Abstract: Farmland consolidation suitable for agricultural machinery is a crucial engineering approach for overcoming terrain constraints and promoting the coordinated development of agricultural mechanization and agronomic practices in hilly and mountainous areas. It plays a key role in improving farmland use efficiency, stabilizing grain production capacity, and supporting high-quality agricultural development. However, under complex topographic and ecological constraints, the parameter design for such consolidation often involves conflicts among agricultural machinery operability, terrain adaptability, engineering cost control, and ecological security. In practice, existing design methods have largely relied on empirical approaches or single-objective optimization. This is inconsistent with the suitability of agricultural machinery operation and ecological security. To address these challenges, this study proposed a parameter design method for farmland consolidation suitable for agricultural machinery, aiming to achieve synergy between production and ecology. This study took the typical farmland consolidation area in Gujiao City, Shanxi Province, as the case study. Based on this, high-resolution topographic data were acquired using drone imagery to generate a digital elevation model (DEM), which accurately characterized micro-topographic features and provided reliable data support for plot parameter design. By integrating agricultural machinery operational requirements and hilly terrain characteristics, key indicators (including agricultural machinery operation suitability, terrain adaptability, and ecological constraints) were incorporated to establish a comprehensive plot parameter design system. A multi-objective optimization model was established to minimize excavation and filling volume, plot slope, and shape index. This was subject to constraints relating to machinery operation, soil and water conservation, and engineering feasibility. The multi-objective particle swarm optimization (MOPSO) algorithm was introduced for efficient solving. The Pareto optimal solution set was successfully obtained, revealing the trade-off mechanisms and synergy paths among the objectives. It provides a scientific basis for multi-objective decision-making. The technique for order preference by similarity to ideal solution (TOPSIS) was then applied to evaluate the Pareto solutions and identify the optimal parameter design scheme. The research results showed that there were six parameter design schemes for the farmland consolidation suitable for agricultural machinery. Among them, the 7-stage terrace scheme (N7) obtained by using the Natural Breaks Method had the most significant comprehensive advantages. The corresponding parameter combination included a plot shape index of 1.58, an average plot width of 27.16 m, a plot slope of 9.95°, and an excavation and filling volume of 42790 m³. Compared with pre-consolidation conditions, this scheme significantly reduced the shape index by 57.9%, increased plot width by 70.2%, and decreased plot slope by 23.2%. It ensures continuity in agricultural machinery operation and terrain adaptability, while effectively controlling engineering costs as well as minimizing ecological disturbance. The findings demonstrate that combining the proposed plot parameter design method with the MOPSO–TOPSIS optimization framework can achieve optimal synergy of "production-ecology-economy" in farmland consolidation suitable for agricultural machinery. In this study, the parameter design methodology and optimization framework proposed can help resolve multi-objective conflicts in farmland consolidation suitable for agricultural machinery in hilly and mountainous areas. They also provide quantifiable and generalizable technical pathways, and decision-making references for harmonizing production efficiency and ecological security.