Bullet-Proofing Manufacturing Supply Chains Though Engineering and Implementation of Automation and Machine-Learning/Big-Data Based Information Systems
Societal upset events such as COVID-19 always expose our weaknesses. These may include the current risks manufacturing industries now face in managing their supply chain in the face of this and future global emergencies. Although most manufacturing companies have implemented reliable supply-chain management software, those applications do not necessarily provide all required operational visibility into their supply chains. For example, Canadian companies may not be fully prepared for supply-chain disruptions because they don’t know which goods and materials are in the supply chain, where they are in that chain, and precisely when their need will become urgent.
The focus of this challenge is therefore to provide ways in which chemical-engineering science may be used to improve supply-chain visibility within the large-scale manufacturing industry. This might be through proposing new ways companies can identify goods and materials as they move through suppliers’ production flow and transportation networks to the company’s receiving docks, or by defining ways a company can engineer the same visibility into outbound goods as they are manufactured, possibly assembled, stored in inventory, and shipped to customers through the transportation network.
Who Can Compete: All 4th or Final Year UG Students
What and Where Do You Submit: A PDF proposal and engineering justification of no more than 5 pages
When is it Due: May 15, 2020 by 5 pm
To Whom Do I submit: Yankai Cao (firstname.lastname@example.org)
What is the Prize: $100 VISA gift card