Abstract:The current maintenance strategy for the inservice agricultural machinery equipment is mainly post maintenance, which often results in poor economy, low maintenance efficiency, and the inability to ensure the reliability and safety of agricultural machinery equipment in service. Aiming at these problems, a preventive group maintenance strategy for inservice agricultural machinery equipment was proposed. Firstly, the fuzzy clustering analysis method was used to classify and grade the failure data of agricultural machinery equipment, and the reliability evaluation model of agricultural machinery equipment based on improved competitive Weibull distribution was established, and the reliability level of agricultural machinery equipment was quantitatively evaluated as well. Secondly, based on the seasonal service characteristics and the economic correlation of agricultural machinery equipment, the algorithm model of preventive group maintenance time interval and maintenance opportunity was given. Finally, considering the relationship between the maintenance personnel and the number of agricultural machinery equipment in service, the algorithm model with the minimum maintenance cost as the goal was established, and the group maintenance plan of agricultural machinery equipment was obtained. Combined with the historical failure data and maintenance cost data of 10 small combine harvesters in a farm in Chongqing, the specific implementation case of group maintenance strategy in the service stage of agricultural machinery equipment was given. The results showed that compared with the traditional post maintenance method, the preventive group maintenance strategy reduced the total maintenance times and the total maintenance cost by 22.37% and 19.11%, respectively, which verified the effectiveness of preventive group maintenance strategy in the service stage of agricultural machinery equipment. The proposed method provided an important reference for the research work of maintenance strategy for agricultural machinery equipment.