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Case Study

Ailsa Reliability Solutions + University of Strathclyde

To integrate condition monitoring sensor technologies, electrical and mechanical, into a unified platform, therefore streamlining the monitoring process.    

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Awards and Achievements

Innovator of the Future 🏆

KTP Associate Matthew Gibson won the Innovator of the Future award at the 2025 Scottish Knowledge Exchange Awards.

Ailsa Reliability Solutions

The business was formed in 2020 as Jamie, the MD saw a change in the market, where industry sectors were starting to look to embrace technology to increase reliability of their plant and assets. ARSL focuses on the following sectors: oil andgas; pharmaceuticals; manufacturing; energy from waste; and, renewables.

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What was the need?

The Challenge

When industrial sites invest in condition monitoring technology, they are often required to pay for multiple OEM sensor with associated dashboard technologies to access their data. Managing multiple dashboards is time-consuming and limits the potential to fully leverage valuable data insights. Another common challenge in modern condition monitoring is that engineers lack the time to analyse all data comprehensively, leaving important insights into a future failure unnoticed. Failures of machines can be costly, with plant downtime sometimes costing millions of pounds in lost production.

This project aims to create an integrated platform that consolidates diverse data pipelines into a single, cohesive solution. Each pipeline requires tailored integration, secure storage, efficient processing, and thorough analysis. The requirement of multiple data streams adds complexity when integrating varied data formats into one system. Additionally, the project will assess the available data and apply AI analytics to enhance analysis, enabling deeper insights and more effective data analysis. These AI models need to be developed to provide value to the engineer so that not only more data can be analysed, but the data can be analysed in greater detail.

What did we do?

The Solution

Ailsa Vision is a platform that ingresses multiple types of condition monitoring sensor technologies and displays them in one location. Ailsa Vision provides alarms and trends for the data so that an operator/engineer only needs one platform to analyse their simplified data. Ailsa Vision will not only display alarms and trends but also provide analytics, graphs, and spectra to give the engineers all the data they require for a full analysis. The aim is when developed, the smart analytics embedded into Ailsa Vision platform will automatically detect up to 80% of faults within electrical and mechanical equipment. This means the product can be scalable, quickly, with less burden on finding “unicorns” who have both the engineering and data science expertise to be able to remotely monitor and service a global customer base.

Once taken to market, this product will be sold to industrial plants and, with the expert system model included, allows site engineers access to expert condition monitoring knowledge without having to undergo years of experience in the field.

Ailsa Vision will be allow the companies who operate with the system to be more profitable and reduce their energy usage across their site.

What changed?

The Impacts and Benefits

Impacts for the Company 

Ailsa Reliability Solutions Ltd (ARSL) are thrilled to be part of the Knowledge Transfer Partnership (KTP) program with the University of Strathclyde. The KTP aligns perfectly with three of ARSL's core values, consultative, partnerships and innovation. This collaboration provides a significant advantage in the development of our Ailsa Vision product. By leveraging the university's expertise in applying AI models to condition monitoring data, ARSL is enhancing its ability to extract valuable insights, ultimately improving the reliability carbon footprint for our customers. While the KTP is ARSL's first engagement with the University of Strathclyde, the partnership has since expanded to a graduate apprenticeship program and a summer internship project. When fully developed, Ailsa Vision will allow us to scale quickly on a global level. We have already proven that our approach will save companies £Millions by eliminating unplanned downtime and provide key information on wasted energy allowing a more positive impact on the planet. Our expectation of the KTP is to harness the knowledge that currently resides within our top analyst minds and then work with the university to build this knowledge into an AI model to allow the system to accurately detect issues in advance of failure for our clients.

 

Impacts for the Academic Team 

Ailsa Reliability Solutions are an enthusiastic industry partner supporting the development of academic outputs. In a methodology that is mutually beneficial to the KTP project and academic pursuits more generally, the team are conducting experiments to create new datasets that can be used to train and test the models embedded in the Ailsa Vision product. This data is intended to be published and shared in an open access manner. Aligned with this data set creation, an academic publication applying data analytics to this data set is in development. Ailsa have demonstrated an interest in leveraging the KTP process to enable Ailsa staff to access further education, with enrolment on Strathclyde’s graduate apprentice programme. Additionally, the KTP and associate are engaging with 4th and 5th year undergraduate projects. ARSL have a fan skid located within the Digital Process Manufacturing Centre (DPMC) which will allow the university to harness valuable data streams for our PhD data science team to help build their AI and Machine Learning protocols. ARSL’s technical expertise will be invaluable in the validation of these models as they have years of knowledge of the equipment in “real life” operation. One key milestone for the university will be to get some key white papers written up on the outcomes form the KTP and PhD studies.

 

Impacts for the KTP Associate 

For the KTP Associate, the project has provided invaluable access to industry experts, offering a rich environment for professional growth. Working closely with these experts has given the associate deep insights into their approach and thought processes, which has been transformative for their own development. The academic side of the KTP is equally rewarding, especially with the associates industrial background, as it creates new ways of thinking that hadn’t been anticipated. This project is incredibly exciting for the associate, particularly as they never imagined deploying AI models in an industrial setting. Seeing firsthand the positive impact these models will have within the industry makes the work deeply satisfying. Their previous industrial experience allows them to fully appreciate the project’s vision and the challenges it addresses, creating a high level of job satisfaction. The KTP programme also offers significant opportunities for skill development, supported by a generous training budget. This budget enables the associate to acquire skills that enhance the KTP project, benefiting all parties involved. After completing several courses through this program, they are now preparing to apply for professional registration, which marks an important milestone in their career development.

The People

Meet the Team

Matthew Gibson

KTP Associate

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Dr Blair Brown

Knowledge Base Supervisor

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Jamie Burns

Company Supervisor

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