实例探究 > Transportation Success Story

Transportation Success Story

公司规模

1,000+

地区

America

国家

United States

产品

Aspen Mtell

技术栈

Machine Learning

实施规模

Enterprise-wide Deployment

影响指标

Cost Savings

技术

分析与建模 - 机器学习

适用行业

铁路与地铁

适用功能

物流运输

用例

预测性维护

服务

数据科学服务

关于客户

The customer is a major U.S. transportation company responsible for delivering goods on time, safely, and reliably. The company operates a large fleet of locomotives and is committed to ensuring the highest levels of operational efficiency and reliability. However, the company was facing significant challenges due to undetected catastrophic failures of locomotives. These failures were not only costly in terms of repairs and additional operational costs but also resulted in fines and disruptions in the delivery of customer goods. The company needed a solution that could help it detect these failures in time and prevent them from occurring.

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挑战

A major U.S. transportation company was facing significant losses due to undetected catastrophic failures of locomotives. These line-of-road (LoR) engine failures were costing the company over a million dollars each in repairs, additional operational costs, and fines. The company's existing reliability techniques were not sufficient to detect these failures in time, leading to disruptions in the delivery of customer goods and impacting the company's reputation for safety and reliability.

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解决方案

The company partnered with AspenTech and implemented their product, Aspen Mtell. Aspen Mtell is a machine learning-based solution that was used to examine laboratory analysis data from engine lube oil samples. Through multi-variate machine learning analysis of archived samples from the 30 “bad” actors, Aspen Mtell insight discovered normal behavioral patterns and exact failure patterns. These insights were then transferred to Agents executing on as many as 600 locomotives. The solution provided the company with the ability to detect potential failures in advance, allowing them to take preventive action and avoid costly repairs and operational disruptions.

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运营影响

Within four months of implementing the Aspen Mtell solution, the company was able to prevent 10 major locomotive failures. This was achieved through the foresight alerts provided by the Aspen Mtell Agents, which included prescribed action to prevent the failures.
In one instance, even when an engine successfully passed a low-pressure test, the Aspen Mtell application engineer noticed a failure signature and alerted management. A subsequent high-pressure test showed leaks in eight places, preventing an expensive, looming LoR failure.
After scaling the Aspen Mtell solution to more than 4,000 locomotives, the company was able to detect failures on 96 engines, resulting in additional major savings.

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数量效益