Search Results (4)

Based on the monthly panel data of China’s imports of agricultural machinery products from 2016–2022, this paper uses a multi-period double-difference model to assess the impact of China’s imposition of counter-tariffs on China’s imports of agricultural machinery in the context of U.S.–China trade friction. It is found that China’s implementation of counter-tariffs significantly reduces China’s imports of agricultural machinery products from the U.S. and significantly increases imports from 16 other countries, but the trade diversion effect is lower than the trade suppression effect. Mechanism analysis finds that China–U.S. trade friction affects the technological innovation capacity of agricultural machinery enterprises and the degree of uncertainty in the Chinese economy, which in turn affects China’s agricultural machinery imports. Heterogeneity analysis finds that China–U.S. trade friction has a more significant inhibitory effect on seeding and planting and fertilizing machinery, drainage, irrigation, and water lifting machinery, and other machinery imported from the U.S., and a more significant diversionary effect on agricultural primary processing machinery and harvesting machinery imported from 16 other countries. The imposition of countervailing tariffs mainly affected imports of complete machinery products rather than machinery spare parts. Full article

The maintenance service network is always designed as a multi-level service network to provide timely maintenance service for failed machinery, and is rarely studied in agriculture. Thus, this paper focuses on a three-level maintenance service network location–allocation problem in agriculture, which contains several spare part centres, service stations, and service units. This research aims to obtain the optimal location of spare part centres and service stations while determining service vehicle allocation results for service stations, and the problem can be called a multi-level facility location and allocation problem (MLFLAP). Considering contiguity constraints and hierarchical relationships, the proposed MLFLAP is formulated as a mixed-integer linear programming (MILP) model integrating with P-region and set covering location problems to minimize total service costs, including spare part centre construction costs, service vehicle usage costs, and service mileage costs of service stations. The Benders decomposition-based solution method with several improvements is then applied to decompose the original MLFLAP into master problem and subproblems to find the optimal solutions effectively. Finally, a real-world case in China is proposed to evaluate the performance of the model and algorithm in agriculture, and sensitivity analysis is also conducted to demonstrate the impact of several parameters. Full article

High labor wages brought on by a shrinking agricultural labor force, as well as promises of increased crop yields and decreased labor requirements, have spurred the adoption of agricultural mechanization in Bangladesh. Due to these factors, the market for more complex agricultural machinery, such as rice transplanters and combine harvesters, is growing substantially in Bangladesh. As a result, a market has developed for agricultural workshops to manufacture spare parts within the local communities. However, the current manufacturing practices of local agricultural workshops limit their ability to produce high-quality parts that can compete with spare parts imported from China. This paper presents the analysis of the manufacturing processes used in the manufacturing of two key spare parts for the mechanization of planting and harvesting in Bangladesh: rice transplanter claws and combine harvester blades. The manufacturing processes proposed in this paper use machine tools and manufacturing processes that are ubiquitous in Bangladesh, such as grinders and drill presses. Additional manufacturing processes, such as blanking and forming with punch and die sets, are proposed as the methods for increasing product quality and reducing the manufacturing time required to produce complex geometries, such as those found on rice transplanter claws and combine harvester blades. The results from the experimental testing and the finite element simulations of the deformation processes indicate that local manufacturing of high-quality rice transplanter claws and combine harvester blades is viable with the proposed manufacturing processes. Full article

Because of the continuous improvement of technology, mechanization has emerged in various fields. Due to the different suitable seasons for the growth of agricultural plants, agricultural mechanization faces problems different from other industries. That is, agricultural machinery and equipment may be used frequently for a period of time, or may be idle for a long time. This leads to the aging of equipment no longer becoming regular, the maintenance time of spare parts is not fixed, the number of spare parts stored in the spare parts warehouse cannot be too large to occupy funds, and the number cannot be too small to meet the maintenance needs, so the prediction of agricultural machinery spare parts has become particularly important. Due to the lack of information, the difficulty of labeling, and the imbalance of positive and negative sample classification, this paper used a semi-supervised learning algorithm to solve the problem of agricultural machinery spare parts data classification. In order to forecast the demand for spare parts of agricultural machinery, this paper compared the IPSO-BP neural network algorithm and BP neural network algorithm. It was found that the IPSO-BP neural network was used to forecast the demand for spare parts of agricultural machinery, and the error between the predicted value and the actual value was small and met the accuracy requirements. Full article