Architecture for Industry 4.0-based Manufacturing Systems

Achal Arvind
Master's Thesis, Tech. Report, CMU-RI-TR-16-43, Robotics Institute, Carnegie Mellon University, August, 2016

View Publication

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.


Industry 4.0 or the fourth industrial revolution refers to the trend of integrating cyber-physical systems into manufacturing. Outfitting manufacturing units with an array of sensors/end effectors provides the ability to build a virtual model of the unit. This virtual model can, in turn, be used for automated decision making leading to improvement in performance. We propose a next-generation computational framework for dynamic, data-driven optimisation of production. In keeping with the principles of Industry 4.0, our architecture is easy to reconfigure and connect to various hardware/software devices allowing for quick reconfiguration of factories. It has a live representation of the real world enabling managers and other users to keep track of activities in the factory. It also provides users with statistics and other abstraction tools to augment decision-making capabilities and has the ability to automatically allocate resources thereby allowing for nearly autonomous operation of the factory. We further demonstrate an implementation of the proposed architecture on a model problem developed in conjunction with Foxconn. The implementation consists of a Robot Operating System (ROS) based event simulator, ROS based visualization platform and multiple planners. We implement a baseline strategy inspired by the working of Foxconn factories and then show how our architecture improves upon the performance of the baseline method. The proposed architecture yields an almost 100% improvement over the baseline strategy.

author = {Achal Arvind},
title = {Architecture for Industry 4.0-based Manufacturing Systems},
year = {2016},
month = {August},
school = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-16-43},
} 2017-09-13T10:38:18-04:00