A Petri net model for the design and performance evaluation of a flexible assembly system

Abstract

Purpose

The purpose of this paper is to present a Petri net (PN) model based on assembly plan is presented for modeling a flexible assembly system (FAS) configuration, determining an optimal work‐in‐process (WIP), lead time, throughput, and utilization of each station.

Design/methodology/approach

PN model is developed for design, analysis, and performance evaluation of a FAS, keeping in view the assembly line balancing. PN is optimized using weighted WIP. The throughput is bounded by the utilization of the bottleneck machines.

Findings

The PN optimization gives minimum WIP corresponding to the maximum production rate. Minimum WIP leads to minimum lead time. The weighted arcs make the model simple and reduce the optimized number of kanbans. Moreover, the PN model pushes more inventory to the initial assembly phase. This reduces the total cost of the WIP.

Research limitations/implications

In the proposed PN model, the transportation times are included in the transitions times. In the future research, the proposed model can be extended for inclusion of transportation times for AGVs.

Practical implications

Using the PN model, the assembly manager may design, analyze, evaluate, and even optimize the layout of the assembly system for minimum WIP, maximum throughput, and reduced lead time. The determination of the total WIP, total number of stations in the assembly system, and the number of servers at each station may be helpful in factory floor management. The same cycle time is managed at each assembly station for the purpose of line balancing. It may result in the highest efficiency and the shortest idling time along with ease of management and supervision.

Originality/value

This paper presents a new PN model for the design and performance evaluation of a dual kanban FAS.

Citation

Ullah, H. and Bohez, E.L.J. (2008), "A Petri net model for the design and performance evaluation of a flexible assembly system", Assembly Automation, Vol. 28 No. 4, pp. 325-339. https://doi.org/10.1108/01445150810904486