Operations
Case Studies
A UK registered charity predicts visitor flow to its building with Markov chain algorithms
A UK registered charity leveraged technology from ASI to predict visitor flow. The provider used wifi usage data to track crowd movement within the building and gather information on the amount of time people spent in each location. ASI created a model indicating the most likely routes people would take through the attraction, congestion points and locations prone to overcrowding using Markov chain algorithms. The algorithm simulated the movement of 500 different hypothetical visitors over a fifteen minute period to come up with the results.
Linked use case: Optimise product layout in stores
A large european bank identifies issues in post-trade operations by analysing mailboxes with the use of machine learning
A large european bank is leveraging re:infer''s technology to identify inefficiencies from communication data. By using supervised and unsupervised learning the system analysed 300 of the bank''s shared mailboxes to identify issues in operations. The system then conducted a more targeted analysis of the fixed income mailboxes to identify and quantify specific issues that needed attention. The bank identified several areas for improvement and implemented the necessary targeted solutions to improve efficiency.
A large european integrated electric power company is predicting, diagnosing and reducing equipment failures in conventional power plants with machine learning
A large european integrated electric power company implemented C3 IoT''s C3 Predictive Maintenance solution to achieve more accurate predictions of equipment failure and maintenance needs. The technology uses advanced machine learning-based algorithms to monitor instrument signals, track failure modes and detect anomalies in equipment components. The company''s 2,640 megawatt conventional coal-fired power plant benefited from the implementation at it improved prognostic lead time and flexibility in scheduling of maintenance tasks and reduced ununplanned, emergency maintenance tasks.
Linked use case: Predict problems and recommend proactive maintenance for power generation and supporting equipment
ARUP saves 790 engineering hours using machine learning to detect utility clash points planning a light rail system for Auckland
Arup, in a joint venture with Jacobs, was selected to plan a new light rail system for the city of Auckland. The assessment of utility systems clashing at different locations along the proposed rail line was automated using supervised learning algorithms, reducing the amount of engineering time which would have been required for manual checks by 790 hours.
Linked use case: Collate and evaluate site data for architectural planning
AXA UK saves 18,000 people hours in six months by deploying bots to handle repetitive tasks
AXA UK has successfully deployed bots to handle repetitive tasks. Over the last six months the insurance company has leveraged 13 software bots that assist its employees in three departments, the customer property claims, the commercial property and the liability department. The three bots that were named by employees, Harry, Bert and Lenny, helped the staff in tasks like matching customer correspondence with the relevant claims record. The specific task required the bot 42 seconds, while a human needs about four minutes, thus saving the company 18,000 people hours, which translates to about £140,000 in efficiency and productivity gains.
Linked use case: Digitise and automate processes using Robotic Process Automation (RPA)
Abellio London claims it reduced bus collisions and injuries by 29% and 60% respectively with collision avoidance technology
London’s leading bus operators, Abellio London, have collaborated with Intel''s Mobileye to launch a trial of safety technology. The aim of the project is to reduce bus collisions with cyclists, motorcycles, pedestrians and other road users and hence injuries. 66 buses were included in the trial, on three of the company’s London routes, and were equipped with a camera unit installed on the inside of the windshield and a display placed in the driver’s cab both providing audio and visual warnings. Findings to date who that Mobileye collision avoidance technology has managed to reduce collisions by 29% and reduced injuries from such collisions by 60%.
Linked use case: Automate driving with self-driving vehicles
Abundant Robotics device autonomously harvests apples using machine vision to identify appropriate fruit
Abundant Robotics, a vendor, offers technology which is able to autonomously harvest firm fruits using machine vision. Their product detects the location of apples on branches and according to their color, which signifies if they are ready for harvest, uses a vacuum style system to pull them and collect them.
Linked use case: Deploy robots to do physical tasks in the agricultural process
Accenture redeploys after automating tasks with RPA system
Accenture has developed a system, SynOps, for analysing its various data input sources and automating things like contract review. While it has been using this system internally to automate processes in finance, marketing, accounting, and procurement, purportedly resulting in the redeployment of 40,000 staff, it is now selling it tp clients.
Linked use case: Digitise and automate processes using Robotic Process Automation (RPA)
Admiral automobile insurance planned to offer discounts to drivers based on data in their Facebook profiles but were prevented by Facebook
Admiral insurance had planned to analyse drivers'' Facebook data to offer discounts to those customers deemed less risky; Facebook intervened and prevented the project from going live as it was a violation of its terms of services.
Linked use case: Enhance motor insurance by predicting driving behaviour through the use of language in Facebook posts
Airbus is investing in developing autonomous passenger aircraft
Airbus has set the goal of developing autonomous planes that operate with just one person pilot. It is working with Chinese tech and AI companies in order to make self-driving technologies found in the automotive industry applicable to airplanes. To accelerate the development of the project, which in the future would cut staffing costs down, the company has committed to setting up an innovation hub in Shenzhen, China.
Linked use case: Automate aircraft piloting
Airbus is offering a virtual assistant for astronauts that gives companionship and expert advice while in space through a neural network based astronaut assistance system
Airbus has designed an AI-based assistant for astronauts, a machine able to support space flight crews by problem solving and ensuring the completion of a routine schedule. Using IBM''s Watson it provides the psychological support of talking to a crew member, which is believed is crucial for the success of long-term missions. The assistant will first be tested by Alexander Gerst on the ISS during the European Space Agency’s Horizons mission in mid-2018.
Linked use case: Deploy robots to replace human staff
Alibaba Group detects pigs'' pregnancy seven times quicker using facial recognition technology
Alibaba Group claims it has developed a system to identify pregnant pigs by observing their behaviour after mating. The task was previously a manual procedure were farmers had to observe each of their cow''s behaviour over a 21 day period. With the algorithm, it is now possible to determine if a pig is pregnant on the third day to increase the number of newborns and maximise production. The company expects that its system will be adopted by some Chinese farms in early 2019.
Linked use case: Tracking, monitoring and analysing livestock behaviour to optimise production
Ant Financial automates vehicle damage assessment to assist automobile insurers using image recognition
Ant Financial introduced an AI image recognition system for insurers which assesses external automobile damage and sets claims amounts based on the assessment. The system uses image data which automates part of the claims assessment process.
Linked use case: Recognise and categorise type of damage to predict insurance claim valuation through accessing photographic data
AstraZeneca plans to crack down on online sale of counterfeit drugs in China using machine learning and natural language processing
AstraZeneca teams up with Tencent and Alibaba to strengthen the fight against counterfeit efforts. Alibaba will put traceability codes on drug packages and through their app patients will receive personalised recommendations and healthcare services. Tencent will work with AstraZeneca to identify online counterfeit drug sale using natural language processing to identify suspect language.
Linked use case: Identify and manage potentially fraudulent activity
Australian Renewable Energy Agency improved accuracy of solar energy predictions by 31% using machine learning methods based on a distributed network
Australian Renewable Energy Agency investigates the ability of machine learning models to predict the output of photovoltaic (solar) energy at different timeframes for a network of sites. Three machine learning methods are investigated along with a baseline. Each performs differently depending on the time interval at which they provide predictions. However, basing predictions on a distributed network versus single site, as used in other methods, resulted in increased accuracy of 9-31% over existing methods.
Linked use case: Automate aircraft piloting
Aviva accelerates from 400 to 10 days post-merger organisational planning and employee data integration with the use of machine learning
Aviva wanted to accelerate the post merger integration with Friend''s Life. They used Concentra''s AI powered OrgVue to help design a new integrated organisation and merge employee data from disparate systems. Time was reduced from a typically 400 days to ten.
Linked use case: Optimise staff and resource planning
BHP saves $5.5M by predicting mining truck maintenance requirements with machine learning
BHP has established a Maintenance Centre of Excellence to analyse data from its machinery in order to predict equipment maintenance needs, improving the maintenance of trucks at several of its sites, saving $5.5 million in costs at one mine alone.
Linked use case: Predict problems and recommend proactive maintenance for mining, drilling and support equipment
BP reduces methane emissions by 74% and increases production volume by 20% by optimising oilfield well valve functions with AI modelling
BP is trialling a modelling system which uses current and historic oilfield data to build a simulation and test the effects opening and closing valves at different production sites on gas emissions, which has resulted in decreased methane coming from the vents by 74%, increased production volume of 20% and overall costs decrease of 22%.
Linked use case: Optimise extraction plans based on data including drilling samples and performance at historic and comparable sites
Baidu does underwriting for consumers with limited credit history using machine learning
Baidu partners Zest Finance to use their machine learning platform to underwrite credit risk for consumers with little credit history. The platform analyses data such as payment and purchase history, customer support data etc. They also analyse variables such as how customers fill out forms, how they navigate websites, whether they are being honest about reporting income etc.
Linked use case: Evaluate customer credit risk using application and other relevant data for faster and more efficient decisions
Baillie Gifford investigates the potential of AI to improve efficiencies through automating fund manager''s tasks
Billie Gifford investment management firms has begun to investigate the potential of AI algorithms to suggest wealth management strategies and provide investment advice.
Linked use case: Forecast asset pricing based on market patterns
Baltimore Gas and Electric generated $2.8 million in economic benefit from identifying fraud and unbilled energy usage with machine learning
Baltimore Gas and Electric Company (BGE) is leveraging machine learning to identify and tackle unbilled energy usage. In doing so, the company has generated $2.8m in economic benefit and is expecting its annual economic benefit to reach $20 million. The company is using C3 IOT''s solutions, such as C3 Revenue Protection™ and C3 AMI Operations™ to improve the operation of its advanced metering infrastructure (AMI) network.
Linked use case: Identify potential fraud from utility consumers
Bank of America enhances its published currency research with machine learning
Bank of America is the first among three biggest U.S. banks to provide machine learning based currency research for the foreign exchange (FX) market. In fear of market turmoil, following political issues in Italy in the beginning of summer 2017, the bank began using machine learning programs to advise clients on what to sell and buy. To predict how the euro-dollar currency pair could possibly perform, BoA trained its system using both supervised and unsupervised learning on data, such as government spending and consumer confidence. Its inference was that in the aftermath of the Italian election the euro would likely weaken.
Linked use case: Compose and conduct market research
Bank of England analyses limit order book data using machine learning
Bank of England ran a Proof of Concept (POC) with BMLL Technologies to explore the capabilities of machine learning in analysing limit order book data from a number of trading exchanges. The Bank evaluated an alpha version of the company''s machine learning API (application programming interface) programmed to recognise patterns in the data. The Bank has noted improvements for the company following their experience of the product and identified that such technology could be beneficial for their operations in the future.
BankMobile approves loans for young banking customers based on non-traditional data measures using Upstart''s machine learning
BankMobile is planning to implement Upstart''s online lending software which assesses loan creditworthiness by using machine learning to model risk based on alternative data. This is is intended to target younger customers who may have no traditional credit history.
Linked use case: Evaluate customer credit risk using application and other relevant data for faster and more efficient decisions
Big River Steel maximises energy consumption at off-peak times to minimise energy costs using an AI powered optimisation model
Big River Steel has implemented Noodle.ai''s enterprise AI solution aiming to optimise operations at the company''s new metal recycling and steel production facility in Arkansas. Using machine learning models, the company is able to reduce energy costs by optimising scheduling and maximising energy consumption at off-peak times.
Linked use case: Optimise energy scheduling and management of power plants based on energy pricing, weather and other real time data