Optimizing Product Wheel Time in Lean Manufacturing Systems

TL;DR

This paper formulates the optimization of product wheel sequences in lean manufacturing as an optimization problem, proposing two solution methods and analyzing their impact on production efficiency and costs.

Contribution

It introduces a novel optimization framework for product wheel sequencing in lean manufacturing, employing integer linear programming relaxation and simulated annealing.

Findings

Simulated annealing outperforms ILP relaxation in certain scenarios.

Optimal product wheel length balances changeover costs and production flexibility.

The methods improve understanding of trade-offs in lean manufacturing scheduling.

Abstract

Lean manufacturing is a production method focused on reducing production times, eliminating waste, and synchronizing production with fluctuating demand. A standard lean manufacturing methodology is the product wheel, a repeating sequence of production of various items. If this product wheel sequence is short, it is easier to interrupt or alter production to adjust for failures or fluctuations in demand, so the manufacturing process is leaner. However, a sequence that is too short results in frequent changeover from the production of one item to the next, yielding higher costs. This study formulates the product wheel methodology as an optimization problem and proposes two approaches to solving this problem: one via a relaxation to integer linear programming, and another via the probabilistic optimization technique of simulated annealing. We assess the performance of these two approaches through simulations and analyze the relationships between production leanness and costs.