Dynamics of assembly production flow

TL;DR

This paper models assembly production flow as a directed tree to study how manufacturing systems respond to disruptions, revealing complex phenomena like stockout cascades and phase transitions.

Contribution

It introduces a novel discrete assembly process model on a directed tree that captures dynamic behaviors and phenomena in manufacturing systems under fluctuations.

Findings

Identification of overstock cascade phenomena

Discovery of phase transition related to demand and supply fluctuations

Observation of nonmonotonic stockout distribution and chain formation

Abstract

Despite recent developments in management theory, maintaining a manufacturing schedule remains difficult because of production delays and fluctuations in demand and supply of materials. The response of manufacturing systems to such disruptions to dynamic behavior has been rarely studied. To capture these responses, we investigate a process that models the assembly of parts into end products. The complete assembly process is represented by a directed tree, where the smallest parts are injected at leaves and the end products are removed at the root. A discrete assembly process, represented by a node on the network, integrates parts, which are then sent to the next downstream node as a single part. The model exhibits some intriguing phenomena, including overstock cascade, phase transition in terms of demand and supply fluctuations, nonmonotonic distribution of stockout in the network, and the formation of a stockout path and stockout chains. Surprisingly, these rich phenomena result from only the nature of distributed assembly processes. From a physical perspective, these phenomena provide insight into delay dynamics and inventory distributions in large-scale manufacturing systems.