Meet The Team Q&A | Alex Mollison-Ball | Senior Backend Developer
We know that we’re only as good as our people, and at Ada Mode, we have an impressive team at the helm. This Humans Behind the AI series aims to highlight the talented individuals that work here. For this month’s edition, we’re featuring Alex Mollison-Ball, Senior Backend Developer at Ada Mode.
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“The only constant in life is change… and the accumulation of data” - Heraclitus*
Asset Management. Dealing with disparate data
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How Data Science can Help with the Management of Legacy Assets
Legacy Assets: How data science can help
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AI in Civil Nuclear
With the UK Government setting out its AI strategy last year, there has been time to take stock and reflect on what it means for industry, particularly civil nuclear, where the uptake of AI can be more challenging. In this post, we consider how AI assurance and governance for civil nuclear can be developed in line with existing regulatory principles.
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Meet the Team Q&A | Michelle Barker | Senior Front End Developer
We know that we’re only as good as our people, and at Ada Mode we have an impressive team at the helm. This Humans Behind the AI series aims to highlight the talented individuals that work here. For this month’s edition, we’re featuring Michelle Barker, Senior Front End Developer.
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How to Calculate the Remaining Useful Life (RUL) of Industrial Assets
In this post we explore the benefits and complexities of calculating an asset's remaining useful life (RUL) and how machine learning can help.
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How and When to Implement Predictive Maintenance in FMCG
In this post we explore the key considerations and techniques associated with a successful predictive maintenance strategy in FMCG to improve OA and OEE.
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Meet The Team Q&A | Rebecca Walton | Head of Operations
We know that we’re only as good as our people, and at Ada Mode we have an impressive team at the helm. This Humans Behind the AI series aims to highlight the talented individuals that work here. For this month’s edition, we’re featuring Rebecca Walton, Head of Operations at Ada Mode.
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How to Use Surrogate Models and Simulations to Optimise the Engineering Design Process
In this post we explore how machine learning and surrogate modelling can reduce the time, cost and complexity of the engineering design process.
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COVID Notes: How to get immediate benefit from new sensors with AI
There is no need to wait for data to accumulate before leveraging AI and data science to start benefitting from new instrumentation.
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Race to Zero: How machine learning can help the water industry achieve their Net Zero goals
Race to Zero: How machine learning can help
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The Humans Behind the AI - Samara Vazquez
This Humans Behind the AI series aims to highlight the talented individuals that work here. For this month’s edition, we’re featuring Samara Vazquez, Graduate Data Scientist at Ada Mode.
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The Humans Behind the AI - Nick Barton
This Humans Behind the AI series aims to highlight the talented individuals that work here. For this month’s edition, we’re featuring Nick Barton, Senior Data Scientist at Ada Mode.
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How to develop digital twins for industrial plants to drive operational improvement
Digital Twins for Industrial Plants. They key elements for successful implementation
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Self Organising Maps: The next generation of condition monitoring
Easily digest current system operational state through visualising the system as a 2D map. Isolate zones on the map that represent faulty operation for simple condition monitoring and fault detection. Identify unexpected and potentially fault driven novel operation detected by a poor fit to the map
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The 3 Ds: What industrial operators need to consider before their next data project.
From non-data-rich plants to dealing with disparate data, in this mini-series, we look into the most common issues and constraints that industrial plants face when it comes to improving operations through data. In this edition, we discuss the difficulties that operators encounter when partnering with large technology companies.
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How industrial operators can overcome data scarcity with machine learning
From disparate data to dealing with many small assets, in this mini-series, we look into the most common issues and constraints that industrial plants face when it comes to improving operations through data.
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Machine Learning Control for Automatic Industrial Process Optimisation
Machine learning control can provide benefit to many industrial problems through the provision of optimal and automated control policies to support system owners
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Water: How to get more from acoustic inspection data with AI
Audio data can contain a lot of information indicative of system performance, the unstructured nature of this data type lends it’s self best to deep learning approaches
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How to use machine learning with video data to optimise rail infrastructure maintenance
Rail: How to use machine learning with video data to optimise rail infrastructure maintenance
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