Building Smart Factories through Advanced Analytics
We are living in the fourth Industrial Revolution, or Industry 4.0, a new world powered by smart, interconnected technologies that allow us to store and share a massive amount of information at an incredible pace. From artificial intelligence to cloud computing, from machine learning to big data, these disruptive technologies have affected how we live our daily lives, communicate and work. They have also transformed the way entire industries operate and produce services and products.
For example, Industry 4.0 is reshaping the manufacturing process, creating what experts call “smart manufacturing.” The tedious, repetitive operations of traditional manufacturing are now being transformed by advanced analytical tools. These tools allow production and maintenance engineers and other professionals to harvest an incredible amount of data, create predictive and descriptive models, and design decision support systems to address complex challenges. Companies from different areas, including telecommunications, automobile manufacturing and health care, have reinvented their manufacturing processes by employing these tools.
What’s this research about?
Bijan Raahemi, full professor at the University of Ottawa’s Telfer School of Management, has partnered with Ciena Canada, a well-known telecommunications equipment vendor that provides digital platforms and advanced professional services to support the delivery of 5G services. The company was looking into implementing a “smart factory” with AI processes. Raahemi will develop state-of-the art analytic tools to help Ciena automate its manufacturing facility and processes, increase efficiency and improve service quality. His research will be funded by the ENCQOR 5G Ontario Centre of Excellence Academic Technology Development Program.
What’s the potential impact of the project?
Ciena has collected extensive data from its manufacturing facilities, which Raahemi’s team will analyze using big data analytics. “Ciena is looking for ways to leverage new insights that can be derived from its centralized data repository, and we will explore and design novel techniques and innovative solutions to analyze such a large amount of data using machine learning and big data,” says Raahemi. “The developed predictive and descriptive models can be used to make data-driven decisions on Ciena’s manufacturing lines.” he adds. For instance, insights gained from this research partnership could help production and maintenance engineers at Ciena plan resource use and manage bottlenecks more effectively.
This research collaboration will also have a great impact on the lives of Matin Ashtiani and Waeal Obidallah, doctoral students in uOttawa’s Digital Transformation and Innovation program. The two are affiliated with Raahemi’s Knowledge Discovery and Data mining lab. Part of the team working with the Ciena researchers, they stand to gain both academic and industry experience working on innovative solutions for Ciena.