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Starting Semester: Fall 2022 Assigned: Yes Location: Atlanta Ga Submitted:05/18/2022
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High Level Objective: Development of decision support tool to provide visibility and transparency to the upstream supply chains. The tool will measure relevant key performance indicators to assess the supply chains performance with the potential to use Ai+ML to predict disruptive events towards the objective of enhancing flexibility, resilience, and agility. Complication: Supply chain management is based on knowledge and understanding of the supply chain tiers (Tier 1, Tier 2, Tier 3 ...), and with limited visibility to these upstream supply chains management in a data driven method is limited at best. These supply chains at Tier 1 are well documented but visibility of performance is extremely limited. Tier 2 & Tier 3 supplier visibility and performance is nearly non-existent. How would a digital twin of our supply chains network enable Steelcase to proactively monitor performance and identify problems? And subsequently leverage a learning system using Ai+ML to predict performance and simulate alternate strategies? Objective: A digital twin of the seating category supply chains network that drives a tool that monitors the network health and performance for all Tier 1 & Tier 2 nodes. Stretch goal objective: Explore Ai+ML to develop a learning system that explores the ability to predict network performance events before they happen to enable preventative measure actions.
Organized and professional team Optimization Simulation Analytics Supply Chain
H. Milton Stewart School of
Industrial and Systems Engineering
755 Ferst Drive, NW, Atlanta, GA 30332