on terminal kiosks to help speed check-in at the airport.

Most facial-recognition algorithms are based on deep learning, which is part of machine learning. Delta Airlines is the first to deploy this process, speeding up passengers' time to gate by almost 10 minutes, according to the airline's estimates. The system, used currently for check-in and baggage check on international flights, leverages passengers' passport photos. Delta expects to expand operations to domestic flights next year.

Preventing future disasters 
Perhaps one of the most important uses of AI-based analytics, however, may be in identifying risks to the safety of aircraft before a disaster-such as the crash of Lion Air Flight 610, when a failure of the automated control system on a prior flight may have signaled a major safety issue. NASA Ames Research Center in Silicon Valley is heavily involved in aviation-related AI, and one of NASA's projects there is focused on identifying "anomalous operations" within data from commercial aviation-events that could be precursors to potentially bigger problems.

This is a primary area of research for Nikunj Oza, a computer scientist and leader of the data sciences group within NASA Ames' intelligent systems division known as Code TI. Because commercial aviation's safety record is so good-much better than driving, for example-it's much more difficult to identify those few cases where there's an anomaly that might represent a safety issue.

NASA has done some initial development of algorithms related to anomaly detection and incident precursor identification, and it has started the process for gathering feedback from experts in the field. The agency is currently developing a system for use in safety analysis of aircraft data-in particular, for FAA's analytics partner Mitre, the federally funded research and development center. Mitre runs a program called Aviation Safety Information Analysis and Sharing (ASIAS), a data consortium that shares safety data among NASA, the Federal Aviation Administration, the National Transportation Safety Board, aircraft manufacturers, and more than 50 airlines. The airlines upload some subsets of their flight-recorded data to Mitre, which performs analysis and provides feedback on potential problems. (The data is shared confidentially by the airlines.)

The hope for the analytics being developed at Ames is that the AI can discover patterns of anomalies in flight data that could be indicative of a systematic problem with aircraft. "You'd like to find that as soon as possible and come up with some kind of a mitigation to prevent it happening again," Oza explained. He said that, so far, rather than AI replacing humans outright in aviation, AI and human experts have proven to be complementary-a partnership that can save human lives.

https://arstechnica.com/information-technology/2018/12/unite-day1-1/

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NATS and McLaren Deloitte to partner on aviation technology
 
UK air traffic service NATS and McLaren Deloitte have announced a collaboration agreement aimed at transforming how operational decisions are made in the aviation industry.

The partners will work together on products that combine the relative expertise of leading organizations, bringing together state-of-the-art analytics and data science with the real-world experience of network and airport capacity management.

During every Formula 1 race, McLaren takes into account millions of possible scenarios to then model the outcome of a range of tactical decisions. Meanwhile, Deloitte is renowned for its experience in using data analytics to deliver large consulting projects globally. These capabilities, combined with NATS' expertise in managing congested and complex airspace and airports, are now being deployed to help the aviation industry understand and accurately predict the impact of decisions before they are made.

Performance Optimiser is the first product to emerge from the collaboration. Developed by NATS air traffic and airspace capacity management experts with McLaren Deloitte data scientists, Performance Optimiser enables air navigation service providers (ANSPs) to review and model the effect of a huge range of tactical decisions in en route and terminal airspace - such as the use of flow regulations - to maximize available airspace capacity and minimize delays.

The cloud-based system offers instant access to operational data, allowing the user to view a range of factors that may influence air traffic - from the level of flow regulations and weather conditions, through to the occurrence of sporting events - in order to make an informed decision that helps best manage the airspace.

Performance Optimiser can then simulate how different decisions would have changed the outcome for any given day, enabling operational supervisors to not just review performance, but inform future decisions and quickly apply their learning to drive improvement.

Martin Rolfe, CEO at NATS, said: "On the surface, aviation and Formula 1 might seem like an unlikely collaboration, but we are increasingly looking at opportunities to work with people outside of the traditional aviation industry to find new ways to help our customers.

"NATS has a world-class capability in managing busy and complex traffic flows, and we're already seeing the benefits of combining that expertise with what McLaren Deloitte do so well. I'm excited to see where this will go next."

Mike Phillips, director, aviation, at McLaren Applied Technologies, commented, "Together McLaren and Deloitte are focusing on the growing needs of airport operations and are investing in a suite of solutions. This new collaboration with NATS enables us to deliver F1 derived simulation and analytics to air traffic management, enabling operational supervisors to make decisions based on data driven insights.

"The potential offered by sensors, simulation and data analytics to the airspace navigation sector is significant, but until now it has been difficult for the industry to bridge the gap between the physical and digital world. This relationship will provide NATS and its customers with data that allows them to improve operational efficiency and unlock the benefits that come with it."

Other products already in advanced development include additional airline and airport optimization products.

https://www.passengerterminaltoday.com/news/technology/nats-and-mclaren-deloitte-to-partner-on-aviation-technology.html

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Aeronautical university to help plan Atlantic County aviation academy

Atlantic County officials announced Tuesday that a leading aeronautical university has agreed to partner with them to help plan a county aviation maintenance and technical academy.

Embry-Riddle Aeronautical University will develop an operational plan that will include recommendations for the location of the academy, design concepts, an educational curriculum and a strategy for operations and sustainability, according to a press release.

The county was awarded a $120,000 Innovation Challenge grant from the New Jersey Economic Development Authority to develop the plan, according to the release.

"Embry-Riddle is considered to be the finest aeronautical university in the world," county Executive Dennis Levinson said in the press release. "We are pleased that they recognize the opportunities our area offers in aviation, and we hope this project leads to additional areas of collaboration at the National Aviation Research and Technology Park such as Smart Airport initiatives and STEM education."

Embry-Riddle will also work closely with Atlantic Cape Community College, which operates an aviation program and is a partner in the grant, officials said.

"A key goal of the proposed Atlantic County academy is to help broaden and diversify the regional economy to facilitate development of an aviation economic hub centered around the FAA Tech Center, the Atlantic City Airport and the National Aviation Research and Technology Park," Lauren Moore, executive director of the Atlantic County Economic Alliance, said in the release.
 
According to Levinson, an Aviation Maintenance and Technical Academy would also offer workforce development opportunities.

"The skill sets that are learned at the academy would be transferable to the repair and maintenance of wind energy turbines. This would be critical to meeting the state's plans to develop offshore wind energy, which will also need skilled workers."

According to the release, the Economic Alliance is working closely with the South Jersey Transportation Authority to assist with its efforts to develop air cargo and aircraft maintenance and repair operations at the airport.

Officials said the success of these operations will depend on the availability of a skilled workforce and that the academy is intended to help meet that need.

The development of air cargo and maintenance and repair operations in Atlantic County was a recommendation in the Atlantic County Economic Development Strategy prepared by AngelouEconomics in 2015.

The Economic Alliance was vested with the responsibility of implementing the strategy, officials said.

https://www.pressofatlanticcity.com/news/press/atlantic/aeronautical-university-to-help-plan-atlantic-county-aviation-academy/article_39ed1206-0c14-55f8-be87-f39db8ad0fe1.html


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Exclusive with IATA: adapting VR and AR technology in training
 
New technology encourages to rethink training processes and learning experience, especially when it comes to adaptation of VR and AR in training. At Air Convention 2018, Kim Kian Wee, Assistant Director of Training and Innovation at IATA, talked to Ruta Burbaite from AeroTime about the introduction of new innovative solutions in training and how it can be enhanced with the use of VR and AR.

Introduction of new technology provides an opportunity to rethink how training is conducted and how the learning experience can be optimized. One of those transformative innovations is the adaptation of VR and AR in training.

Limitations of theoretical operational training are well-known. The value of VR, on the other hand, is that it offers live, practical experience while also addressing the limitations of practical training: it is accessible anytime, easy to set-up and use, and has full compliance with industry standards.

IATA believes that VR training enhances knowledge retention, improves effectiveness through full immersion, offering faster familiarization to real environment, accommodating better understanding of learning abilities, and simply bringing out greater excitement in the learning process.

Although there is always trepidation surrounding the adaptation of new technologies, IATA Training assures it provides a low-risk approach to its members by experimenting with proof of concepts and pilots.

 
Interview with Kim Kian Wee, IATA - Air Convention, 27.09.2018

 
https://www.aerotime.aero/ruta.burbaite/22150-exclusive-with-iata-adapting-vr-and-ar-technology-in-training


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Enter Air Entrusts Magnetic MRO with Nineteen Boeing 737NG PBH Support
 
Magnetic MRO, a provider of Total Technical Care, and Enter Air, Poland's largest and Eastern Europe's second largest charter carrier, have signed a three-year contract for PBH support for the airline's 19 Boeing 737-800s.

The recently signed agreement includes scheduled and 24/7 ad-hoc supply of components, component repair management, loan, exchange and warranty support services for the carrier's Boeing 737 NG fleet at Warsaw Chopin, Katowice-Pyrzowice and at its other main airports.

"As a charter airline, Enter Air is nothing but a demanding customer to any PBH provider. What has brought Magnetic MRO into the arena is the fusion of our growing asset management expertise combined with extensive component maintenance capabilities by our new shareholder Guangzhou Hangxin Aviation Technology (Hangxin)," shares Inga Duglas, Commercial Director at Magnetic MRO.

"Being one of the largest charter airlines in the region, we need efficient component supply in order to ensure the fleet's smooth performance. However, launching and maintaining an extended stock of non-critical components requires substantial investments and an additional team to run it.
 Luckily, together with Magnetic MRO and their PBH program, we will be able to keep our component supply, repair and overhaul costs optimized while maintaining high fleet performance and timely AOG support," says Mariusz Olechno, Chief Technical Officer at Enter Air. 

https://www.aviationpros.com/press_release/12438388/enter-air-entrusts-magnetic-mro-with-nineteen-boeing-737ng-pbh-support


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Entering the Cloud-Based Era of Aviation Maintenance
 
COLD SPRING, N.Y., Dec. 4, 2018 /PRNewswire/ -- CloudVisit Aviation has released empowering new software that will usher remote aviation maintenance, repairs, and inspections into the era of cloud technology. CloudVisit Aviation Maintenance Software software as a service (SaaS), is a paperless filing system and combines project management with video conferencing. It features checklist integration, annotated screen capture, and session recordings with remote connectivity benefits to produce paperless, cloud-based records of aviation maintenance and repair.

CloudVisit Aviation Maintenance Software is available in anticipation of the Federal Aviation Administration's (FAA's) remote connectivity guidelines, which will be released in October 2019. "The FAA's decision is monumental for the aviation industry" affirmed CEO and Founder of CloudVisit Aviation, Daniel Gilbert. CloudVisit Aviation Maintenance Software can be implemented immediately, before October 2019.

Inefficiency In Current On Site Aircraft Quality Controls, Inspections and Repairs
The current aircraft inspection process is not time efficient as it relies upon an already scarce number of industry experts to be physically present at each inspection site. Often, on-site technicians are kept waiting for experts to arrive, meaning an unnecessary increase in labor expenses, along with potential  passenger delays. Additionally, the costs to bring industry experts to each field site quickly accumulates in gas, meals, transportation, and hotel stays. The shortage of experts creates large backlogs of uncompleted work and decreases the number of aircrafts that could be flying but are not since inspections have not been completed. According to a 2017 study, Aircraft on Ground (AOG) situations can cost up to $150,000 per hour for large airlines, meaning that remote inspection software can save airlines companies millions.

Remote Aviation Maintenance and Inspection Solutions

CloudVisit's aviation software maximizes the availability of experts, whose work location is virtual and not physical. No one is kept waiting, and inspections are completed instantly. Meetings between experts and on-site technicians can be both scheduled and impromptu, and each session can be recorded and referred back to at any time. CloudVisit's software documents each step of aircraft maintenance and repair in real time and saves to the cloud for easy reference, so that data is never lost and is easily recovered.

When aircraft repairs take place a checklist is developed so that all steps of maintenance and repair are completed. Checklists are customizable according to each projects' needs, and all documentation, including captured images, audio, and video, are uploaded and linked into the checklist. This process ensures that all data is organized, and the supplemental documentation provides verifiable evidence of quality assurance.

About CloudVisit

CloudVisit Aviation provides leading-edge aircraft maintenance software, which integrates remote project management with quality control. Our software maximizes efficiency while reducing cost and time. CloudVisit is backed by 15 years of success in software programming, video conferencing and telecommunications with a proven record of excellence, efficiency and security. For questions about our leading aviation quality control and inspection software, or to request a no-obligation demo, call 845-809-5770.

https://www.aviationpros.com/news/12438418/entering-the-cloud-based-era-of-aviation-maintenance


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CISF to deploy robotic canines at Indian airports

The Indian Central Industrial Security Force (CISF) is reportedly planning to deploy robotic canines at airports across the country in an effort to boost security.

These robotic canines will replace airport security dogs such as the German shepherds, Labradors or Belgian Malinois, which are used by the CISF in airport security, reported the Times of India.
Robotic canines are capable of detecting explosives and can scan the luggage of passengers using an X-Ray system fitted in their eyes.

With deployment of robotic canines, CISF aims to use the latest technologies to deal with increasing global threats to aviation, greater volumes of air travellers and new tactics used to smuggle illegal items through airports.

The idea of deploying robotic canines was discussed when CISF director general (DG) Rajesh Ranjan and additional DG Ganapathy attended the Global Aviation Security Symposium in Canada.
An officer told the publication: "We already have a tie-up with Transport Security Administration (TSA) of the United States but now we have a capacity building pact with the EU as well, which will help us explore a lot about new technologies and methods of securing our airports."

In addition, the officials discussed the use of CT scan-based screening of hand-luggage, cabin baggage, artificial intelligence, latest explosive detectors and biometric control access at the airports.

At present, several airports in the UK, US, Canada, Japan, and Korea are using robotic dogs for various purposes, including passenger information and security checks.

CISF is responsible for providing security services at 61 airports across the country. It has already started biometrics system at some airports and is trialling full-body scanners.

https://www.airport-technology.com/news/cisf-robotic-canines-indian-airports/


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SpaceX Launches Its 20th Rocket Of The Year, But Doesn't Quite Make The Landing
 
 


SpaceX has successfully launched its 20th rocket of the year, a mission taking supplies to the International Space Station (ISS), but the landing wasn't quite as successful.

Their Falcon 9 rocket lifted off from Cape Canaveral's Space Launch Complex 40 in Florida at 1.16pm Eastern time (6.16pm UTC) today, carrying the CRS-16 Dragon spacecraft into orbit. This is a mission under contract with NASA, as part of their Commercial Resupply Services (CRS) program.
SpaceX also attempted to land the first stage booster of the rocket - the first in a new Block 5 class - back on Earth about eight minutes after launching at Landing Zone 1 in Cape Canaveral. However, the landing appears to have experienced some problems, with the rocket instead hitting the ocean rather than landing on the ground.

Video footage from just before the landing attempt showed the first stage spinning out of control, with one of its grid fins that it uses to steer itself seemingly out of position. SpaceX later confirmed the booster had performed a "water landing", rather than making it to the landing pad.

"Grid fin hydraulic pump stalled, so Falcon landed just out to sea," CEO Elon Musk wrote on Twitter. "Appears to be undamaged & is transmitting data. Recovery ship dispatched."

The Falcon 9 rocket used on this mission had not been used before, but the Dragon spacecraft had. It had previously flown on the CRS-10 mission in February 2017. It will take the spacecraft several days to reach the ISS, due to arrive on Saturday December 8.
 
On board are 2,540 kilograms (5,600 pounds) of supplies, which includes 250 experiments. Among these are 40 mice as part of the Rodent Research-8 (RR-8) mission, along with food bars for the mice. This had caused the flight to be delayed from its initial planned launch yesterday, December 4, when their food became mouldy and NASA had to fly some replacements in.

These mice will live on the station for between 30 and 60 days. Sadly after that they'll be euthanized, so that their tissue samples can be studied to see how their muscles have coped with living in the microgravity environment of the ISS.

As mentioned this was SpaceX's 20th launch of the year, and the 19th launch of a Falcon 9 rocket in 2018 - the other was the Falcon Heavy launch on February 6. This is the most launches SpaceX has ever completed in a single year, with their previous record of 18 coming in 2017.

This week also marked the eighth anniversary of SpaceX's first Dragon flight for NASA, which launched on December 8, 2010, with this being the 16th. SpaceX is contracted in total for 26 missions to the ISS, and next year they are set to begin not just cargo flights, but human flights too.

The number of paylaods on board Dragon is the largest number of payloads ever taken to the ISS in a single launch. And it's been a good week for multiple-payload fans, because just two days ago on December 3, SpaceX launched the SSO-A mission with a whopping 64 different satellites on board.

Dragon will remain on the ISS after about five weeks, when it will depart the station, re-enter our atmosphere, and splash down in the Pacific Ocean. At the moment, this is the only cargo spacecraft that can return experiments and research from the ISS.
 
https://www.forbes.com/sites/jonathanocallaghan/2018/12/05/spacex-launches-its-20th-rocket-of-the-year-but-doesnt-quite-make-the-landing/#78bb7c277990

Curt Lewis