Expertise

maintAI for maintenance optimisation

Optimise maintenance operating models with AI-powered insights and process improvements

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Intelligent asset management
Predictive maintenance – six steps for effective implementation
maintAI analyses your operational data to increase uptime and reduce operating costs.

Industrial operators are under pressure to manage costs, risks and emissions while meeting production, reliability and safety targets.

Today’s assets generate vast amounts of data, but making sense and making the best use of it can be challenging. Information is often scattered across various systems, making it difficult to get a comprehensive view of workflows and optimise operations.

Wood combines cutting-edge technology, machine learning and industry expertise to optimise asset management. Our maintAI solution solves the problem of varied and diverse data to provide decision-makers with timely and actionable insights, enabling you to respond quickly to changing circumstances and identify opportunities for efficiencies.

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Improve plant reliability

Target critical systems, equipment and failure modes through prescriptive recommendation models powered by our vast industry database

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Reduce emissions

Predict and optimise power generation and gas-fired systems, avoid trip-related flaring and methane leaks

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Elevate safety

Apply smart strategies and monitoring technologies to remotely diagnose and predict failures while reducing operational cost

Focus maintenance activities when and where they’re needed

maintAI empowers your decision-making today, streamlines your tasks for tomorrow and cuts maintenance costs now and in the future.

maintAI models apply the latest industry global best practices, lessons learned and digital technology, combining engineering first principles and AI models to rapidly optimise your maintenance operating model.

Our approach lets you make better decisions with your data and create an improvement roadmap to achieve and exceed your performance targets.

Capabilities

Backlog optimisation
Leverages AI, data processing and domain knowledge to recommend backlog removal and prioritise reliability improvements.

Predictive maintenance
Uses advanced data analysis and machine learning to identify equipment failures before they occur, enabling maintenance teams to perform repairs proactively and avoid unplanned downtime

Spares optimisation
Provides recommendations on holding requirements, linking material data with usage rates, our experience library and industry standards.

Maintenance strategy optimisation
Utilising CMMS data such as corrective maintenance history, planned maintenance work orders and asset database information, our models deliver recommendations to optimise maintenance plans.

maintAI applies AI and domain expertise to your data and processes to
optimise equipment maintenance and operations from end to end

The process

1

Gain alignment

We understand your requirements and align with your processes to deliver solutions quickly and accurately, without impacting your current operations.

2

Configure the models

Models are optimised for performance and scalability and validated against industry standards.

We customise models to your unique data to advance your organisational goals.

3

Apply recommendations

maintAI outputs provide actionable insights with a data-driven foundation to help stakeholders make informed decisions.

Our models are agile and can adjust to align with facility changes.

4

Monitor results

Wood will work with you to extract value from the insights maintAI generates and create a plan for ongoing maintenance optimisation.

5

Get assurance

We provide transparency so you can trust the outputs from our models as a layer of validation and risk mitigation.

The results

Results visible in

8-16

weeks

Maintenance cost reduced by

20-40%

on average

Unplanned downtime

10%

reduction for typical clients

By applying our maintAI models, you will get:
  • A clear path to smart maintenance, linking sparing to maintenance and facility health
  • Optimised ‘low-touch’, smart maintenance strategy outcomes
  • Increased critical asset availability
  • Decreased maintenance cost without production loss
  • Reduced production losses and trips, as well as trip-related emissions
  • Reduced person-on-board requirements and a workforce focussed on reliability optimisation
  • Real-time updates of strategy, equipment maintenance and backlog improvement suggestions

See if maintAI works for you

Get in touch with us, and one of our consultants will get back to you shortly to arrange a free consultation or demo.

Schedule a demo Ask a question

Common questions

Wood has been optimising equipment maintenance and reliability
of asset-intensive industries for 25+ years.

  • Technology-enabled, independent engineers – combining domain expertise with data-driven models
  • Superior in our capability offering – full complement of in-house expert knowledge and experience
  • Problem solvers – combination of desktop simulation and field experts for optimum solution development
  • Thought leaders – based on our strong commitment to research, innovation and knowledge sharing, backed by decades of experience
  • First-class in our service – in-house software tools, resulting in improved accuracy, faster service and lower costs
  • Consistent in our delivery – standard processes and quality control for inspections, simulations and risk evaluation
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