Artificial intelligence opportunities and an end-do-end data-driven solution for predicting hardware failures

Artificial intelligence opportunities and an end-do-end data-driven solution for predicting hardware failures

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT.

Bibliographic Details
Main Author: Orozco Gabriel, Mario
Other Authors: Kalyan Veeramachaneni and Tauhid Zaman.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2016
Subjects:
Sloan School of Management.
Mechanical Engineering.
Leaders for Global Operations Program.
Online Access:http://hdl.handle.net/1721.1/104304

Internet

http://hdl.handle.net/1721.1/104304

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