Manufacturing & Logistics Analytics

Manufacturing & Logistics Analytics

This research area is focused on addressing operational decision-making problems focused on examining shop floor control management technologies to improve operational performance. In particular, the group investigates operational decision-making problems that focus on using information in real-time to sequence operations that closely match the supply and the demand. Much of the research on this topic is focused on information distortion and bullwhip effects while generalized heuristics that promotes coordination in complex production environments within the supply chain is comparatively limited.

Applying business analytical tools to understand and leverage the empirical and formal connections among business drivers in the supply chain provides opportunities to create new knowledge that allows for examining the effects of novel supply chains enablers as well as generating new theories that explain these connections. The application of quantitative tools in production environments seeks to bridge the gap between issues in using information technology in the supply chain, e.g., real-time data management to improve the performance of pull, push, and hybrid production systems.

Main Researcher

Dr. Gültekin Kuyzu

Professor, MIT-Zaragoza
Research Affiliate, MIT CTL
PhD Summer Academy Director

Related Publications