predictive maintenance Archives

SIXT turns to predictive maintenance for its UK fleet

Posted on 18 March, 202529 July, 2025 by Will Priestman

Geotab Inc., a global market leader in connected transportation solutions, today announced a strategic partnership with SIXT van & truck. The landmark collaboration aims to enhance SIXT van & truck’s fleet management capabilities and elevate customer service standards for the company across the UK market.

SIXT van & truck will incorporate Geotab’s advanced telematics solutions into commercial vehicles within its UK-wide fleet. This integration, which will roll-out across the next 12 months, will leverage Geotab’s Original Equipment Manufacturer (OEM) integrated data to facilitate predictive maintenance and efficient Service, Maintenance and Repair (SMR) operations. By utilising Geotab’s highly precise mileage tracking and vehicle data solutions, SIXT van & truck aims to ensure seamless contract compliance with OEMs while improving vehicle efficiency and performance.

The decision to form a long-term partnership follows a successful pilot programme, during which SIXT van & truck successfully recovered two stolen vehicles, further underscoring the value of Geotab’s telematics solutions in boosting fleet security and operational competence.

David Saint, Managing Director SIXT van & truck UK, said: “Partnering with Geotab allows us to harness cutting-edge telematics technology to enhance our fleet operations in the UK. The ability to access accurate, real-time vehicle data enables us to perform predictive maintenance, reduce downtime and offer an improved experience to our customers.”

Rental and leasing organisations have traditionally engaged in bulk purchasing agreements with OEMs, involving complex contracts to sell vehicles back to manufacturers under specific detail-driven conditions, including precise mileage limits and vehicle standards. By integrating Geotab’s technology, SIXT van & truck is set to streamline such opaque processes, providing the company with comprehensive management of vehicle data to uphold contract terms and deliver superior service to customers.

Geotab’s extensive OEM network and robust market coverage empower leasing and rental companies such as SIXT van & truck to integrate diverse fleet data. This advanced and unmatched capability not only supports predictive maintenance but also ensures compliance with contractual obligations, ultimately leading to cost savings and customer satisfaction.

Implementing predictive maintenance allows rental companies to anticipate and address vehicle issues before they escalate, thereby minimising unexpected breakdowns and reducing operational costs. By having the capability to analyse real-time data thanks to Geotab’s innovations, SIXT van & truck can schedule maintenance during optimal periods, ensuring maximum vehicle availability. This proactive approach not only extends the lifespan of fleet vehicles but also helps contribute to cost savings by preventing major repairs and reducing downtime.

“We are delighted to be working with SIXT van & truck, delivering an innovative telematics solution to their commercial vehicle fleet across the UK,” said Christoph Ludewig, Vice President, EMEA. “Geotab will provide SIXT van & truck UK with actionable insights that improve efficiency and elevate service quality. This collaboration not only reinforces our commitment to supporting partners in achieving operational excellence but also marks a key milestone in our continued growth within the rental and leasing space. As we forge new alliances and strengthen existing relationships, we remain focused on delivering telematics solutions that drive real value.”

Real-world applications of Geotab’s advanced telematics solutions have shown significantly enhanced fleet operations for rental and leasing organisations. By integrating Geotab’s connected vehicle technology, a rental company last year achieved 100% fleet connectivity in the UK and 67% across six core European markets. This comprehensive data integration has led to improved vehicle recovery rates, real-time collision detection and remote monitoring of vehicle metrics such as odometer readings and fuel levels. These breakthrough advancements have also collectively optimised fleet management and elevated customer service standards.

As part of the partnership, SIXT van & truck will explore opportunities to integrate Geotab’s advanced telematics solutions into its rental services, providing end customers with added value.

Read Similar…

Asset Tracing and Transport Flow Optimization with ANT Locator

Strengthening Supply Chains with Data-Driven Solutions

Posted on 20 September, 202429 July, 2025 by Keith McKinley

Supply chains can be strengthened by using data-driven solutions, says Brian Fitzgerald (pictured), Growth Strategist at Augury.

It is no secret that today’s purpose-built AI tools can not only analyse vastly more data than they could a few years ago but synthesise it into more easily accessible forms, from graphic and narrative to speech. In recent years, AI has revolutionised manufacturing by enhancing predictive maintenance, improving quality control, and optimising supply chains. Additionally, AI facilitates data-driven decision-making, optimises energy consumption for sustainability and enables personalised and customised products.

These advancements have significantly increased efficiency, reduced costs and have improved product quality in the manufacturing industry. Augury’s recent research shows that 39% of European manufacturers already use AI to improve production health. To stay competitive in an evolving landscape, it is crucial for manufacturers to extend AI adoption to logistics and supply chain management.

Cutting costs and significant boosting sustainability

By implementing AI-driven solutions in logistics and supply chains, manufacturers can optimise machine health and maintenance practices by detecting problems long before they happen, which reduces energy consumption and minimises waste. AI can be used to identify process inefficiencies, helping to streamline operations and reduce waste, boosting sustainability and ensuring a more efficient and reliable supply chain. The primary reason? AI systems can make sense of vast and varied streams of input and draw from millions of hours of training, finding correlations and patterns between the thousands of potential data inputs in a manufacturing process that no human could ever spot.

AI can also significantly reduce manufacturing costs by optimising production processes. AI-driven solutions offer predictive maintenance and prescriptive analytics, preventing costly equipment failures and unplanned downtime by monitoring machine health and finding issues before they occur. This allows for efficient scheduling of maintenance activities and avoids mishaps such as loss of product and unexpected breakdown expenses.

Integrating AI with IoT

AI can be strategically combined with various technologies to revolutionise supply chain and logistics operations, driving substantial gains in efficiency, productivity, and quality. When integrated with IoT devices and sensors, AI can turn every manufacturing asset into a digital asset, continuously collecting and analysing massive volumes of data from across the supply chain, including from transport vehicles, warehouses, and inventory systems. This real-time data analysis enables predictive maintenance for equipment, which reduces unexpected downtime and optimises maintenance schedules, thereby ensuring smoother and more reliable logistics operations.

The synergy between AI and IoT extends to optimising supply chain management by enhancing demand forecasting, improving route planning, and streamlining inventory management. With accurate, data-driven insights, companies can better anticipate and respond to disruptions, minimise costs, and enhance overall operational efficiency. This integration not only supports cost savings and operational improvements but also provides a significant competitive advantage by enabling more agile and responsive supply chain strategies.

similar news

How to Unlock Value of Data-driven Logistics

AI in Transportation: the Future of Smart Logistics

Posted on 2 August, 202431 July, 2025 by David Priestman

Logistics is the backbone of global commerce, transporting all kinds of goods from manufacturers to consumers all over the world. With the explosion of e-commerce and changing expectations of consumers, there has never been more pressure or greater demand on the supply chain. To function in an increasingly complex world, logistics and transportation need more intelligent and more agile systems, say Oz Moving & Storage.

Artificial intelligence (AI) is revolutionizing each link in the supply chain, creating transportation solutions that are more efficient, more sustainable, and safer than ever. AI is fundamentally changing the landscape of transportation through automation, predictive analytics, and enhanced decision-making processes. Autonomous vehicles, powered by AI, are becoming increasingly common, promising to reduce human error and increase safety and efficiency.

AI can respond to changing conditions, automate tasks, make data-backed decisions, and predict the future, allowing teams to be proactive rather than reactive. By leveraging vast amounts of data, machine learning algorithms can detect patterns and make predictions with far greater accuracy than humans can alone. AI-powered fleet management systems can analyze data from sensors, cameras, databases, and GPS systems in real time to monitor driver behavior, offer recommendations, and detect potential hazards. What’s more, because machine learning is constantly taking in new information, it can adapt and improve over time. This is important, because the world we live in is constantly changing, and we need systems that can keep up.

Making Logistics Smarter with AI

There are some key ways AI can make logistics and transportation smarter:

Route optimization – Route optimization involves using AI algorithms to find the most efficient paths for vehicles to travel from one point to another, considering numerous variables such as traffic conditions, weather, road closures, and delivery windows. AI leverages historical data and real-time inputs to dynamically adjust routes, ensuring the fastest, safest, and most fuel-efficient journeys. This not only reduces delivery times and operational costs but also minimizes environmental impact by lowering emissions. In complex logistics operations, where multiple deliveries are made on a single trip, AI can sequence stops in an optimal order, further enhancing efficiency.

Predictive analytics – AI-driven predictive maintenance systems forecast potential vehicle breakdowns before they occur, minimizing downtime. Predictive analytics in transportation uses AI and machine learning to forecast future trends and events based on historical and real-time data. This can include predicting vehicle maintenance needs, optimizing inventory levels, forecasting demand for public transportation, and anticipating traffic patterns. By accurately predicting these aspects, companies can proactively manage their resources, reducing downtime and costs. For example, predictive maintenance can alert operators to the need for vehicle repairs before a breakdown occurs, significantly reducing unexpected delays and extending the lifespan of the trucks.

Self-driving trucks – Autonomous trucks are set to revolutionize the freight industry by offering safer, more efficient, and cost-effective solutions. Powered by AI, these self-driving trucks can operate without human intervention, navigating roads and obstacles using sensors, cameras, and complex algorithms. They’re designed to operate in various conditions, making long-haul freight transport safer by reducing accidents caused by driver fatigue. Autonomous trucks can also operate 24/7, increasing productivity. The integration of platooning technology, where trucks drive closely together at consistent speeds, further optimizes fuel efficiency and reduces emissions.

Data-driven decision-making – Data-driven decision-making in transportation leverages big data analytics to inform and optimize decisions across the supply chain. AI algorithms analyze vast amounts of data from diverse sources — including vehicle telematics, traffic reports, weather information, and more — to provide insights that human operators might not discern. Managed transportation services, by integrating AI, enhance overall supply chain efficiency through strategic planning and optimized route execution, complementing the data-driven decision-making process. For instance, logistics companies can use data analytics to understand patterns in demand, adjust their operations accordingly, and thus improve asset utilization and customer satisfaction.

Going Green: AI’s Role in Sustainable Transport

AI-powered logistics can help your fleet reach its sustainability goals. Route optimization doesn’t just make your operations faster and less expensive; it can also reduce wasted resources and increase fuel efficiency. This optimization minimizes unnecessary travel, reduces fuel consumption, and lowers greenhouse gas emissions. For fleets that include electric vehicles, AI can also optimize routes based on the availability of charging stations, ensuring that vehicles are charged in the most energy-efficient manner.

AI can predict demand and optimize load consolidation, ensuring that vehicles are fully utilized and reducing the number of trips needed to transport goods. This not only cuts down on fuel usage and emissions but also decreases wear and tear on vehicles, extending their lifespan and reducing the need for new vehicles and parts manufacturing.

Challenges and Opportunities in Smart Logistics

Despite its potential, the integration of AI into transportation faces several challenges. Privacy and security concerns, particularly related to data collection and processing, are paramount.
The demand for secure, AI-driven logistics solutions is spurring innovation in cybersecurity and data protection. In order to implement AI-driven solutions, transportation companies may need to update outdated technologies and invest in replacements for legacy systems. This transition can come with some upfront costs and a learning curve. AI and automation are poised to transform the jobs that transportation and logistics workers perform. As technology gets smarter, employees in this industry will need to learn new skills as their roles adapt to the changing landscape.

The Future: AI Solutions in Transportation

Looking forward, the role of AI in transportation is set to deepen, with emerging technologies offering even more sophisticated solutions. The development of AI-powered infrastructure, such as smart roads and IoT-enabled ports, will further enhance efficiency and safety. Additionally, as AI technologies mature, their integration with other cutting-edge technologies like blockchain and 5G is expected to unlock new possibilities for smart logistics.

AI works in the transportation and logistics sector by analyzing vast datasets to understand patterns, making predictive analyses, optimizing operations through intelligent algorithms, enabling autonomous decision-making, and continuously learning to improve system efficiency and reliability. The combination of these capabilities allows AI to address complex challenges in the industry.

Similar News

Transforming Logistics with Predictive Analytics