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Equipment Health & Maintenance
Overview
The Equipment Health & Maintenance (EHM) solution is an offering that provides predictive equipment analytics to monitor equipment health and performance and boost preventative maintenance strategies. EHM helps reduce equipment downtime, improve reliability, and improve performance while enabling organizations to optimize operations and maintenance expenditures. As a cloud-based solution, EHM can easily scale across downstream operations to fit business needs.
Specifically, the Equipment Health & Maintenance solution delivers the following capabilities for the customer:
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Operational Insights - Real-time visibility and insights on critical equipment health and performance
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Equipment Productivity – Timely alerts and notifications of equipment anomaly and failure detection days or weeks in advance
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Performance & Maintenance Improvement - Enables equipment optimization and proactive maintenance planning to improve performance health and maintenance strategy
The Equipment Health & Maintenance solution boosts asset management to address top downstream business priorities: Reliability, Performance, Cost Control, Safety
EHM addresses the following key challenges:
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Suboptimal equipment performance
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Unplanned equipment failures and downtimes
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High maintenance costs
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Resource constraints
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OPEX constraints
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Inefficient servicing of aging equipment
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Work order backlog
- Disparate tools for monitoring and maintenance tracking
- Lacking advanced equipment analytics
- Disjointed technology and data systems
Customer Reference
Australia’s leading natural gas producer announced an ambitious target of increasing operational efficiencies by 30% over the next three years to its investors. To work towards this target, the customer, headquartered in Perth, is strongly leveraging digitization and automation with AWS services to find the right balance between production and equipment maintenance strategies, in an effort to decrease costs and increase labor productivity.
Specifically, the customer launched a Condition-Based Maintenance Project targeting 1,500 cooling fans in an LNG processing facility to improve equipment visibility for analysis, troubleshooting, and maintenance. Previously, equipment condition data was manually collected only every 3 months and analyzed by a mix of machine and person; the average maintenance work time was 80 days. Since migrating to the AWS Cloud, the company developed and implemented sensors to transmit site equipment data to the cloud, built customized machine-learning models to perform continuous analysis on data in production, and automated the work planning process. The Condition-Based Maintenance Project, has resulted in the following benefits for the customer:
- Cooling fans equipment field data is captured every 15 minutes to provide near real-time monitoring
- The average work planning process has reduced from 80 days to one day
- Templated, automated steps and responses vs. building artifacts and work orders from scratch
- An 80% reduction in inspection costs
How to get started
1
Deployment Readiness Assessment
Activities
- Business Case Definition
- Analytics/ML Feasibility
- Data Strategy
- Security Strategy
Outcomes
- Readiness and Maturity Assessment
- Infrastructure inputs into Planning
- Engagement Scope
2
Deployment planning
Activities
- Evaluate Analytics/ML Strategy
- Data Lake Environment Review
- Enrich Data Lake with Additional Sources
- Architecture Design
Outcomes
- Reference Architecture
- Analytics/ML Strategy
- End to End Engagement Plan
3
Deployment execution
Activities
- Security (Implement Firewalls & Data Security)
- Implement Analytics Workflow
- Build Data Visualization and UI
- End to End Workflow Testing
Outcomes
- Implemented Analytics/ML Solution
- Implemented Data Visualization and UI
- Deployed Use Cases
AWS Solutions Library
Visit the AWS Solutions Library so you can learn how to get started with Equipment Health & Maintenance and other solutions for the energy industry.
