AI and analytics automation for the heavy machinery and logistics industry
AI and Data Science for Mining and Logistics
We develop a real-time analytics dashboard connected to water level sensors and weather data for the coal barging operations in Kalimantan, Indonesia, helping the client optimize their coal logistics through predicting river water levels for up to 7 days in advance.
From power plant operations, to machinery maintenance and coal logistics, Supertype's consultants work with the best in the industry (world's sixth largest coal mining company) to build out new innovations across the mining supply chain.
A predictive, forward-looking approach to maintenance, logs diagnosis, and machinery lifecycle management specifically designed for the heavy machinery industry such as energy and agriculture. From tractors to excavators, we use AI to reduce unwanted downtime.AI in Mining Operations
AI in mining works best on the decisions a mine makes every day: which machine needs attention, how coal moves to port, and how the market around it is shifting. These are the areas we work on.
Fleet and equipment
Dump trucks, excavators and haul trucks drive mining productivity. We build fleet analytics, early warnings and automated reporting for heavy equipment operations.
Production and site operations
From overburden removal and coal transport to power plant operations and maintenance scheduling, we automate the analytics that mining contractors and operators rely on, working with companies across the Alamtri group (formerly Adaro) since 2020.
Commodity and mining market intelligence
Our Sectors for Mining platform (mining.sectors.app) covers production, sales and export volume, logistics, licenses and parent-to-subsidiary structures across metals and minerals, so mining groups can see the market around their operations.
AI in Logistics and Maritime Analytics
River water level forecasting for barging
A real-time dashboard connected to water level sensors and weather data predicts river water levels up to 7 days ahead for coal barging operations, so shipments can be planned around the river rather than surprised by it.
Deep learning for barging decisions
Continual deep learning models on historical data and real-time sensors assist the decision-making behind Adaro's barging operations, with cost savings of USD 2 million a year.
Fleet routing and logistics analytics
Fleet management, route optimization and automated log analysis and reporting for large heavy equipment and transport fleets.
An Analytics-First Approach to Mining Operations
The Supertype team has demonstrated high capability in understanding our challenges, which were relatively new to them in a relatively short time. The resulting model also has a high degree of accuracy, which we can use to reduce the element of surprise in our dynamic coal supply chain. Currently, it's like having a special ability to predict the very dynamic of natural conditions. We are very satisfied with the work of Supertype.
Eri Basuki
President Director, Adaro Mining Technologies
Cost Savings
Deviation Rate
Machinery Components
Deep Learning Models for Barging Operations
Supertype use continual deep learning models on historical data & real-time water level sensors to elevate Adaro's mining logistical operations, enabling a machine learning model to assist in the decision making process that results in a cost savings of USD 2 million annually.
Predictive Maintenance & Machinery Lifecycle
The design and implementation of a comprehensive predictive maintenance system that predicts equipment failure and maintenance schedules, reduce unplanned downtime, and reduce reactive maintenance — the end result is a maintenance cost savings of up to USD 1.2 million annually for each type of heavy equipment across its fleet of mining equipment
Dump Trucks, Excavators, Haul Trucks & More
Mining productivity is highly dependent on the equipment's health and availability. With a fleet of over 500 heavy machinery components and operated by over 7,200 employees of various expertise, there are ample opportunities to systemize and automate the mining operations, be it for coal transports, overburden removal, or maintenance scheduling.
Heavy Industry and Large-Scale Logistics
Despite being relatively new to the field of heavy machinery (in service of the mining industry), Supertype's capabilities are beyond impressive. They understood the technical needs related to prolonging every key component's health index while demonstrate exceptional statistical capabilities during the development of highly tuned Machine Learning models. We are pleased by the work produced by Supertype and look forward to cooperating again in the future.
Mungky Andyan
Plant Engineering Manager, PT. Saptaindra Sejati
Machinery Lifecycle Management
- Predictive Maintenance
- Equipment Health Index
- Remaining Useful Life (RUL)
- Failure Prediction
- Root Cause Analysis
- Unscheduled Downtime Reduction
Industrial IoT & Sensor Data
- IoT Data Analytics
- Sensor Data Integration
- Real-Time Machine Learning
- Streaming Data Processing
- On-Device AI Computing
- Computer Vision on Edge Devices
Automation & Big Data
- CAT- and Komatsu-compatible data processing
- Early Warning System for Machinery Failure
- Fleet Management & Route Optimization
- Automated Log Analysis & Reporting
Frequently Asked Questions
What are practical uses of AI in the mining industry?
The most practical uses are early warnings for machinery failure, fleet management and route optimization, automated log analysis and reporting, and forecasting for logistics such as river water levels for coal barging. Market intelligence on commodities, production and exports adds the view outside the mine.
For the Alamtri group (formerly Adaro), this work delivered USD 2 million a year in barging cost savings. The forecasting behind it is a form of predictive analytics: a dashboard fed by water level sensors and weather data predicts river levels up to 7 days ahead.
What AI and data science solutions do you provide for mining and logistics?
We build predictive analytics, IoT data processing and automation for mining operations and coal logistics. That includes predictive maintenance, early-warning systems for machinery failure, fleet management and route optimization, and automated log analysis and reporting.
The aim is fewer unplanned stoppages and more efficient operations. Reporting jobs fall under report automation, and we have worked with companies across the Alamtri group since 2020.
What is predictive maintenance and how does it help heavy industry?
Predictive maintenance uses sensor and operational data to forecast equipment failures before they happen, so maintenance is scheduled in advance instead of after a breakdown.
For mining and heavy industry this reduces costly unplanned downtime, extends equipment life and improves safety. The models behind it are built with predictive analytics methods, trained on your own machine history.
Can you work with our equipment and fleet data?
Yes. We process data from heavy equipment fleets, including CAT- and Komatsu-compatible data, and integrate it into pipelines for monitoring, optimization and reporting.
That way insights cover your whole operation rather than sitting in isolated machine logs. If you are unsure where to begin, opportunity discovery is how we find the first use case worth building.
Do you offer commodities and mining market intelligence?
Yes. Alongside operational AI, our Sectors for Mining platform (mining.sectors.app) provides market intelligence on commodities, metals and minerals. It covers production, sales and export volume, logistics, licenses and parent-to-subsidiary structures.
Mining groups get operational and market-facing data in one place, as part of the wider Sectors family.