Modeling System Efficiency in Mixed-Model Assembly Lines

Abstract

This thesis details the development of a system efficiency model at the Nissan Smyrna Vehicle Assembly Plant. System efficiency at Nissan is one measure of performance used to allocate new business to plants, and in pursuit of this new business, leaders at the Smyrna Plant maintain a continuous improvement culture where teams are regularly engaged in plant production improvement efforts.

Production improvements at the Smyrna Plant typically focus on fault reduction and line balancing. These efforts leverage either vehicle or process data, but none incorporate both, as no combined data system exists. One can overcome this disconnect by generating an integrated model that links the production sequence with assembly jobs using vehicle model and feature relationships. What results is a repository of work content on produced vehicles containing real and ideal production times, which can be used to measure system efficiency. Creation of such a system greatly enhances existing capabilities to identify bottlenecks in the plant, to improve system health, and to optimize the production sequence.

The completed research demonstrates the modeling capability to integrate product and process data and the use cases of such an integration in enhancing production improvements. The research also demonstrates how internal innovation can happen through the novel use of existing resources to unlock new capabilities. The recommendations focus on implementing the integrated system into stakeholder workflows, creating new data architectures to simplify data management and model development, and re-thinking plant performance models to incorporate current production data.