Proposal of Real Time Predictive Maintenance Platform with 3D Printer for Business Vehicles

TL;DR

This paper introduces a real-time predictive maintenance platform for business vehicles that leverages IoT data, online machine learning, and 3D printing to detect failures, automatically order repair parts, and reduce stock costs.

Contribution

It presents a novel integrated platform combining real-time failure prediction, automatic parts ordering, and 3D printing for vehicle maintenance.

Findings

Effective real-time failure prediction using online machine learning.

Automated ordering and 3D printing of repair parts near the destination.

Reduction in parts stock costs through optimized inventory management.

Abstract

This paper proposes a maintenance platform for business vehicles which detects failure sign using IoT data on the move, orders to create repair parts by 3D printers and to deliver them to the destination. Recently, IoT and 3D printer technologies have been progressed and application cases to manufacturing and maintenance have been increased. Especially in air flight industry, various sensing data are collected during flight by IoT technologies and parts are created by 3D printers. And IoT platforms which improve development/operation of IoT applications also have been appeared. However, existing IoT platforms mainly targets to visualize "things" statuses by batch processing of collected sensing data, and 3 factors of real-time, automatic orders of repair parts and parts stock cost are insufficient to accelerate businesses. This paper targets maintenance of business vehicles such as airplane or high-speed bus. We propose a maintenance platform with real-time analysis, automatic orders of repair parts and minimum stock cost of parts. The proposed platform collects data via closed VPN, analyzes stream data and predicts failures in real-time by online machine learning framework Jubatus, coordinates ERP or SCM via in memory DB to order repair parts and also distributes repair parts data to 3D printers to create repair parts near the destination.