Human Activity-based Cycle Time Analysis for Optimizing Repeatable Processes on Manufacturing Floors

Over 70% of tasks in manufacturing are still manual and because of this over 75% of the variation in manufacturing comes from human beings. Human errors were the major driver behind the $22.1 billion in vehicle recalls in 2016. Currently when plant operators want to gain an understanding of their manual processes, they send out their highly paid industrial engineers to run time studies. These studies produce highly biased and inaccurate data that provides minimal value to the manufacturing teams. This project aims to create a smart production assistant that helps manufacturing plant operators gain unprecedented visibility into their manual production operations allowing them to optimize their worker efficiency while maximizing productivity.

Faculty Supervisor:

Jonathan Wu

Student:

Jie Huo;Abdul Muntakim Rafi

Partner:

i-50

Discipline:

Computer science

Sector:

University:

University of Windsor

Program: