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The purpose of this study is to investigate the benefits of the turning point layout; a simulation model being applicable for strategic level is designed that compares systems with and without turning points. Specifically, the avoidance of deadlocks and prevention of conflicts is substantial.

Optimization process for different layouts and configuration of autonomous guided vehicles (AGVs) are worked out using statistical methods for design parameters. Regression analysis is used to find effective design parameters and analysis of variance is applied for adjusting critical factors. Also, the optimal design is then implemented in a manufacturing system for an industrial automation and the results are reported.

The outputs imply the effectiveness of the proposed approach for real industrial cases. This research will combine both simulation-based method and optimization technique to improve the quality of solutions.

In AGV systems, the begin-end combinations are usually connected by using a fixed layout, which is not the optimal path. The capability of these configurations is limited and often the conflict of multiple AGVs and deadlock are inevitable. By appearing more flexible layouts and advanced technology, the positioning and dispatching of AGVs increased. A new concept would be to determine each path dynamically. This would use the free paths for AGVs leading to overcome the conflicts and deadlocks.

This paper aims to propose and formulate a complicated routing/scheduling problem for multiple automated guided vehicles (AGVs) in a manufacturing system.

Considering the due date of AGVs requiring for material handling among shops in a jobshop layout, their earliness and tardiness are significant in satisfying the expected cycle time and from an economic view point. Therefore, the authors propose a mathematical program to minimize the penalized earliness and tardiness for a conflict-free and just-in-time production.

The model considers a new concept of turning point for deadlock resolution. As the mathematical program is difficult to solve with a conventional method, an optimization method in two stages, namely, searching the solution space and finding optimal solutions are proposed. The performance of the proposed mathematical model is tested in a numerical example.

A case study in real industrial environment is conducted. The findings lead the decision-makers to develop a user interface decision support as a simulator to plan the AGVs’ movement through the manufacturing network and help AGVs to prevent deadlock trap or conflicts. The proposed decision support can easily be commercialized.

The benefits of such commercialization are increase in the quality of material handling, improve the delivery time and prevent delays, decrease the cost of traditional handling, capability of computerized planning and control, intelligent tracking and validation experiments in simulation environment.