Machinery Selection Research Articles

Novel Technical Parameters-Based Classification of Harvesters Using Principal Component Analysis and Q-Type Cluster Model

The advancement of agricultural mechanization necessitates precise and standardized classification based on technical characteristics to enhance green, efficient, and high-quality development. The current lack of scientific and standardized definitions and classifications for various types of agricultural machinery has become a bottleneck, complicating the machine selection and affecting the compatibility of the machinery with optimized field operations. To address this complexity, we propose a comprehensive classification method that integrates principal component analysis (PCA), cluster analysis, and the qualitative analysis of the functional components for defining and scientifically classifying harvesters. The key functional and technical properties of harvesters were analyzed, and eight primary parameters (machine weight, cutting width, feed rate, rated power, overall machine length, width, height, and working efficiency) were selected, supplemented by nine key functional components (walking mechanism, cutting device, threshing device, separating device, cleaning device, grain collecting device, grain unloading device, cabin, and track size). In the first step, principal component analysis was performed to reduce the dimensionality of the parameters, yielding three principal components with contribution rates of 41.610%, 28.579%, and 15.134%, respectively. One primary parameter from each component was selected for further analysis. In the second stage, Q-type cluster analysis classified the harvesters based on the squared Euclidean distance between the operational parameters, resulting in three classes of harvesters. Finally, functional component analysis provided detailed insights, further refining the classification into four major categories: mini, small, medium, and large harvesters. The results of this work provide a scientific basis for the definition and classification of the harvester products available on the market. This method offers a robust framework for the rational selection and planning of agricultural machinery, promoting sustainable mechanization with a focus on technical parameters and functional attributes.

A Review of Dimension Stone Extraction Methods

This review paper examines extraction methods in the dimension stone industry. Traditional techniques, like thermal shock, hammer and chisel, and plug and feather, were used historically. However, advancements in technology have led to the adoption of mechanized methods. Diamond wire cutting is a highly efficient technique that reduces waste and ensures quality. Challenges like high costs and wire breakage remain. Circular diamond saws and frame sawing are explored as alternative methods. Stone characteristics influence machinery selection and researchers have studied the impact on extraction efficiency. Controlled blasting with explosives shows promise and requires further exploration and optimization.

Selection of peanut butter machine by the integrated PSI-SV-MARCOS method

Production enterprises are enterprises that produce goods or services that aim to meet human needs such as machinery-equipment materials and labour. In order for a manufacturing enterprise to carry out its activities successfully, it must make the right choice when choosing its inputs. The correct execution of production activities and the selection of machinery, which requires high capital investments, also affect the efficiency of the enterprises, the correct use of materials and their costs. Therefore, it is an important decision for business managers to choose the right machine. At this stage, multi-criteria decision making (MCDM) methods are used for choosing the right machine. MCDM methods are methods used in the evaluation of alternatives using more than one criterion. In addition, the MCDM method is used in machine selection as well as in many areas. In this study, PSI, SV and MARCOS methods, which are among the MCDM methods, were used for peanut butter machine selection. First, the criteria and alternatives to be used for the peanut butter machine selection were determined by interviewing a peanut butter factory manager. In the study, while the criteria weights were determined, PSI and SV methods were used, while the machines were ranked with the MARCOS method. In addition, the MARCOS method was compared with other MCDM methods such as PIV, CODAS and WEDBA methods. After the rankings were found according to the methods, the relations between the rankings were examined using the Spearman Correlation method. The main purpose of the study is to determine the suitable butter machine for a peanut paste production factory. Contribution of this study to the literature PSI, SV and MARCOS methods were used together for the first time. In addition, no study has been found in the literature related to peanut butter machine. Therefore, this study is original and contributes to the literature.

An Intelligent Fuzzy MCDM Model Based on D and Z Numbers for Paver Selection: IMF D-SWARA—Fuzzy ARAS-Z Model

One of the most important challenges when building road infrastructure is the selection of appropriate mechanization, on which the efficiency of construction and the life of exploitation depends largely. As construction machinery, pavers occupy a significant place in civil engineering projects, so their selection, depending on a road category, is a very important activity. The objective of this paper is to develop an intelligent Fuzzy MCDM (Multi-Criteria Decision-Making) model, which consists of the integration of D and Z numbers for the selection of construction machinery. The IMF D-SWARA (Improved Fuzzy D Step-Wise Weight Assessment Ratio Analysis) method was used to determine weighting coefficients. A novel Fuzzy ARAS-Z (Additive Ratio Assessment) method has been developed to determine an adequate paver for a lower category of roads (asphalt width up to 5 m), which represents an important contribution and novelty of the paper. A total of 10 alternatives were evaluated based on 16 criteria which were classified into 4 main groups. The results have shown that the alternative A8—SUPER 1300-3 represents a paver with the best characteristics for the considered set of parameters. After that, verification tests were calculated, and they include a comparative analysis with four other MCDM methods based on Z numbers, a change in the normalization procedure, and the impact of changing the size of an initial fuzzy matrix. The tests showed the stability of the developed model with negligible deviations.

Determination of Planting Pattern and Screening of Agricultural Machineries for Maize-Peanut Strip Intercropping: A Case Study in Henan Province of China

Maize-peanut strip intercropping is an important method to solve the contradiction between grain and oil land competition, and achieve stable grain and oil production. However, there are no research reports on the selection and matching of agricultural machinery for such planting patterns at home and abroad. Therefore, this article takes the Henan Province of China as an example to carry out a study. The main content of this study is to determine the pattern of maize-peanut strip intercropping and screen the agricultural machinery from the perspective of deep integration of agricultural machinery and agronomy. A new strip intercropping pattern consisting of four rows of maize and two ridges (four rows) of peanut was determined. A series of operating machineries suitable for this planting pattern were selected for the needs of mechanized sowing, field spraying, and harvesting. Field experiments were conducted to further verify the applicability and reliability of the determined planting pattern and operating machinery. The yield of 4-4 strip intercropping is slightly lower than that of monocropping maize, but the yield of peanut per mu can be increased by 105.2 kg. Moreover, the yield per mu of 4-4 strip intercropping is about 40% of that of monocropping peanut. This study can effectively compensate for the lack of research on the screening of agricultural machinery for maize-peanut strip intercropping at home and abroad. It also can provide beneficial exploration for the full mechanized production of maize and peanut under this planting pattern, and provide reference for the mechanized production of other crops strip intercropping.

Maintenance Technology and Practice of Mooring Anchor Leg in Deepwater Floating Production Facility

“Nanhai Shengli” is a floating production storage and offloading unit (FPSO) in the Liuhua 11-1 oil field in the South China Sea. During its service, the FPSO suffered severe broken anchor legs due to the hostile impact of several strong typhoons. In order to ensure the safety of its mooring system, emergency maintenance operations were carried out on 10 mooring anchor legs under the condition of non-release and non-production of FPSO, which was the first time in deep water in China. Its construction is difficult, high risk, weather and FPSO draft time window requirements are high, the use of reasonable technology and construction methods is the key to efficient completion of the operation, such as simulation analysis, reasonable selection of machinery and resources, efficient control of site construction, accurate environmental monitoring, etc. Taking the release and tieback of the mooring system of "Nanhai Shengli" FPSO in Liuhua 11-1 oilfield as an example, various technical difficulties and key points in the process of release and tieback construction are introduced, and the rules are summarized and analyzed. The safe and efficient completion of this construction operation is not only the embodiment of management level, but also the result of daring to innovate and face challenges. It has a typical guiding significance for the maintenance of mooring anchor leg of similar deep-water floating production facilities in China.

Combination of symmetry point of criterion, compromise ranking of alternatives from distance to ideal solution and collaborative unbiased rank list integration methods for woodworking machinery selection for small business in Vietnam

Woodworking industry plays an important role in the development of Vietnam’s economy. The efficiency of woodworking process depends a lot on the machinery used in the woodworking process. Selecting the best option among a variety of machines is tedious and complex work. However, if the choice of machine is based only on the subjective opinion of the customer, it will lead to mistakes. That mistake is understood that the customer will choose the option that is not the best among the machines proposed by the supplier. Instead, machine selection must be based on all machine parameters. This is called multi-criteria decision making (MCDM). There are MCDM methods, when used it is necessary to know the weights of the criteria. However, there are also methods that do not need to know the weights of the criteria. CRADIS (Compromise Ranking of Alternatives from Distance to Ideal Solution) is a method that, when used, is required to weight the criteria. In contrast, this problem is unnecessary when using the CURLI (Collaborative Unbiased Rank List Integration) method. In this study, three kinds of machinery commonly used for small business in woodworking field were selected. The three kinds of machinery mentioned in this study include wood milling machine, wood saw machine, wood planer. The SPC (Symmetry Point of Criterion) method was used to calculate the weights of the criteria for each kind of machinery. This is the youngest method among the methods of determining the weights for the criteria, it was only found in 2023. The two methods include CRADIS and CURLI were used to rank the machinery kinds. The result showed that in all the surveyed situation, the best alternative is always determined consistently when using CRADIS and CURLI methods. Accordingly, three best alternatives with three different machinery kinds (milling machine, saw machine and planer) were found in this study

Inžinjerske osobine semena Dioclea reflexa (Hook. F.) relevantne za upotrebu mašine kod zapreminske prerade

Interest is growing in the utilization of fringe plant materials such as Dioclea reflexa seed to cater for the need of growing global population. It has demonstrated potentials for a wider use as human food, and as industrial raw material. This research focused on determines the engineering properties of the seed that will be useful in the design or selection of industrial machinery for its processing and bulk handling. Four types of tests were carried out on the seeds: geometric, gravimetric, frictional and mechanical tests. Results revealed that the seed's mean geometric diameter was 25.84mm at 5.60 % (w.b.) moisture content. The individual seed average mass, true density and bulk density were 7.76g, 948.5kg.m-3 and 558.5kg. /m3 respectively. Among the surfaces tested, glass has the lowest coefficient of friction (0.221) while wood has the highest (0.424). Seed orientation during compression test has effect on fracture force, deformation, toughness as well as energy absorbed. Variation of mechanical properties along axes of orientation in quasi-static compression of the seeds showed that major axis has the highest mean fracture force, mean deformation to fracture, and mean fracture energy at 1.38kN, 3.05mm and 2.10J respectively. However, the axis with the highest strength is the minor axis at 1.01kNmm-1 . From energy efficiency point of view, when designing machine for cracking the seeds, provision must be made for the seeds to be oriented in such a way that the applied cracking force will impact the seeds along their major axis.

Evaluation of Current Farm Machinery Selection Practices of Wonji Shoa Sugar Factory

The Government of Ethiopia is trying to improve sugar industry sector by establishing new factories, expansion projects and rehabilitation of existing ones. The main input in this process is agricultural mechanization; however it has been resulted in a huge number of farm machinery of various types and sizes, without consideration of proper selection and matching between tractors and their attachments (implements). This approach had led to high cost of agricultural operation, resulted in an unbalanced distribution of machinery and the agricultural operations throughout the years. Wonji Shoa Sugar factory is one of the victims of the aforementioned problem. The present study was conducted to evaluate the current farm machinery selection practices of Wonji Shoa Sugar Factory. Three soil types namely; heavy clay, vertisol and sandy loam were selected with four field activities (subsoiling, ploughing, harrowing and furrowing). For subsoiling, ploughing and harrowing, 9410-R John Deer tractor with implements of 5 shank and 3.2 m wide mounted subsoiler, 2.8 m wide double gang offset disc plough, and 3.5 m wide semi mounted four gangs double offset were used respectively. For furrowing YTO-1804 tractor and a four bottom fully mounted 4.5 m wide rider was used. For each experiment, the draft force requirement of the implements, the drawbar power, fuel consumption, overall energy efficiency and power utilization ratio were determined at different tractor travel speeds. Subsoiling, ploughing and harrowing were activities were evaluated at the travel speed of w 3, 4, 5 and 6 km/hr. And a travel speed of 4, 5, 6 and 7 km/hr were used for furrowing operation. Linear regression tests were run to examine the interactions between the factors and determine their significant impact. The results of this study noted for furrowing operation as lowest draft force, drawbar power, fuel consumption and energy efficiency of 14 kN, 12.65kW, 13 lit/hr and 8.7 % respectively in sandy loam soil type. The maximum Draft force of 79.8 kW and drawbar power of 131 kW was noted for subsoiling operation in Heavy clay soil. Moreover the results of all operation in all soil type, as indicated by both overall energy efficiency and power utilization factor shows the mismatch between the tractor and implements, as the tractors were overpowered. That means a less amount of the available power from the tractor is being used to operate the implement. If the tractor had been matched with a bigger and compatible implement a better efficiency and higher productivity of the tractor implement combination could have been achieved.

IDENTIFICATION OF THE IMPACT OF THE AVAILABILITY FACTOR ON THE EFFICIENCY OF PRODUCTION PROCESSES USING THE AHP AND FUZZY AHP METHODS

Maintenance has a key impact on the efficiency of the production processes because the efficiency of the machines determines the ability of the system to produce in accordance with the assumed schedule. The key element of the system performance assessment remains the availability of technological equipment, which directly translates into the efficiency and effectiveness of the performed production tasks. Taking into account the dynamic nature of manufacturing processes, the proper selection of machinery and equipment for the implementation of specific production tasks becomes an issue of particular importance. The purpose of this research was to determine the impact of technical and non-technical factors on the material selection of machine tools for production tasks and to develop a method of supporting the selection of production resources using the AHP and Fuzzy AHP methods. The research was carried out in a manufacturing company from the automotive industry.

A Spatial Distribution Empirical Model of Surface Soil Water Content and Soil Workability on an Unplanted Sugarcane Farm Area Using Sentinel-1A Data towards Precision Agriculture Applications

Obtaining soil water content and soil workability data using remote sensing technology with passive sensors has some limitations due to cloud cover, cloud shadow, haze and smoke. This study proposes a method for computing soil water content and soil workability over large areas, faster and in near real-time based on Sentinel-1A (SAR) data. Sample data collected from sugarcane plantations in the Kediri and Sidoarjo districts in East Java, Indonesia, were used to develop a mathematical model of the proposed method using multi-polynomial regression. The performance indicators of the model (RMSE, MAPE and accuracy) were calculated with the results of RMSE = 0.213 and 0.250, MAPE = 16.39% and 18.79%, and accuracy = 83.6% and 81.2% for the training and testing models, respectively. The distribution of soil water content and soil workability can be computed and visualized using a spatial map. The future contribution of this work is to develop a decision support system for the selection of appropriate machinery for sugarcane field operations based on the principles of precision agriculture.

The Impact of Traffic-Induced Compaction on Soil Bulk Density, Soil Stress Distribution and Key Growth Indicators of Maize in North China Plain

The traffic-induced soil compaction in the field has gradually become an important constraint to sustainable agricultural development. A field experiment was conducted to acquire the stress transmitted caused by multiple passes with different types of tractors and to investigate the impact of these stresses on soil bulk density and crop growth. The experiment applied two tractors with different masses: LOVOL M904 (HC) and John Deer 280 (LC), and six different treatments of 0 (C0), 1 (C1), 3 (C3), 5 (C5), 7 (C7), and 9 (C9) tractor passes for each tractor. The results showed that at each number of passes, tractors with small axle-loads at 0–20 cm depth generated higher soil additional stress, while tractors with large axle-loads at 20–80 cm depth generated higher soil additional stress. In the 0–20 cm soil layer, when the number of continuous passes is less than 7 times, the passes of a small axle-load tractor lead to larger soil bulk density, and when the number of continuous passes is more than 7, the compaction of large axle-load tractor leads to larger soil bulk density. At depths of 20–80 cm, compaction by large axle-load tractors results in larger soil bulk density. In this study, different levels of tractor compaction inhibited key growth indicators of maize, resulting in yield reductions. The effect of different tractor load compaction on maize yield increased significantly with the number of compaction passes, with 1–5 tractor passes having no significant effect on yield and 7–9 passes producing greater yield reductions for HC. This study will provide a theoretical basis and technical support for the selection of agricultural machinery and reasonable tillage technology.

Intelligent Novel IMF D-SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure

The quality of road infrastructure largely depends on the quality of road construction and adequate construction machinery. In order to reduce uncertainties and improve the performance of road infrastructure, it is necessary to apply modern and appropriate construction machinery. The aim of this study was to create a novel integrated multi-criteria decision-making (MCDM) model for the selection of pavers for the middle category of roads. A total of 16 criteria were defined and then divided into four main groups, on the basis of which the performance of 12 pavers was evaluated. Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA) with D numbers (IMF D-SWARA) was extended to determine the significance of the criteria for the selection of construction machinery based on two groups of experts. Rough measurement of choices and their ranking as a compromise solution (R-MARCOS) was used to evaluate and rank the performance of construction machinery. The results show that three alternatives out of the set considered can satisfy defined requirements. After that, we performed a multi-phase validity test in which different values of criterion weights were simulated. A comparative analysis with seven other Rough MCDM methods was also created, and the Spearman’s correlation coefficient (SCC) and WS coefficient were calculated to determine the correlation of ranks for sensitivity analysis and comparative analysis. Thus, the obtained results were verified.

Refreshed internal working characteristics of the single screw compressor based on experimental investigation

Single screw compressor is theoretically the optimal selection of compression machinery in mechanical vapor recompression (MVR), low temperature heat-pump system and sea water desalination fields because of simple structure, good force balance, big pressure ratio and wet compression. However, there is less thorough design criteria to guide design of key components in single screw compressor due to the lack of mechanism research. Therefore, it is necessary to investigate the working characteristics of the single screw compressor in detail. In this paper, a dynamic characteristics test rig based on the p-V diagrams on both sides of an oil-injection single screw compressor is established. According to the internal working characteristics based on performance experiment and p-V diagrams, the variations of key performance parameters under different rotation speeds, back pressure and oil injection flowrates are analyzed in detail. Meanwhile, the change mechanism of internal working characteristics are investigated deeply based on the p-V diagram, such as pressurization effect during suction process. In addition, an asymmetrical phenomenon of single screw compressor is found and analyzed in detail. The results provide the design and optimizing direction for single screw compressor.

Selection of Agricultural Machinery Based on Improved CRITIC-Entropy Weight and GRA-TOPSIS Method

In view of the problems existing in the process of agricultural machinery selection, such as inadequate decision-making information, strong subjectivity and quantification difficulty of the index weight assignment, and accuracy deficiency of the selection results, a model on the selection of agricultural machinery based on the improved CRITIC-entropy weight and GRA-TOPSIS method was established in this study. Through analysis, based on the construction of a comprehensive evaluation index system for the selection of agricultural machinery, the combined weight value was determined by combining the weights obtained using the improved CRITIC method and the weights obtained using the entropy weight method. The grey relational analysis method was also combined with the TOPSIS method. The power machinery combination with 88.2 and 73.5 kW of the 68th Regiment of the Fourth Division of Xinjiang Production and Construction Corps was used as an example for verification to determine the optimal power machinery combination. Results indicated that the ranking results were consistent, and the GRA-TOPSIS method was of the greatest degree of discrimination, which was conducive to the selection and evaluation of agricultural machinery equipment. Moreover, the equipment selection results were determined after the comprehensive ranking of machinery types under the different subjective preferences of decision makers was performed.

Selection of heavy machinery for earthwork activities: A multi-objective optimization approach using a genetic algorithm

Earthmoving activity is considered one of the most critical elements in construction projects. The overall cost of earthmoving activity during construction projects can account for more than 30% of the total cost. Moreover, earthmoving equipment emits enormous carbon, which has adverse environmental effects. A mathematical model is needed to optimize the selection of the equipment types (i.e., trucks and excavators) and the numbers of each type to be employed on a particular project, based on the work capacity of each unit, the number of units, and the speed at which each unit travels. The model proposed here is based on a genetic algorithm (GA) based optimization technique for planning earthmoving projects. The model has three main steps: (1) identify all the relevant decision variables for choosing the earthmoving equipment, (2) derive a mathematical optimization model, and (3) apply multi-objective genetic algorithms. For a particular selection of earthmoving units, the model can show how the total project costs will vary concerning the time allowed to complete the project while also providing data showing the total amount of carbon emissions and fuel consumption for the entire project. Data derived from a real-world earthmoving project was employed to test and validate the model. The model was able to show the potential for saving substantial cost and time. On average, the optimization model showed how to obtain savings of 14.35% and 9.5% for the time and the cost objectives, respectively, along with significant reductions in fuel consumption and CO2 emissions. These results suggest that the proposed optimization model would be a valuable tool to support contractors and construction management engineers to minimize earthmoving projects' time and cost.

Design and Experiment on Rotary Cutting Test Bench for Sweet Potato Vine

In order to study the cutting mechanism of sweet potato vine, provide technical support and theoretical basis for the development of sweet potato vine harvesting machinery and improve the resource utilization rate of sweet potato vine, a cutting test bench for sweet potato vine was designed. The test bench consists of two parts: Mechanical part and measurement-control part. In this study, the requirements for the mechanical structure design of the test bench are first put forward and then the structure and hardware of the measurement control system are described. Using this platform, the cutting experiment of sweet potato vine was carried out and the effects of cutter roller speed, conveying speed and feeding amount on cutting torque, cutting power and cutting force were deeply discussed. The test shows that the sweet potato cutting test bench not only realizes the visualization of the test process, but also has the characteristics of small measurement error, stable operation and simple operation. Through experiments, when the cutter roller speed is 1266 r·min-1, the conveying speed is 0.54 m·s-1 and the feeding amount is 1.0 kg, the sweet potato vine cutter has excellent working performance such as high processing efficiency and low energy consumption. The platform can provide reliable scientific basis for cutter design and power selection of sweet potato vine harvesting machinery.

Cost Minimizing Farm Machinery Selection for Rice Farming

In this study, we determine cost minimizing machinery selections for rice farming by solving mixed integer programs with various acreage constraints. Results indicate that small farms can lower costs by hiring customized machinery operations including plowing, rotary tillage, transplanting, harvesting. Farms equipped with large size farm machines can earn extra income and save fixed costs by providing customized services for neighboring small farms. The optimal size of a single paddy farm is found to be 45 to 50 hectares. Policy support is needed for improving machine performance that can lead to increased optimal acreage as well as decreased cost.

Active-passive and passive-passive configurations of combined tillage implements for improved tillage and tractive performance: A review

Proper selection of energy-efficient agricultural machinery helps to reduce drudgery, increase cropping intensity and reduce time required for field preparation. With conventional tillage implements, multiple passes are required to obtain desired seedbed which increase soil compaction due to repeated movement of tractor in field. With combined tillage implements two or more tillage implements are combined to reduce time and fuel energy required for seedbed preparation. In this paper, various researches on active-passive and passive-passive configurations of combined tillage implements have been discussed along with their working principles. It was found that these were associated with less draft, specific energy, and tire slippage compared to conventional implements which provides a sound basis for using them with suitable engine power to improve the power utilization of tractors. Hence, use of these implements could help to reduce soil compaction, labour, fuel cost as well as save time in preparing seedbed. More analytical studies and classical approaches are needed to predict energy requirements of these implements from the knowledge of individual energy requirements of conventional implements to help in proper matching of tractor-implement and also to develop decision support systems. Considering their promising outcomes, they will emerge as effective tools to improve agricultural mechanization.

Embodiment design of a soil bin for soil-tool interaction study

The agriculture industry is an important aspect of Indian economy. The changes occurring in global climate and increased frequency of extreme weather conditions pose challenges for agriculture industry. In such unpredictable conditions, achieving required outputs from farming for supporting continuously increasing population necessitates the mechanization of traditional processes. The selection of machinery for such mechanized setup is a key management task. Tractor is one of the farm machines being used in various farm related operations. Thus understanding constraints imposed on selection of a tractor is a primary factor in decision making process. The study has highlighted importance of power requirement for farming operation in tractor selection process. Thus to determine power requirement for farming operation a study of soil-tool interaction is necessary. A soil bin setup is one of the tools for studying the soil-tool interaction. This work presents the conceptual and embodiment design of a soil bin developed to find variation in draft force with respect to variations in the parameters like tillage depth, operation speed and soil moisture level. The tillage depth and operation speed were found to be directly proportional whereas the soil moisture level was found to be inversely proportional to the draft force.