CONFIRM Principal Investigator and Professor of Data Science & Statistical Learning
at MACSI in the University of Limerick
Life science manufacturers are being supported by data scientists to analyse the huge amounts of information generated in their production processes to help improve performance.
Data analytics is providing a critical insight into production processes for the life science manufacturing sector.
By using adaptable algorithms and statistical models, data scientists are analysing vast amounts of data acquired during production to help manufacturers learn more about their processes as well as make improvements and efficiencies.
Data scientist Norma Bargary explains that advances in technology across life science manufacturing, such as state-of-the-art sensing, robotics, automation and machine connectivity are delivering extensive data from cognitive systems in real time.
“This builds a very complete picture of what is going on in the manufacturing process and on the quality of the product,” she says. “Organisations are also striving to become more data driven in this space and utilise that data to make better and faster decisions.”
Bridging the gap
But Bargary, who is Professor of Data Science & Statistical Learning at MACSI in the University of Limerick, and a Principal Investigator at CONFIRM, the Science Foundation Ireland-funded Research Centre for Smart Manufacturing, says: “There is a huge gap between the advanced technology and the amount of data collected, and the algorithms available.
“Our research wants to bridge that gap and develop models and algorithms to make sense of those big, complicated, data sets.” The statistical models and algorithms can highlight relevant data and facilitate and enhance decision-making to benefit the manufacturing firms and, ultimately, the end consumer.
Our research wants to bridge that gap and develop models and algorithms to make sense of those big, complicated, data sets.
Her work at CONFIRM involves applying research to life sciences manufacturing problems and working with companies to gain an in-depth understanding of their processes and data analytics challenges.
The work at the centre also aims to help life science companies understand production issues and processes to make systems more resilient to meet challenges such as Brexit or COVID-19. A further challenge is sustainability, with large amounts of energy required for computing power, storing and analysing vast volumes of data.
CONFIRM has worked with manufacturers to analyse their data and offer a clearer understanding of production processes to identify potential changes that will enhance product yield, understand how products are being used by consumers in the field and model the reliability and life-time of products.
Bargary emphasises the importance of collaboration in research with a range of inter- and trans-disciplinary expertise required, and that the models and algorithms developed also have applications beyond life sciences manufacturing.