Akiem partnered with Plasma to create a unified data platform, allowing to optimize trains allocation.
Plasma changes the way Akiem, as an operational fleet manager, optimizes its fleet allocation, ensuring seamless operations and maximum efficiency on a very large scale.
Tracking location and status of fleet assets in real-time is essential for ensuring efficiency and timely decision-making.
Standardized and consistent data is crucial for analysis, reporting, and decision-making, leading to improved efficiency and cost management.
Effective exploration and use of data-driven insights are key to optimizing fleet operations and maintenance strategies.
Scaling fleet management to growing volumes and evolving operational needs is vital for long-term success.
Fleet Signals operates by collecting real-time data from trains and/or railway infrastructure to provide insights into their status and location.
How it works:
- Sensors and monitoring systems on trains capture data continuously
- This data is processed to determine the real-time status and location of each train
- Fleet operators use this information for precise allocation and scheduling
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Operational dashboards work by providing a visual and intuitive interface that consolidates essential data and KPIs for fleet management.
How it works:
- Data from various sources, including Fleet Signals, is centralized in dashboards
- Fleet operators can easily monitor the performance, status, and allocation of trains
- Real-time information allows for rapid decision-making
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Predictive Maintenance feature functions by leveraging data analytics and machine learning to predict when trains require maintenance, reducing downtime and costs.
How it works:
- Data from sensors and historical maintenance records are analyzed
- Machine learning algorithms identify patterns and predict maintenance needs
- Preventive actions are scheduled to optimize train reliability and availability
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Plasma's AI-Driven Decision Making feature empowers the train fleet operator by using advanced algorithms to make data-driven decisions for optimal train allocation.
How it works:
- Historical and real-time data is continuously analyzed
- AI models identify the most efficient allocation strategies based on current conditions
- Operators receive recommendations and insights to improve allocation and scheduling at scale
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Our AI-powered fleet management ensures the optimal allocation of resources, minimizing costs, and maximizing operational efficiency for fleet operators.
Our AI-driven solutions enhance safety by predicting maintenance needs and ensuring compliance with regulations, creating a secure and reliable fleet environment.
We empower fleet operators with data-driven decision-making, providing insights that lead to smarter, more efficient, and more profitable operations."