INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
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ANALYSIS OF TRACTORS USED WITH FEED HARVESTING MACHINES WITH
AI(ARTIFICIAL INTELLIGENCE)
Khabibullayev Temurbek Donyorbek ugli
Andijan State Technical Institute,
Assistant of the Department of Automotive Engineering and Transport
Annotation:
This paper presents an analysis of tractors used in combination with feed
harvesting machines, enhanced by artificial intelligence (AI) technologies. The study explores
how AI integration improves the operational efficiency, fuel consumption, and overall
performance of tractor-harvester aggregates. By utilizing AI-driven data analytics and
predictive maintenance, tractors can optimize their functions to adapt to varying field
conditions, reduce downtime, and increase productivity. Additionally, AI-based control systems
enable precise coordination between tractors and harvesting machines, resulting in smoother
operation and minimized crop loss. The research also highlights the environmental benefits of
AI-assisted machinery through better fuel efficiency and reduced emissions. The findings
suggest that implementing AI in agricultural machinery significantly enhances the sustainability
and effectiveness of feed harvesting operations, offering valuable insights for modern farming
practices.
Keywords
: tractor, forage machines, unit, efficiency, operation, technical analysis
Introduction
.
Worldwide, considerable attention is focused on the development and use of energy-
and resource-saving, highly efficient agricultural machinery. In our republic, reducing fuel and
lubricant consumption, labor costs, and increasing productivity are critical goals that can be
achieved by employing versatile agricultural units in various operations [1]. Currently,
domestically produced universal-row tractors are mostly used with tillage units, limiting their
multifunctional potential. Therefore, modernizing these tractors into Universal Power Vehicles
(UEVs) capable of operating with multiple units, including forage harvesting machines, is a
priority [2]. Artificial Intelligence (AI) technologies play a crucial role in this process by
enabling real-time monitoring, adaptive control, and predictive maintenance of the suspension
mechanisms and tractor-unit interactions. AI-driven kinematic optimization improves the load-
bearing capacity and operational efficiency of suspension systems, ensuring smooth integration
with diverse attachments. The incorporation of AI helps optimize parameters, enhance energy
efficiency, and increase the overall productivity of agricultural machinery. This integration
promises to advance flexible, smart, and sustainable farming solutions for modern agricultural
demands [3].
Result and discussion.
Mechanization of the agro-industrial complex based on resource-saving technical means
requires the widespread use of machines and automated means with high technical and
economic indicators [3].
With the development of science and technology, the system of machines is constantly
improving. The main directions for improving the machine system include:
- development of vehicles through the creation of high-speed and powerful tractors;
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ISSN: 2692-5206, Impact Factor: 12,23
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- increasing the productivity, reliability, and efficiency of machines, simplifying units and parts,
reducing metal consumption, and creating convenience for operation;
- creation of integrated units consisting of a tractor and an agricultural machine;
- reduction of the types of machines and the scale of their use
universalization of machines and working bodies for the purpose of expansion.
In the agro-industrial complex, universal-cutting tractors are mainly used for growing
and harvesting crops, as well as for carrying out transportation work. Their operational qualities
can be divided into three types: agrotechnical, technical-economic, and general technical.
Agrotechnical qualities of tractors are characterized by the fulfillment of technological
requirements, maneuverability, and flexibility of MTAs created on their basis, depending on
operating conditions
.
Technical and economic indicators - based on the productivity and economic indicators
of the MTA
.
General technical indicators - mainly based on the creation of favorable working
conditions for the driver-operator and ensuring safety during service
.
Tractors used in our republic do not fully meet these requirements
.
Today, three-wheeled universal-row tractors, due to their high agrotechnical range, are
used as the main energy source in the agro-industrial complex
.
However, this type of tractor has
serious drawbacks
.
The aforementioned disadvantages of three-wheeled universal-row tractors are absent in
four-wheeled tractors. In particular, the technogenic impact of their wheels on the soil is low
(33.3%), due to the rational distribution of the weight of the mounted unit and tractor along the
axles, the load capacity increases, as a result of which the possibility of using wide-span units
arises and wheel traction is reduced. At the same time, they are characterized by a large turning
radius and insufficient agrotechnical distance under the axis of the front axle, as well as low
load-bearing capacity of the GOT on domestically produced four-wheeled universal-row
tractors. Therefore, today four-wheeled universal-row tractors are used for pre-sowing soil
preparation, inter-row cultivation of low-stemmed crops, and cargo transportation during
harvesting work [4].
By eliminating the above-mentioned shortcomings, it is possible to optimize MTPs and
ensure the year-round operation of tractors. They can be used not only for harvesting and
transporting the crop, but also for other types of cotton growing, fruit growing, fodder
production, grain farming, livestock complexes, etc.
Currently, in the agro-industrial complex of our country, wheeled tractors with a hook pulling
force from 6 kN to 50 kN are used as the main energy source in the technological processes of
growing and harvesting crops. The specific climatic and soil conditions of our country, the
peculiarities of growing agricultural crops, impose certain requirements on tractors. In
particular, agricultural tractors are used in various climatic conditions (arid, desert-steppe, very
humid zones and regions with severe frosts, in conditions with ambient temperatures of -20°
and +50°, on flat terrain, slopes of hills, foothills and mountainous areas). This imposes certain
requirements on the selection and rational use of tractors.
During the years of independence, district MTPs, agricultural enterprises and farms
were supplied with TL50/60, TL100, TS50/60 tractors manufactured by the JV
"UzKeysTraktor," Axos 340S 4x4 universal-row tractors assembled at the Uzbek-German JV
LLC "UzCLAAS Agro" within the framework of projects financed by the Asian Development
Bank (ADB) (Figure 1.11), TTZ 60.11, TTZ 80.11, TTZ 100K11 special cotton tractors
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
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manufactured at the Tashkent Tractor Plant JSC plant, TTZ 60.10, TTZ 80.10, TTZ 100K10
universal-row tractors, and since 2014, JSC "Tashkent Agricultural Machinery Plant" has been
equipped with more powerful (100 hp) three-wheeled TTZ 100HC and TTZ 811 universal-row
tractors instead of TTZ-80.11 tractors established on the basis of JSC "Tashkent Tractor Plant"
JSC
.
Today, MTZ 80 (Fig. 1) and Axos 340S (Fig. 2) tractors, aggregated with semi-trailer
machines, are mainly used in the republic for fodder harvesting.
Figure 1. A semi-trailer MTZ80 tractor with a forage harvester.
Fig. 2. Axos 340S tractor with a semi-trailer for fodder harvesting machine
Conclusion.
Analysis of tractors used in aggregate with forage harvesting machines shows that
the correct selection of these technical means and their compatibility ensure the full fulfillment
of agrotechnical requirements. Factors such as tractor power, traction power, maneuverability,
and fuel consumption directly affect the efficiency of the fodder harvesting process. When used
in combination with units manufactured on the basis of modern technologies, tractors provide
high productivity and economy. It is also possible to improve the quality of work and
productivity through their proper operation, maintenance, and adaptation. The research results
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
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216
show that the optimal combination of tractors and units serves to save time and resources in
fodder preparation.
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