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JAM: vehicle predictive maintenance through Artificial Intelligence

Periodic Reporting for period 2 - JAM (JAM: vehicle predictive maintenance through Artificial Intelligence)

Reporting period: 2017-07-01 to 2018-03-31

Today fleet managers lack information regarding their vehicles true reliability and condition (health status). Each vehicle represents 3-5k€ p/year in maintenance. Vehicle malfunctions and their unpredictability lead to higher operational costs and less reliability over the performance and operation of fleets.
In fact, inadequate maintenance has a measurable direct impact on operational costs related to shorter fleet lifetime, more frequent and expensive replacement of vehicle parts, unpredictable and recurrent off-road (VOR) time and even unoptimized fuel consumption.
VOR time has a strong impact on the productivity and efficiency of fleets, and fuel and maintenance costs alone represent 47% of the total costs of trucking. In 2012 fleets of the EU-28 burnt 123 billion litres of fuel, representing around €200 billion in costs. In Europe alone, buses and trucks represent only 5% of the vehicles in circulation, but their CO2 emissions make up one third of total road transport emissions.

Stratio is an IoT product that turns vehicle maintenance into an exact science. Stratio’s device - Stratio Plug - is connected to the vehicle on-board diagnostic (OBD) interface, and collects data in real-time from all vehicle sensors. Artificial Intelligence (AI) is then used to identify failures before they happen.
Stratio explores an existing gap by focusing its approach on predictive maintenance, identifying potential problems and providing solutions through the Stratio Play platform, including expected repair time, potential costs and step-by-step guides on how to perform repair.

Main competitive advantages:
• Predictive maintenance, detecting the onset of systems degradation, reporting anomalies before failures occur
• Capable of extracting more data than competitors (standardized and non-standardized sensor data)
• Agnostic device, capable of retrofitting older vehicles, as it works in all vehicles despite age, brand or model
• Specifically designed for medium/heavy-duty fleets
Main developments so far:
• Product development and production: mass production has been validated and we have agreements in place for the assembly and production of different batch sizes, ensuring growing margins and profitability.
• Certification & other regulatory issues: we are focused in ensuring compliance of the system with current regulations. We are currently CE mark certified, and aiming to be certified as an automotive-grade product (E-mark) and FCC.
• Distribution: A partners’ program was created with different partner levels with agents and re-sellers engaged in various regions to support our commercialization and distribution strategy.
• Business development: proof of concept agreements and full contracts are signed with the two main segments and important partnerships were established.
• Product promotion: Stratio is attending the most important trade fairs and conferences such as: FIAA, European Bus Forum, BusCon, BusWorld Europe, Coach&Bus and APTA.
• Funding: Stratio was awarded by European Space Agency Business Incubation Centre, we are part of Microsoft sponsorship program which provids 120k€ of free Azure credits and we were selected for Impact Growth program.
Stratio target customers are fleets and manufacturers of heavy-duty vehicles. In Europe alone there are an estimated 13 million heavy-duty vehicles in commercial fleets. Operational chaos caused by malfunctions on the road, maintenance and fuel costs, and loss of profitability and opportunity due to downtime in repair workshops are major concerns and constraints for these companies.
Stratio aims to mitigate these problems, introducing the concept of predictive maintenance applied to heavy-duty vehicles, allowing an increase in operational efficiency, and the reduction of consumption and CO2 emissions, by optimizing the functioning of vehicle systems.
Through the mathematical modelling of the vehicle's different components and systems, it will become possible to optimize the data collection from vehicle sensors obtained through Stratio’s Plug equipment (hardware). The correlation between these data sets, the automatic construction and the enrichment of models based on artificial intelligence will produce a product with an advanced capacity for prediction of anomalies and damages in vehicles, even before they become expensive repairs.
The Stratio Plug & Play product had the following main goals:
• Prediction of malfunctions in mechanical components, thus prolonging the useful life of vehicles and reducing maintenance costs.
• Reduction of vehicle downtime in repair shops.
• Reduction of fuel consumption and thereby reduction of polluting emissions generated by the same vehicles, through the monitoring of the configurations/parameterization of the vehicles' different systems.
Stratio Plug & Play will allow the approximation of maintenance in the road transport industry to the maintenance carried out by the aviation and space industry, where it is possible to identify errors even before they have an impact on the equipment or operations.
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