MathWorks Case Studies Predictive Maintenance Software for Gas and Oil Extraction Equipment

	Predictive Maintenance Software for Gas and Oil Extraction Equipment MathWorks

Predictive Maintenance Software for Gas and Oil Extraction Equipment

MathWorks

Technology Category	Analytics & Modeling - Predictive Analytics Functional Applications - Enterprise Asset Management Systems (EAM) Infrastructure as a Service (IaaS)
Applicable Industries	Oil & Gas
Applicable Functions	Maintenance
Use Cases	Predictive Maintenance
Challenge	If a truck at an active site has a pump failure, Baker Hughes must immediately replace the truck to ensure continuous operation. Sending spare trucks to each site costs the company tens of millions of dollars in revenue that those trucks could generate if they were in active use at another site. The inability to accurately predict when valves and pumps will require maintenance underpins other costs. Too-frequent maintenance wastes effort and results in parts being replaced when they are still usable, while too-infrequent maintenance risks damaging pumps beyond repair. Read More
About Customer	In periods of peak demand, Baker Hughes crews work around the clock to tap oil and natural gas reservoirs. At a single well site, as many as 20 trucks may operate simultaneously, with positive displacement pumps injecting a mixture of water and sand at hi Read More
Customer Name	Baker Hughes Read More
Solution	Use MATLAB to analyze nearly one terabyte of data and create a neural network that can predict machine failures before they occur Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Functional Applications - Enterprise Asset Management Systems (EAM)

Infrastructure as a Service (IaaS)

Applicable Industries

Oil & Gas

Applicable Functions

Maintenance

Use Cases

Predictive Maintenance

Challenge

If a truck at an active site has a pump failure, Baker Hughes must immediately replace the truck to ensure continuous operation. Sending spare trucks to each site costs the company tens of millions of dollars in revenue that those trucks could generate if they were in active use at another site. The inability to accurately predict when valves and pumps will require maintenance underpins other costs. Too-frequent maintenance wastes effort and results in parts being replaced when they are still usable, while too-infrequent maintenance risks damaging pumps beyond repair.

About Customer

In periods of peak demand, Baker Hughes crews work around the clock to tap oil and natural gas reservoirs. At a single well site, as many as 20 trucks may operate simultaneously, with positive displacement pumps injecting a mixture of water and sand at hi

Customer Name

Baker Hughes

Solution

Use MATLAB to analyze nearly one terabyte of data and create a neural network that can predict machine failures before they occur

Impact #1	[Management Effectiveness - Data Analysis] Multiple types of data easily accessed.

Impact #1

[Management Effectiveness - Data Analysis]

Multiple types of data easily accessed.

Benefit #1	Savings of more than $10 million projected.
Benefit #2	Development time reduced tenfold.

Benefit #1

Savings of more than $10 million projected.

Benefit #2

Development time reduced tenfold.

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Overview

Predictive Maintenance Software for Gas and Oil Extraction Equipment

Operational Impact

Quantitative Benefit