Models for Performance Analysis of a Cross-dock

Open Access
Ankem, Nikita Sudarshan
Graduate Program:
Industrial Engineering
Master of Science
Document Type:
Master Thesis
Date of Defense:
June 01, 2017
Committee Members:
  • Dr. Vittal Prabhu, Thesis Advisor/Co-Advisor
  • AGV
  • Cross-dock
  • Computational Model
  • Max-Flow
  • Throughput
  • Mean Value Analysis
Increasing demand for high-speed delivery without errors necessitates the need of automation in cross-docking which is inspired by higher automation in distribution centers. Speedy processing and redirection of freight to its destination is the integral part of cross-docking operations and the tremendous labor involvement in the process results in variation and errors. For a completely automated cross-dock with robotic arms for loading and unloading and Automated Guided Vehicles (AGVs) to carry the freight across the cross-dock, the thesis proposes computational models based on shape, size and AGV specifications to determine feasibility and performance parameters under given conditions. The ‘Max-Flow model’ uses the Max-flow Min-cut theorem and determines best shape of the cross-dock based on maximum possible throughput under given conditions. Max-Flow is the maximum possible throughput that a given system can have and gives an upper-bound of throughput for the system. The shapes are also compared based on the area and effect of the type of door assignments for inbound and outbound trucks. A more detailed probabilistic model is proposed which uses Mean Value Analysis (MVA) to calculate the throughput for given data of inbound and outbound freight. The MVA model considers traffic and congestion caused due to AGVs carrying the freight and calculates the throughput for given number of AGVs as well as the wait times and queue lengths at each intersection along the AGV path.