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Public Funding for Advanced Analytics Labs Ltd

Registration Number NI649580

A Remote Monitoring and Analytics Platform for Manufacturing Engineers

49,996
2021-01-01 to 2021-06-30
Responsive Strategy and Planning
Conventional factory management and process control systems are integrated on site, requiring monitoring, management and intervention from engineers directly on the factory floor. However, with the recent lockdown imposed by the COVID-19 outbreak, many manufacturers have been forced to either reduce production throughput due to implementation of social distancing initiatives, or else suspend production indefinitely. Such manufacturing companies may have been designated as a 'nonessential business', however often the products they manufacture, for example, hard-disk-drives, machine parts and medical components, are essential to facilitate working from home, derive innovation and maintain societal harmony. For manufacturing companies, the financial impact of this can lead to business closure and the redundancy of employees. Since manufacturing companies often recruit employees in a range of roles from the surrounding geographical area, this can lead to the decline and deterioration of communities which are already struggling due to the restrictions imposed by the lockdown. With advanced data analytics becoming a key enabling technology across the manufacturing sector, there is now the potential for automated large-scale process systems to make the most of the large volumes of data they collect, and furthermore for users to remotely manage the analytics underpinning the manufacturing process. Advanced Analytics Labs (AAL) are developing a cloudbased Remote Monitoring and Analytics Platform for the manufacturing sector. The platform will enable production engineers and managers to remotely view factory state, interact with AAL's advanced machine learning models and communicate with on-site staff to effect changes in the production process. This would represent a step-change for how the factory floor can be managed in a remote fashion, for both this and potential future pandemics, or even if remote working is sought to become the norm. Using the tool, engineers and process managers will be able to view the status of their production schedule and current units passing along the manufacturing process, remotely. Additionally, the advanced analytics models which provide predictions on final product quality using novel multivariate analytics can be used to make suggested/theoretical changes to a digital twin, in order to determine the optimal way of making reworks to bring units back to specification, an enabler for facilitating a circular economy for companies. The messaging/workspace component of the application may be used to share the optimal rework strategy for specific units with the skeleton factory floor staff on site, thereby further facilitating transition to Industry 4.0 in the era of advanced analytics.

The development of a dynamic analytics software platform, which explains the key core dependencies of the vast multifaceted metrology problems within volume manufacturing through a highly visual interactive interface

272,581
2018-03-01 to 2019-08-31
Collaborative R&D
"This project seeks to develop a dynamic analytics software platform, which explains the key core dependencies of the vast multifaceted metrology problems within volume manufacturing through a highly visual interactive interface where final product performance is determined by the degree of conformance to a 'sameness' metric. This innovative approach pioneered by Belfast-based SME, Data Analytics Labs (DAL) will initially be deployed in one of the critical process blocks at the Seagate Technology wafer fabrication site in Springtown, Northern Ireland. This capability will enable improved productivity through faster cycles of learning for new product introductions, reduced scrap and faster time-to-volume ramps. The project brings together a world-class interdisciplinary UK team. Data Analytics Labs is an ambitious SME with strong growth projection through both collaborative industrial research and independent R&D. DAL has expertise in advanced modelling, machine learning, big data analytics and data engineering. DAL will be able to exploit commercial benefits of a new novel diagnostic and visualisation algorithm application in other technological areas, such as semiconductors, for which commercial exploitation is a viable short or medium term goal. Seagate Technology is a world leader in data storage technology, with approximately 40% share of the global hard disc drive (HDD) market. The Springtown facility produces around 25% of the total global demand for recording heads, the critical sensor in a HDD. As one of only five comparable wafer fabrication sites in the world and the only site in Europe, Seagate is ideally placed to demonstrate commercial viability of the analytics platform in Northern Ireland. For DAL the benefits of grant funding will be significant. This project will enable DAL to prove the viability of a dynamic analytics software platform technology in the data storage field, opening up many business opportunities within the semiconductor industry, an industry which DAL has yet to penetrate."

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