01225 650150 | 0800 772 0795 sales@austinconsultants.com

Industry 4.0

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 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 technologies and manufacturing practices, increased competition, and accelerated product development, all with increasingly tighter budgets.

It can be used for a huge variety of scenarios from accelerating supply chain operating efficiency and process automation to the creation of new customised services and built-to-order on-time products.

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


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 & Integration

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

Austin Consultants is one of the UK’s largest National Instruments Alliance Partners with over 50 years combined expertise in data acquisition, signal processing, and systems integration. Our team are able to harness the value of data from your existing individual and aggregated sources, or deploy additional sensors and instrumentation to collect data from new areas.


Acquiring data from legacy assets is an initial hurdle for many organisations however we are able to offer a wide range of data loggers suitable for every application. We have inhouse expertise to design and build bespoke solutions for complex requirements or we can provide low-cost off-the-shelf plug and play solutions for simple applications. 

Our non-intrusive load monitoring technology simply requires the addition of current clamps to acquire data therefore causing minimal disruption. No customer iInstallation is necessary as any additional sensor installation, if required, is facilitated by our team of highly experienced engineers.

Case Studies


A £multi-billion global leader in the Oil & Gas industry was already collecting significant amounts of operational data and required a partner to help analyse it and improve their operations.

The first phase of the project was to convert the existing finite state machine model to Python code. Using Python to analyse the existing model our team were able to improve the performance of the model by tuning the parameters. We also trained a new machine learning model on the historic data which outperformed the existing model by 20% (tested on data sets provided by the client) which will both reduce operating costs and time to production. 


A £multi-billion global leader in the FMCG industry wanted to optimise the performance of their production line and more specifically a group of identical, highly customised equipment.

The first phase of the project was to install additional sensors on one set of equipment selected by the client. We proposed to analyse data from the additional sensors to identify faulty parts or components (for instance, faults in the existing sensors) in the system. In addition, we worked on captured data to develop a model to detect any faults in the process. With the model, we could provide more accurate and faster information to the controller to improve the performance of the closed-loop system.

The second phase will extend the methodologies to further equipment.


A renewable energy engineering research group were curious to explore how satellite images can be utilised to develop a machine learning prediction model for solar irradiance

Based on an understanding of solar irradiance fundamentals the team reviewed the available meteorological data sets to select the most relevant data to the prediction requirements. The team then formulated a prediction problem with specific forecast duration and resolution.

The second phase of the project involved processing satellite images (The size of a typical image in this project is ~40MB), extracting features, defining performance metrics and training an artificial neural network. The accuracy of the resulting solar irradiance prediction model was higher than our client expected.


An organisation in the Defence sector wished to understand if it was possible to determine specific household activity based on energy consumption.

The first phase of the project was the design of a customised data logger to capture high speed voltage and current data.

The second phase was to detect and disaggregate a specific electrical device profile from the lumped energy data. We trained a detection machine learning model on data from one brand of the device, the accuracy of detecting it when the device is turned on was >95%. The accuracy was above satisfactory when other brands were examined.

The third stage of the project involved the creation of auto-generated reporting.

From our blog

Cyber Essentials Plus Certified

Cyber Essentials Plus Certified

Increasingly high-speed data sampling and feedback rates, high fidelity synchronisation, increased power demands, exponentially increasing volumes of data, and the increasing number of safety factors, means data security and integrity have never been more important....

Solutions for Industry 4.0 and Smart Manufacture

Solutions for Industry 4.0 and Smart Manufacture

13-14 November 2019 our Data Science team will be attending the Smart Factory Expo, Europe's best digital manufacturing show. Part of Digital Manufacturing week the event is aimed at showcasing the latest innovations, technology and best practise in Integrated...

Come and say hello at Smart Factory Expo

Come and say hello at Smart Factory Expo

It's still not too late for tickets Digital Manufacturing Week 2018, 14-15November in Liverpool.  Come along to stand P43 and talk to our data science team about data insight, automation, condition monitoring and prognostics. We look forward to seeing you...

Artificial Intelligence Prognostics Demonstration

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 monitoring to provide condition...

Visit us at Industry 4.0 Summit

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...

News & tips

Sign up to our email newsletter to receive regular LabVIEW tips and related updates from the Austin Consultants team.

Get in touch

Talk to us about your project today.