随着国民经济的高速发展，我国近年来在煤矿领域建成了许多高产高效矿井，这对核心装备采煤机的可靠性提出了更高的要求，特别是对易损备件的供应及时性要求越来越高。驱动齿轮作为采煤机上最重要的易损件，采煤机企业在生产制造过程中，加工效率偏低、交货不及时的问题长期未得到解决。因此，本文尝试用基于仿真软件的模拟方法分析驱动齿轮的生产过程，从而指导生产加工过程优化，提高加工效率。

本文以西安煤矿机械有限公司采煤机驱动齿轮加工过程为研究对象，针对目前驱动齿轮出现的生产供应不及时问题，对比分析了该问题的传统经验式解决思路和方法，提出了应用系统仿真的解决思路与方案。经过实地考察调研，发现驱动齿轮的生产加工系统是一个典型的离散事件动态系统,故采用针对离散事件进行动态仿真的Witness软件，研究采煤机驱动齿轮的生产加工工艺，建立基于Witness的齿轮加工过程的仿真模型。通过对整个加工过程综合性能的分析研究，建立符合企业实际生产的模型，优化生产制造过程，以解决驱动轮生产效率偏低、供应不及时这一瓶颈问题。

通过对模型中设备数量和时间因素的优化，提出合理的优化方案。将原生产线模型的数据与优化后模型的数据进行比对，设备利用率和产出量作为主要研究对象，并通过多次独立运行得出最终的优化方案，优化前本模型零部件的月加工能力为43件，优化后月加工能力达到55-60件，加工效率提高了约35%。结果表明，该优化方案可以为企业的实际生产管理、工艺优化和系统分析提供有效的决策支持。

With the rapid development of the national economy, China has built many high-yield and efficient coal mines in recent years, which makes mining companies put forward higher requirements for the reliability of shearer equipment, especially the timely supply of vulnerable spare parts that requirements are getting higher and higher. However, the driving gear is the most important wearing part of the shearer. In the production process of the shearer enterprises, the problems of low processing efficiency and untimely delivery have not been resolved for a long time. Therefore, this paper attempts to analyze the production process of the driving gear based on simulation software, so as to guide the optimization of the production and processing process and improve the processing efficiency.

This article takes Xi'an Coal Mining Machinery Company's driving gear machining process as the research object. In view of the current manufacturing problems of driving gears, compares with traditional empirical solutions and methods, and proposes solutions for applying system simulation. After field investigation, it was found that the production and processing system of the drive gear is a typical discrete event dynamic system. In this paper, Witness software for dynamic simulation of discrete events is used to study the production and processing technology of shearer driving gears, and a simulation model of gear processing based on Witness is established. Through the analysis and research on the comprehensive performance of the entire processing process, a digital model that conforms to the actual production of the enterprise is established, and the manufacturing process is optimized to solve the bottleneck problem of low production efficiency and untimely supply of drive gears.

By optimizing the quantity and time factors in the model, a reasonable optimization plan is proposed. The data of the original production line model is compared with the data of the optimized model, the equipment utilization rate and output are the main research objects, and the final optimization plan is obtained through multiple independent operations. Before optimization，the monthly processing capacity is 43 pieces, and the optimized monthly processing capacity reaches 55-60 pieces, and the processing efficiency is increased by about 35%. The results show that the optimization scheme can provide effective decision support for the actual production management, process optimization and system analysis of the enterprise.