AI and analytics automation for the heavy machinery and logistics industry
Mining and Logistics
Maritime Transportation Analytics
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.Mining Technology Enablement
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.Predictive Maintenance & Machinery Lifecycle
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.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
