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Data Science

We support companies to realise the benefits of integrated manufacturing by releasing the value of data throughout the product lifecycle; increasing data transparency and supporting innovation by providing greater insight to create actionable information.

Data Science

Data science is a powerful interdisciplinary tool that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from your data.

The demand for data science is increasing rapidly, driven by the need to deliver ever greater operational efficiency, keep pace with new, emerging and converging technologies, new manufacturing practices, increased competition, technical challenges and accelerated product development, all with increasingly tighter budgets.

It can be used for a huge variety of scenarios ranging from understanding market trends and product behaviour to automating time-consuming processes and identifying correlations between several data sets to uncover recurring themes or outcomes.


The intelligence gained can:

  • aid improved decision making, future-proof planning and accelerate product development.
  • support task automation reducing the amount of human intervention required and increasing accuracy.
  • identifying changes, trends, and cost-saving opportunities sooner.
  • facilitating product and service innovation.

Data Acquisition

Vast amounts of data are generated throughout the product lifecycle, however, it is only valuable if it can be interrogated, interpreted and converted into actionable intelligence.

Experts in data acquisition and signal processing, our team are able to harness the value of this data from your existing individual and aggregated sources or deploy additional sensors and instrumentation to collect data from new areas.

Our team of highly skilled data scientists are specialists in statistics, computational mathematics, signal processing, database architecture, and mathematical and predictive modelling.

Case Study: Green Running

Our data scientists working with the team at Green Running implemented structured and unstructured databases and distributed computing tools such as Hadoop, Spark and Pig to perform parallelised machine learning and statistical analysis on the huge and growing Green Running dataset.

From our blog

Artificial Intelligence Prognostics Demonstration

At Factories of the Future and Industry 4.0 Summit Manchester, 28 Feb - 30 March 2018, the Austin Consultants team exhibited a demonstration that illustrates the benefits of using artificial intelligence combined with non-intrusive load...

Visit us at Industry 4.0 Summit

Austin Consultants will be exhibiting at the Industry 4.0 Summit, at Manchester Central Convention Complex, on 28 February - 1 March 2018. The Industry 4.0 Summit is a unique opportunity for the manufacturing industry to get together to specifically share ideas...

NI LabVIEW Vision Demo – Robot playing Air Hockey

Video Demo: Description The system uses the NI LabVIEW Vision tools running on the Laptop to perform high speed object and pattern matching at scan rates of up 80fps to follow both the Puck and the Robot Pusher. Using advanced mathematical...

Hidden Markov Model in LabVIEW

Consider this scenario: a guy (say John) has three dice. The shapes of the die are different. Die 1 has numbers 1, 2, 3, 4, 5, 6 on it, Die 2 has numbers 1, 2, 3, 4 and Die 3 has numbers 1, 2, 3, 4, 5, 6, 7, 8, as seen in the following...

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