Multi-Objective Optimization Method for High-Efficiency and Low-Consumption Wire Rope Greasing Process

TL;DR

This paper introduces a method to optimize the wire rope greasing process for faster maintenance and less grease usage.

Contribution

A novel multi-objective optimization model with an improved genetic algorithm for efficient and low-consumption wire rope greasing.

Findings

The model minimizes greasing time and grease consumption while meeting quality and equipment constraints.

An improved genetic algorithm effectively solves the transformed single-objective optimization problem.

Sensitivity analysis confirms the model's robustness to weight coefficient variations.

Abstract

Wire rope greasing is essential for protecting wire ropes from corrosion and wear. To address issues such as low maintenance efficiency and excessive grease usage, this study proposes a high-efficiency, low-consumption optimization control method for the wire rope greasing process. A time objective function for the greasing process and a consumption objective function for grease are established. Considering the actual constraints of greasing equipment performance and greasing quality, a multi-objective optimization model is developed with greasing speed, greasing thickness, grease flow rate, and greasing time as the optimization parameters. The model aims to achieve high efficiency (minimizing greasing process time) and low consumption (minimizing grease consumption). Weight coefficients are introduced to transform the multi-objective optimization model into a single-objective optimization model, which is then solved using an improved genetic algorithm. The effectiveness of the model is validated through a specific case study, and a sensitivity analysis of the weight coefficients of the objective functions in the optimization model is conducted. This research provides valuable support for wire rope greasing process planning and improvement.

Figures