EMEA Regional Coordinator, Whirlpool Corporation
Nukul Sugandhi graduated with a B.Tech + M.Tech (Dual Degree) in Chemical Engineering from IIT Kanpur in 2010. He has around 8 years of experience in Process and Product design industry and is associated with Whirlpool’s Global Technology and Engineering Center in Pune, India for around 6 years. He has extensively worked in Mathematical Modeling & Simulation, Process Engineering, and Thermal & Fluids System design. He is an OPEX Six Sigma BB trained and has been working on developing analytical models to support key Technology and Business functions inside Whirlpool.
Days of supply and availability projections play a crucial role in the process of Supply chain planning. Limited ability to analyze the sensitivity around Supply chain can result in additional logistics costs and may also result in loss of market share due to trade partner issues. Availability/Days of supply are directly affected by Shipment forecasts and Production plan. Robust supply chain planning requires quantification of Supply risks. The paper explores the use of robust design optimization in Supply chain planning using predictive models for stochastic shipment forecasts and production plan. Polynomial Chaos Expansion is used to quantify the Days of supply risk ahead of time by considering fluctuations in shipment and production. Several what if scenarios are run to see the impact of shipment/production fluctuations on Supply risks and a production plan is optimized to provide minimum inventory cost and maximum plant utilization keeping minimum days of supply and availability constrained.