基于整数规划的板木桌类家具生产线平衡优化

郑珂铭; 张乾辰; 康华; 熊先青

doi:10.12326/j.2096-9694.2026020

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基于整数规划的板木桌类家具生产线平衡优化
Balanced Optimization of Production Line for Panelized Wood Table Furniture Based on Integer Programming
1.南京林业大学家居与工业设计学院，江苏南京 210037
2.玛格家居股份有限公司，重庆 401346
2026年40卷第3期页码：86-93
DOI： 10.12326/j.2096-9694.2026020
稿件说明：

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郑珂铭,张乾辰,康华等.基于整数规划的板木桌类家具生产线平衡优化[J].木材科学与技术,2026,40(03):86-93. DOI： 10.12326/j.2096-9694.2026020.

ZHENG Keming,ZHANG Qianchen,KANG Hua,et al.Balanced Optimization of Production Line for Panelized Wood Table Furniture Based on Integer Programming[J].Chinese Journal of Wood Science and Technology,2026,40(03):86-93. DOI： 10.12326/j.2096-9694.2026020.

摘要

板木家具生产线的运行效率、资源利用率及生产成本直接关乎企业的市场竞争力，是木家具制造的重要环节。针对M企业板木桌类家具生产线存在的工序分配失衡、瓶颈工序（生产线中作业时间最长、制约整条生产线生产速度的工序）突出等问题，采用0-1整数规划方法，分别针对固定生产节拍时间（第I类）与固定工作站数量（第II类）两类生产线平衡问题构建量化模型并求解，以明确该生产线的优化潜力。并基于FlexSim仿真平台对优化结果进行模拟验证，对比分析优化前后的方案。结果表明：针对第I类平衡问题，模型求解结果将生产线的工序数量由15道精简至8道，平衡率提升至87.73%的良好水平，各工序平均加工率提高18.62%；针对第II类平衡问题，模型求解结果使生产线的生产节拍时间从53.22 min降至30.01 min，生产线的平衡率同样达到良好水平，各工序平均加工率提升约12%。虽然两类优化路径视角不同，但均能有效提升生产线的平衡水平，研究为板木桌类家具生产线的精益化升级与智能化转型提供可行的参考路径。

Abstract

The operational efficiency

resource utilization rate and production cost of panelized wood furniture production lines are directly related to the market competitiveness of enterprises

constituting a critical link in wooden furniture manufacturing. Aiming at addressing the problems of unbalanced process allocation and prominent bottleneck processes existing in the panelized wood table furniture production line of Enterprise M

this study adopted the 0-1 integer programming method to construct quantitative models and solved them for two types of assembly line balancing problems

namely fixed production tempo (type I balancing problem) and fixed number of workstations (type II balancing problem)

so as to identify the optimization potential of the production line. Subsequently

simulation verification of the optimization results was carried out based on the FlexSim simulation platform

and a comparative analysis was performed between the pre- and post-optimization schemes. The results showed that for the Type I balance problem

the model reduced the workstations from 15 to 8

improved the balance rate of the production line to a good level of 87.73%

and increased the average processing rate of each process by 18.62%. For the Type II balance problem

the model reduced the Takt time from 53.22 min to 30.01 min

while also achieving a good level of balancing efficiency and an approximate 12% rise in average processing rate. Although the two optimization paths differed in perspectives

both could effectively improve the assembly line balancing level. This study provided a feasible reference for the lean upgrading and intelligent transformation of panelized wood furniture production lines.

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