One of the most exciting developments, in the recent era, is the rise of machine learning techniques to transform factory level data into information and knowledge for decision-making. Machine learning algorithms and applications are helping manufacturers to explore new business models, fine-tune product quality and optimise manufacturing operations. Globally, manufacturing industry is being revolutionised by machine learning tools that can reduce supply chain forecasting errors, increase defect detection rate and reduce lost sales with better product availability. In a pioneer effort, REDC conducted a customised 2-day programme on, 'Machine Learning for Leading Multinational Food Processing and Packaging Company' from December 31, 2018 to January 1, 2019.
Designed by Dr. Zubair Khalid, Dr. Momin Uppal and Dr. Muhammad Tahir of Syed Babar Ali School of Science and Engineering (SBASSE), the programme reviewed theoretical foundations in mathematics, computer science and systems engineering on the diverse set of machine learning tools. The 2-day programme also provided hands-on experience of working with real industrial data and exposure to modern tools, such as Azure Machine Learning Studio and equivalent. The combination of methodologies was well-received and participants appreciated the exposure and insights provided by the programme.
“Very detail oriented programme and can be used in daily routine for better analysis," shared the programme participant, Saba Rashid, Planning Lead, Tetra Pak.
“Knowledge of the instructors on the subject they were teaching was very good. Practical case studies and individual interaction were the most amazing part of the programme,” said the programme participant, Umar Saeed, Material Planner, Tetra Pak.
