Analytical and simulation models for flexible, robotic automotive assembly lines

To adapt to the rapidly changing market, the automotive industry is interested in flexible assembly lines that can handle disruptions due to machine failures or schedule changes. In this thesis, we propose a new assembly line layout (flexible layout) that uses mobile, robotic platforms to transport cars, which can move out of the line when disruptions occur to prevent blocking other cars on the line. We use discrete event simulation and analytical models to analyze the throughput of the new layout in a single band and two bands with a finite buffer. The simulation results show that the new layout achieves an average of 25.6% and 35.9% speed up over the conventional layout for the single band and two bands cases respectively. We improve previous two-machine line analytical models by augmenting the state of the Markov chain to model every machine in a band. We show that the augmented discrete Markov chain model predicts the throughput within 13% and 18% of the simulation throughput for the conventional and flexible layouts respectively. We further evaluate whether the flexible layout can improve its throughput by learning a policy for parking the platforms. By modeling the agents as independent learners, we apply single-agent reinforcement learning algorithms and show that the policy learned works well but suffers from lack of coordination.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Tung, Yi-Shiuan

Advisor dc:contributor.advisor

• Julie A. Shah.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/119702

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/119702