• Thu. Dec 26th, 2024

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TAPEREDPLUSL-R: Rebecca Kitching, Nick Lane and Aman Chahal of TaperedPlus with Dr Alessandro Di Stefano and Professor Farzad Rahimian of Teesside University

Academics at Teesside University are working with flat roofing specialist TaperedPlus  to develop a unique system that uses artificial intelligence to streamline its technical drawing processes.

The Stockton-on-Tees headquartered company is collaborating with researchers from the University’s School of Computing, Engineering & Digital Technologies on a Innovate UK – Accelerated Knowledge Transfer (AKT) project to develop design tools which use Natural Language Processing (NLP).

NLP is a branch of artificial intelligence (AI) that enables computers to comprehend, generate, and manipulate human language.

The project will play a crucial role in TaperedPlus’s mission to digitise its processes, enabling the scaling of product manufacturing and consultancy services in new markets by targeting inefficiencies within its business processes. Once it has been fully evaluated there is the potential to roll it out to the wider industry.

TaperedPlus is a national leader in the design and supply of flat roofing and insulation systems across multiple sectors, including health, education, and retail, as well as additional services in technical specifications such as BIM, acoustic, thermal measuring, and surveying.

The AKT, titled “NLP-Supported Design Tools for Automated, Assisted, and Enhanced Technical Drawing Processes”, proposes creating a design assist tool with Natural Language Processing (NLP) capabilities and other methods like RASE (Requirement, Applicability, Selection, and Exceptions) which will examine diverse digital sources such as emails, PDFs, and Word documents and be able to extract their meaning, known as the semantic information.

By automating the semantic capture process and creating rule administration across the design process, the tool will ensure consistency and protocol adherence.

The potential impact promises increased efficiency in the technical drawing process, leading to a quicker extraction of essential technical details and ultimately contributing to higher turnover and net profitability. Moreover, it introduces cutting-edge technology into the workflow, fostering a culture of innovation and adaptability within the company.

Dr Alessandro Di Stefano, Senior Lecturer in Computer Science, and Professor Farzad Rahimian, Relevant Knowledge Base Supervisor, will utilise their expertise in machine learning, AI, and predictive modelling to support the project.

TaperedPlus and Teesside University have also appointed two Teesside University research associates Ghazal Salimi and Donatus Okonta (PhD students at Teesside University) as the AKT Research Associates to work on the project.

Dr Di Stefano said: “As a University which is dedicated to supporting the growth of the economy in the Tees Valley and beyond by fostering innovation, we are delighted to be working on this project with TaperedPlus.

“By embedding cutting edge technology within its design processes, this ambitious project is destined to have a major impact on TaperedPlus’ efficiency and sustainability.”

Aman Chahal, CEO of TaperedPlus, said: “We are thrilled to be harnessing the power of AI to revolutionise our technical drawing processes and creating a synergy between the technology’s huge potential and our expert knowledge in flat roofing systems.

“By integrating Natural Language Processing into our design tools, we aim to enhance efficiency, precision, and innovation within our operations – enabling us to scale our offerings more effectively.

“I believe that the future of building and construction lies in such innovations, and we are proud to lead the way in digitising and optimising industry standards.”

The four-month programme is part-funded by the Government’s Innovate UK. Innovate UK – Accelerated Knowledge Transfer (AKT) is jointly delivered by Innovate UK and Innovate UK Business Connect.

The programme has been designed to create short-term collaborations between a Business Partner and a UK Knowledge Base to rapidly inject innovation capacity. Inspired by the highly successful partnership model of KTP (Knowledge Transfer Partnership), Innovate UK – Accelerated Knowledge Transfer’s concept is to deliver a rapid and targeted intervention to accelerate the evaluation or development of an innovation project or concept, which has the potential for significant impact for the Business Partner.