Warehouse Telematics Automated Forklifts CAN Bus


Forklift Telematics - Predictive Maintenance for 250+ AGVs

Case Studies / Anonymous

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Large OEM (anonymous)

This case study was provided anonymously by a top tier OEM using the CANedge2 on AGVs across multiple manufacturing facilities.

What problem did you solve?

We have 250+ Automated Guided Vehicles (AGVs) deployed across four manufacturing facilities. The AGVs sometimes breakdown due to battery thermal events, causing significant downtime at our sites.

As a result, we needed a way to predict/detect if an AGV was about to experience potential thermal events. The purpose was to setup predictive maintenance and allow our teams to take AGVs out of service to perform maintenance preemptively.


How did you solve it?

Through collaboration with our AGV manufacturer, we were given specific battery KPIs to monitor (and details on how to decode the relevant BMS CAN bus signals).

Next, we needed a way to collect data across all the vehicles for analysis, troubleshooting and predictive maintenance. Here, we decided to use the CANedge2 CAN bus data logger with WiFi.

Forklift Telematics Predictive Maintenance
CANcloud enables remote monitoring and management of data/devices

Specifically, we created a CANedge2 configuration file and distributed it for deployment across the 250+ CANedge2 devices by our on-site technicians. These initial configs included details on the on-site WiFi networks (SSID, password) and our AWS S3 endpoint server. For the initial deployment, the configuration was copied manually onto the device SD cards along with TLS certificates (for secure data transfer).

Once connected, the CANedge2 devices are configured/updated over-the-air through tools like CANcloud. To keep track of devices, we map each CANedge2 serial number to an AGV ID.

The data from all devices is sent to our central AWS S3 server for processing. Whenever a new log file is uploaded, it triggers an AWS Lambda function which leverages the CANedge scripting tools to decode the data and extract relevant BMS KPI information and diagnostic trouble codes (DTCs). Through this process, we determine if an AGV is exposed to a potential thermal event.

If the data indicates a potential thermal event, the DTCs (aka alert flags) are sent to our SQL server and the exposed AGV is automatically sent to its maintenance station. Further, the maintenance team is notified in real-time.

Using the uploaded data, we also create custom reports and browser-based AGV overviews, allowing our maintenance team to access critical AGV information in real-time. It also lets them review historical data for analysis purposes.

Predictive Maintenance CAN Bus Vehicles Forklifts

"The CANedge2 enables plug & play integration with existing infrastructure - with consistent performance and quick support from CSS"


What benefit has this led to?

The CANedge2 deployment has given us the ability to proactively identify AGVs that exhibit BMS alerts and automatically send them to the maintenance area in real-time - thus avoiding costly breakdowns.

Why did you choose the CANedge2?

The CANedge2 is a plug & play and easy-to-use solution for logging our AGV CAN bus data. The devices are autonomous and flexible, enabling automatic logging and offload of data via WiFi - either to a local self-hosted MinIO S3 server or e.g. a central AWS S3 cloud server. Further, the CANedge2 software/API tools enable plug & play integration with our existing infrastructure, while e.g. CANcloud lets us easily monitor device status and perform over-the-air updates.

   — Lead Integration Engineer (anonymous)




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