Expertise
Renewable energy asset management, operations and maintenance
Increase critical asset availability while reducing inventory cost by up to 40%
sparesAI optimises maintenance, repair, and operations (MRO) inventory levels to minimise the cost of your inventory, and maximise the availability of your assets.
Wood’s inventory and materials management expert knowledge is packaged into models and deployed on your data to continuously optimise your asset over time.
Increased accuracy in predictions
Reduced inventory costs and associated working capital
Increased asset availability through avoidance of stockouts
See how sparesAI can help you reduce inventory costs
Big data means traditional approaches to inventory level analysis and optimisation are no longer sustainable
Our research identified that the cost of holding inventory trends towards 30% of capital cost in the ongoing operational expenditure in capital-intensive industries. However, the availability risk on production plants due to stockout is substantial and requires strong reliability knowledge to manage.
This results in companies holding more inventory than required, while still being exposed to availability or reliability risks due to incomplete coverage.
Watch the video to understand how sparesAI works
Peter Carydias, Operations Manager, talks about trends in the industry, why Wood invested in sparesAI, how algorithms can help us predict the future, how we deploy sparesAI and the results we deliver.
sparesAI – domain expertise plus artificial intelligence
sparesAI can rapidly augment inventory data for an advanced and granular analysis based on a scalable, data-driven approach.
Make decisions today with your current data, while consistently optimising your inventory using live reliability information.
Wood has been optimising our clients’ inventories for 20+ years
sparesAI optimises inventory levels at scale. We’ve overhauled classic inventory models and optimised them based on years of R&D and real-life data.
The new models apply a semi-automated approach using data-driven models combined with human experience and proven maintenance management principles.
Rapidly evaluates
larger datasets
Brings operations, maintenance, and integrity insight to your inventory at scale, vetted by our engineers
Forecasts accurate
spare holding levels
Provides real-time updates of
inventory holding suggestions
Uses advanced algorithms to infer reliable solutions, even with incomplete data
Deploys inventory models to client cloud for dynamic inventory analysis
Case study:
$7B Water Corp
Lever
Optimise inventory and improve working capital
<Outcomes
40% reduction in inventory value, while increasing critical spare materials to enable high asset availability (~8% of inventory lines)
Differentiator
We leveraged Wood’s data-driven models on reliability, lead time and cost to quickly improve inventory strategy
sparesAI outlook
Data-driven models are only scratching the surface of what is possible.
Backed by Wood and innovation funding, our team is always pushing to find better, faster, and more robust solutions. With the ability to build specialised teams from over 40,000 experts in 60 countries, our solutions have no boundaries.
Be in the know
Peter Carydias
Global Digital Solutions Manager
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United by our common purpose to unlock solutions to the world’s most critical challenges, we are future ready, now.
