Modeling
M. A. Hormozi; H. Zaki Dizaji; H. Bahrami; N. Monjezi
Abstract
IntroductionThe development of mechanization and machine technology can have positive and negative effects on the economic, social, and environmental conditions of a region. Conflicts in these areas complicate the selection and optimization of sustainable mechanization systems. One of the basic questions ...
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IntroductionThe development of mechanization and machine technology can have positive and negative effects on the economic, social, and environmental conditions of a region. Conflicts in these areas complicate the selection and optimization of sustainable mechanization systems. One of the basic questions in the selection of a sustainable agricultural mechanization system is how and with what methodology would it be possible to propose the closest mechanization model that will overcome the simultaneous contradictions between the three pillars of sustainability; taking into account the natural and technical limitations in agricultural production. What is the appropriate approach considering the economic, environmental, and social aspects? The current research aims to provide a framework for an optimal mechanization model to achieve the goals of agricultural sustainability so that it can be implemented and applied practically. It is possible to provide a model that addresses the conflicting economic, social, and environmental aspects by quantitatively optimizing the level of mechanization.Materials and Methods In this study, a framework is applied whereby contradictory goals of agricultural sustainability can be achieved simultaneously. After selecting the indices and data collection, by combining Shannon entropy and TOPSIS, the similarity index was obtained for each objective. The similarity indices and values of the Benefit-Cost Ratio calculated for each system were considered as coefficients of three objective (economic, social, and environmental) functions in multi-objective optimization. The multi-objective optimization model was applied to achieve sustainable mechanization patterns and was solved using the NSGA-II algorithm. For framework validation, paddy production mechanization systems in the Ramhormoz region located in southwestern Iran were analyzed with constraints: land, water, and machinery. The five mechanization systems of paddy production included puddled transplanted, un-puddled transplanted, water seeded, dry seeded, and, no-till.Results and DiscussionPareto-optimal solutions of different scenarios with water and machine constraints showed that this framework cannot only meet the sustainable goals, but also the optimal allocation of mechanization systems is identified and the effect of different scenarios under different constraints can be examined. The sustainability goals between the no-tillage and planting with puddling systems are highly contradictory. The no-tillage system has the highest score in the environmental aspect and the lowest score in the social and economic aspects. This modern system was developed in Ramhormoz three years ago and has faced technical, economic, and social challenges ever since. The cultivated area using this system was 43 hectares in 2019. Despite the speed and ease of planting with this system, and its direct environmental benefits, the possibility of fungal outbreaks is raised due to the presence of wheat residues from previous cultivation and the warm and humid environment of cultivation. Additionally, weed outbreaks caused by periodic irrigation have greatly affected the satisfaction and profitability of this system, leading to the highest amount of pesticides consumed among the studied systems. The results of multi-objective optimization of sustainable rice mechanization systems in Ramhormoz city showed that the total surface area of optimal point systems is in the range of 2700 to 3200 hectares, which is close to the area under rice cultivation in Ramhormoz (3310 hectares) and it indicates that the output of the model is according to the applied restrictions and close to reality. The limitation of machinery and water has made the two planting systems of un-puddled transplanting and dry-seeding better than other systems. Removing only the machinery restriction can lead to an increase in the area under rice cultivation by about 700 hectares. This means that the requirement for the development of sustainable rice cultivation in Ramhormoz is to strengthen and support modern mechanized systems of no-tillage, dry-seeding, and planting with puddling, with a focus on systems with less water consumption which are the systems with higher levels of mechanization. Without water limitation, if the model is subject to the current machinery limitations, the optimal mechanization systems are the more traditional ones such as transplanting without puddling and wet-seeding.ConclusionOne of the most fundamental challenges in the development of mechanization is identifying systems that can best balance the economic, social, and environmental aspects of sustainability and minimize environmental damage whilst maximizing economic and social benefits. Using the framework for sustainable mechanization will not only accomplish sustainable goals in identifying the optimum agricultural mechanization level, but it will also allow researchers and implementers in the agricultural sector to examine the outcome of various scenarios under different constraints. This framework can be used to find the optimal model for mechanization of all stages of tillage, planting, harvesting, and post-harvest in diverse geographical areas.
Agricultural waste management
V. Ebrahim Khanloo Sisi; N. Monjezi; M. Soleymani
Abstract
IntroductionSugarcane is one of the strategic products of Khuzestan province, which is cultivated in 10 active agro-industrial sites and covers an area of about 110,000 hectares of irrigated farms in the province. Sugarcane harvesting, like most crops, is done by special sugarcane harvesters. Due to ...
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IntroductionSugarcane is one of the strategic products of Khuzestan province, which is cultivated in 10 active agro-industrial sites and covers an area of about 110,000 hectares of irrigated farms in the province. Sugarcane harvesting, like most crops, is done by special sugarcane harvesters. Due to the life of machines and also the amount of heavy machine operations in each season of sugarcane harvest, the loss is inevitable. On the other hand, in Khuzestan province, due to lack of studies, there is little information in this area. Therefore, the aim of this study is to investigate the extent of losses during sugarcane harvesting operations, taking into account factors such as cultivars, age of sugarcane, and reaping speed of the Astaf 7000 model. The study will be conducted at the sugarcane agro-industrial site of Dehkhoda in 2021.Materials and MethodsThe experiment was conducted as a factorial split-plot design based on randomized complete blocks (RCBD) with three replications. The first factor included four levels of cultivars (IRC-12, CP48-103, CP 73-21, and CP69-1062), the second factor included three levels of harvest age (plant, Ratoon 1, Ratoon 2), and the third factor included three levels of speed (3, 5, and 7 km h-1). Sampling was carried out under the same and constant conditions with respect to soil moisture content, harvester operator, harvester characteristics, harvester settings, and crop density in each field.Results and DiscussionThe results of analysis of variance of the data obtained from measuring sugarcane losses showed that the effect of cultivar on yield, full-length sugarcane, chopped sugarcane and splinter sugarcane had a significant effect at a probability level of one percent. The effect of age had a significant effect on yield, full-length sugarcane, chopped sugarcane with a probability level of one percent, but had no significant effect on the amount of splinter sugarcane. The interaction between cultivar and age had a significant effect on yield, chopped sugarcane, and full-length sugarcane with a probability level of one percent and on splinter sugarcane with a probability level of five percent. The effect of machine speed had a significant effect on full-length sugarcane, chopped sugarcane and splinter sugarcane with a probability level of one percent, but had no significant effect on yield. The interaction of cultivar and machine speed had a significant effect on yield, full-length sugarcane, chopped sugarcane and splinter sugarcane with a probability level of one percent. The interaction effect of age and machine speed on yield had a significant effect on full-length sugarcane and splinter sugarcane with a probability level of one percent and on the amount of splinter sugarcane with a probability level of five but had no significant effect on yield. Also, the interaction of cultivar, age and machine speed had a significant effect on yield, full-length sugarcane and chopped sugarcane with a probability level of one percent, but had no significant effect on the amount of splinter sugarcane. The results showed that the highest yield in CP69-1062 variety was observed in the plant farm with average machine speed (144.33 tons per hectare). Also, the highest amount of sugarcane losses in cultivar CP48-103 in Raton II and with 7 km h-1 machine speed (3.32 tons per hectare), the highest amount of chopped sugarcane losses in cultivar CP48-103 in plant farm and with average speed (1.78 tons per hectare) was observed. According to the results under the interaction of cultivar and device speed, the highest amount of sugarcane losses in CP69-1062 cultivar and high speed (0.314 tons per hectare) as well as IRC-12 cultivar and high speed (0.308 tons in Hectares), and under the interaction of farm age and speed of the harvester, the highest amount of sugarcane losses was observed in Ratoon farm and the high speed of the harvester (0.300 tons per hectare).ConclusionTherefore, in order to reduce the amount of losses in sugarcane fields, it is recommended to use resistant and somewhat later cultivars for cultivation, because early cultivars are more fragile during harvest due to stem fragility and the rate of losses increases. Also, Harvester speed optimization reduces the amount of losses, and due to the increase in the rate of losses in reclaimed farms, it is recommended to create more resistant stem tissue by proper plant nutrition and more care to reduce the rate of losses in ratoon farms.
N. Monjezi; M. Soleymani
Abstract
Introduction Sugarcane cultivation in Khuzestan province is in the form of planting in-furrow. Due to the fact that in a machine harvesting, the reaper is not able to fully harvest the straw in the furrow, in the planting in-furrow method, it is necessary to transfer the rows of straw to the stack. So ...
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Introduction Sugarcane cultivation in Khuzestan province is in the form of planting in-furrow. Due to the fact that in a machine harvesting, the reaper is not able to fully harvest the straw in the furrow, in the planting in-furrow method, it is necessary to transfer the rows of straw to the stack. So one of the measures at the time was hilling up operations or stacking reeds planted in the furrow. Therefore, due to the salinity of irrigation water and high groundwater levels, which have increased the salinity of sugarcane fields in Khuzestan province, planting this product in summer to protect the seedlings against salinity is mandatory in the furrow. On one hand, due to the difficulty of harvesting operations in the furrow during the harvest season, and on the other hand, because of the reduction of waste during harvesting, the plant needs to be located on the ridge. Therefore, in sugarcane fields, when the seedlings are established and grown, the furrow and ridges are replaced, and to perform this operation special machines are required. According to the study, so far there has been no scientific and reasoned report on the study and evaluation of different types of hilling up devices and different speeds in sugarcane cultivation, and the use of machines in sugarcane cultivation and industry is based solely on objective observations. Therefore, in this study, three different types of devices have been evaluated in two soil textures and three different forward speeds as a step towards choosing the best type of machine and optimal speed of hilling up operations in sugarcane cultivation.Materials and Methods The purpose of this study was to evaluate three different methods of sugarcane hilling up in two soil textures and three different forward speeds. Research treatments include: soil texture (clay loam and silty clay loam), hilling up methods (6-shanks subsoil + 10-shanks subsoil, 8-shanks subsoil + hilling up device No. 1 and 8-shanks subsoil + hilling up device No. 2), and forward speeds (5, 6, and 7 kilometers per hour). Design of a factorial experiment based on randomized complete block design with three replications in Amirkabir field 208 (ALC 200 field 8) with clay loam texture and cultivar CP69-1062 and farm ARC14-22 with silty clay loam texture and cultivar CP69-1062, 15% moisture, and first-year cultivation was performed. The test plot includes 108 furrows. The area of each plot was two furrows. The length of each furrow was 250 meters (equal to the length of the sugarcane rows). To avoid affecting the interactions of the treatments, a distance was given between the treatments. The farms being tested were newly cultivated farms. The surface of the farm was furrowed and ridged. Care was taken in selecting the farm so that the humidity was similar in its different sections. After setting the right time for the hilling up and before starting the operation, soil sampling is required to determine the soil cone index and soil moisture. The physical properties of this study include Mean Weight Diameter (MWD), bulk density, soil surface uniformity, soil water permeability, and furrow depth (stack height). Analysis of variance and Duncan test were used to compare the treatments using SAS 9.4 software.Results and Discussion The results showed that there was a significant difference between soil Mean Weight Diameter, bulk density, soil surface uniformity, and soil water permeability in soil texture treatments, type of hilling up machine, and forward speed. Furrow depth index (stack height) was significantly different in treatments of type of machine and forward speed but not in soil texture treatments. The comparison of means showed that the whole loam texture treatment had 6-shanks + 10-shanks at a speed of 7 km h-1 with the smallest mean weight diameter (16.06 mm). The use of 6-shanks subsoil + 10-shanks subsoil in hilling up in whole texture and speed of 5 km h-1 significantly reduced soil bulk density. The lowest coefficient of variation of soil surface uniformity was obtained with 8-shanks subsoil + hilling up device No. 1 in clay loam texture and 7 km h-1 forward speed. The highest rate of water permeability in the soil was obtained after the hilling up operation with 6-shanks subsoil + 10-shanks subsoil in a total texture of 2.32 cm h-1. Furrow depth index (stack height) was also within the acceptable range (10-15 cm) in all treatments. But in addition to height, the appearance of the ridges is also important. In the treatment of 6-shanks + 10-shanks in plant stacking and embankment operations, sometimes in fields, there are parts where this operation is not done well and the machine is not capable enough and is in the middle of the created ridges. Harvesting operations do not cause proper reed flooring. Therefore, to solve this problem, it is necessary to perform the hilling up operation at the appropriate speed and humidity so that the soil is well placed on the rows of reeds and the proper appearance of the ridge is maintained.Conclusion In this study, three different types of devices have been evaluated in two soil textures and three different forward speeds as a step towards choosing the best type of machine and optimal speed of hilling up operations in sugarcane cultivation. The physical properties of the soil, including the soil Mean Weight Diameter, bulk density, soil surface uniformity, soil water permeability, and the size of the furrow depth (ridge height) were measured, and the best treatments were identified. Considering the importance of hilling up operations in sugarcane cultivation and to complete the results of this experiment, the following items that could not be studied in this study are suggested. The effect of using different methods on hilling up should be investigated on the yield of sugarcane. The effect of using different devices on hilling up in terms of tensile strength, work efficiency, and time required to do the work, fuel consumption, cost of timely work, and maintenance costs in operations on sugarcane hilling up should be investigated.
N. Monjezi
Abstract
Every organization needs an evaluation system in order to be aware of the level of performance and desirability of its units. It is more important for agricultural companies, including agro-industries. In this study, 20 sugarcane harvesting units were selected. After modeling based on input-oriented ...
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Every organization needs an evaluation system in order to be aware of the level of performance and desirability of its units. It is more important for agricultural companies, including agro-industries. In this study, 20 sugarcane harvesting units were selected. After modeling based on input-oriented CCR and BCC models, efficiency values for sugarcane harvesting units were calculated and the CART decision tree was used to extract rules to predict the efficiency of these units. The results of a study of 20 sugarcane harvesting units in the CCR model showed that 6 units had an efficient score and 14 units had an inefficient score, and their technical efficiency score was in the range of 0.73-0.95. The results of the BCC model study also showed that out of a total of 20 sugarcane harvesting units, 8 units had efficient scores. As can be seen, in the BCC model, more units are introduced as efficient units and there is less dispersion between inefficient units. Also, the distribution of efficient units in the BCC model is less than the CCR model. The average technical efficiency, pure technical efficiency, and scale efficiency were 93%, 88%, and 93%, respectively. Also, the accuracy of the decision tree model for technical efficiency and pure technical efficiency was 86% and 93%, respectively.
N. Monjezi
Abstract
Introduction One of the most important risk factors for developing musculoskeletal disorders is the inappropriate work of postures and since maintaining the health of the workforce promotes community development. Therefore, the workforce should be in an appropriate working environment without any harmful ...
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Introduction One of the most important risk factors for developing musculoskeletal disorders is the inappropriate work of postures and since maintaining the health of the workforce promotes community development. Therefore, the workforce should be in an appropriate working environment without any harmful factors to ensure its physical and mental well-being. Among the various problem found in agriculture mentioned above, a problem commonly reported in agricultural workers in particular farmers in a rural area is work-musculoskeletal symptoms (MSS) in a different part of the body. In the process of producing sugarcane, a significant part of the stage of cuttings, planting, and harvesting is done manually. A low level of knowledge about the correct condition of the body during work is one of the problems of farmers. Therefore, body status assessment methods are considered as the basis and the basis for assessing the risk of musculoskeletal disorders associated with work. We decided to do a posture assessment in these persons while working to determine the posture hazard level. The purpose of this study was to identify inappropriate working conditions in sugarcane fields at the cutting, planting and harvesting manual stages. Materials and Methods This study was a descriptive-analytical approach performed on 300 workers by using the REBA method. The Rapid Entire Body Assessment (REBA) method was used to determine the risk of MSDs. The REBA posture-targeting method is probably the most well-known method for rapid assessment of risks. The REBA method is ideal for rapid assessment of standing work. In order to collect the required data, each part of the body was scored and work frequency, load/force, coupling were considered to achieve a REBA score. The REBA provides a quantitative value to the evaluation that indicates the level of severity of each task. The calculation was made by using the REBA Employee Assessment Worksheet that has been divided into two groups; Group A (Trunk, Neck, and Legs) postures and Group B (Upper Arms, Lower Arms, and Wrists) postures for left and right. A summary of the procedure for the REBA score and the degree of risk is found in the REBA decision table. The risk score of this approach should be in the range of one of fifteen, where the higher scores signify greater levels of apparent risk. An analysis of scores represents the work’s risks and indicates possible actions to avoid or minimize the risks. The method of work was to photograph workers in sugar cane fields of Khuzestan province during the activity and analysis of photographs using modeling the body of workers with REBA 6 software and analyzing different situations using REBA method. Results and Discussion By cutting stage, a total of 6.6% of evaluating postures by REBA technique obtained scores of 8-10 (very high risk level) and 93.4% had scores of 11-15 (very high risk level) that correspond to the action level 3 and 4, respectively. In planting stage, a total of 12.10% of evaluating postures by REBA technique obtained scores of 8-10 (very high risk level) and 87.90% had scores of 11-15 (very high risk level) that correspond to the action level 3 and 4, respectively. In the harvesting stage, a total of 15.30% of evaluating postures by REBA technique obtained scores of 8-10 (very high-risk level) and 84.70% had scores of 11-15 (very high risk level) that correspond to the action level 3 and 4, respectively. The results showed that according to the REBA method, in preparation cuttings, planting and harvesting sugarcane manually, respectively, 93.48, 90.87 and 84.77% of the workers' posture are in the most critical group that should be avoided. Risk level should be reduced, especially in sugarcane fields. More training and instructions are needed to have a good working position in sugarcane procedures. Improvement of working posture need to be done by improving all aspects that related to physical workload such as by reducing the workload on the back, neck, shoulder/arm, and also hand/wrist. Conclusion A high percentage of musculoskeletal disorders in workplaces occur due to awkward posture and non-ergonomic design of the workstations for lifting and carrying of materials. To avoid these injuries, jobs should be designed in a way that ergonomics risk factors are controlled properly. The results of this study can be used to develop WMSDs preventive strategies in the workplace and improve workers’ health. Educational intervention can be an appropriate way to improve the physical condition and ultimately reduce musculoskeletal disorders. Some proposed corrective actions include: standardizing the design and construction of the work tool used by the user's anthropometric study (especially sharp sickle), establishing suitable work-resting cycles and conducting periodic examinations for the early detection of musculoskeletal disorders. Of course, given the high percentage of damage to sugarcane production during manual operation, it's definitely a move to mechanized operations in sugarcane crops.
Modeling
H. Zaki Dizaji; H. Bahrami; N. Monjezi; M. J. Sheikhdavoodi
Abstract
Introduction The sugar industry usually gathers huge amounts of information during normal production operations, which is rarely used to study the relative importance of both management and environment on sugarcane yield performance. Yield prediction is a very significant problem of agricultural organizations. ...
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Introduction The sugar industry usually gathers huge amounts of information during normal production operations, which is rarely used to study the relative importance of both management and environment on sugarcane yield performance. Yield prediction is a very significant problem of agricultural organizations. Each agronomist wants to know how much yield to expect as soon as possible. The aim of this study was to determine the performance of C5.0 and QUEST algorithms to predict the yield of sugarcane production in Amir-Kabir agro-industry Company of Khuzestan province, Iran. However, the working method described in this paper is applicable to other geographical areas and other kinds of crops. Materials and Methods The data for the study were collected from Amir-Kabir agro-industry Company. The data is obtained from 2012 to 2016 years. The study area is located in Khuzestan Province which is a major agricultural region in Iran. The geographical location of the study area is between latitudes 31° 15′ to 31° 40′ north and longitudes 48° 12′ to 48° 30′ east. It covers an area of about 12000 ha. The average elevation of the study area is 8m above sea level. Mean annual rainfall within the study area is 147.1mm, the mean annual temperature is approximately 25°C and the mean soil temperature at 50cm depth is 21.2°C. The used data were obtained from a survey with 15 variables carried out on 1201 sugarcane farms. Variables used in the study of data mining can be divided into two categories: target variable and predictor variables. The variable of yield was used as the target variable (dependent) and other variables as predictor variables (independent). In two models, the input data included crop cultivar, month of harvest, chemical fertilizer (Nitrogen), chemical fertilizer (Phosphate), age (plant or ratoon), times irrigation, ratio of surface spraying, soil texture, soil electrical conductivity (EC), water consumption per hectare, drain, farm management, crop duration, area, and yield-category. The study was included in 1201 farms. The necessary data were collected and pre-processing was performed. We propose to analyze different decision tree methods (C5.0 and QUEST). Results and Discussion First, decision tree methods were analyzed for variables. Then, according to C5.0 method (error rate 0.2319 for the training set and 0.3306 for test set) performed slightly better than another method in predicting yield. Crop cultivar is found that an important variable for the yield prediction. 24 rules were found in this study, C4.5 showed a better degree of separation. The measured prediction rate of C5.0 was correct: 76.81% and wrong: 23.19% in the training data, and correct: 66.94% and wrong: 33.06% in the test data. The prediction rate of QUEST was correct: 68.25% and wrong: 31.75% in the training data, and correct: 70.83% and wrong: 29.17% in the test data. Using the training data comparison between the model types showed that the C5.0 model produces a more accurate prediction model and was, therefore, the model to use. Using the testing data in comparison with the model types showed that the QUEST model produced a more accurate prediction model. The results of our assessment showed that C5.0 and QUEST algorithms were capable to produce rules for sugarcane yield. Therefore, our proposed methods as an expert and intelligent system had an impressive impact on sugarcane yield prediction. Conclusion In today's conditions, agricultural enterprises are capable of generating and collect large amounts of data. Growth of data size requires an automated method to extract necessary data. By applying data mining technique it is possible to extract useful knowledge and trends. Knowledge gained in this manner may be applied to increase work efficiency and improve decision making quality. Data mining techniques are directed towards finding those schemes of work in data which are valuable and interesting for crop management. In this research, decision tree algorithms (C5.0 and QUEST) were used. This classification algorithm was selected because it has the potential to yield good results in prediction and classification applications. This study was performed to present a model-based data mining to predict sugarcane yield in 2012-2016. The 24 classification rules generated from the C5.0 decision tree algorithm have great practical value in agricultural applications. The results showed the QUEST and C5.0 decision tree algorithms produced the best prediction accuracy. Sensitivity analysis results indicated that crop cultivar was the most important variables. It was observed that efficient technique can be developed and analyzed using the appropriate data, which was collected from Khuzestan province to solve complex agricultural problems using data mining techniques (decision tree). The decision tree has been found useful in classification and prediction modeling due to the fact that it can capability to accurately discover hidden relationships between variables, it is capable of removing insignificant attributes within a dataset.
H. Zaki Dizaji; N. Monjezi
Abstract
Introduction Mechanized harvesting of sugarcane by harvesters and the lack of proper management of harvesting, increase the cost of production and eventually become unprofitable. In the case of sugarcane harvester, because the systems are used to be repaired, increasing in system consumption will reduce ...
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Introduction Mechanized harvesting of sugarcane by harvesters and the lack of proper management of harvesting, increase the cost of production and eventually become unprofitable. In the case of sugarcane harvester, because the systems are used to be repaired, increasing in system consumption will reduce machine reliability (Failure rate will increase). So, timely annual overhaul has effective role in enhancing the reliability of sugarcane harvesting machines. Because of time importance indicator for reducing timeliness cost and work breakdown, project scheduling techniques and work study especially network models are used. In this study, because of the ability of GERT networks capabilities in planning and scheduling, GERT networks were used and overhaul scheduling of sugarcane harvester in Amir Kabir Agro-Industry of Khuzestan province, Iran as a case study was analyzed. Materials and Methods The study was carried out in Khuzestan province of Iran in 2016. Data were collected from variety sources such as opinions and comments of experts and reports and statistics of Sugarcane Agro-Industry. All activity times are given in hour. At first, the project activities are determined and the work breakdown structure was drawn. Finally, GERT network was plotted and analyzed. GERT is a procedure, which combines the disciplines of the flow graph theory, Moment Generating Function (MGF) and Project Evaluation and Review Technique (PERT) for analyzing stochastic networks having logical nodes and directed branches. Each branch has a probability that the activity associated with it will be performed. Therefore, GERT provides a visual picture of the system by means of the corresponding graph and makes it possible to analyze the given system in a less inductive manner. The following steps are employed, when applying GERT: 1. Convert a qualitative description of a system or problem to a model in a stochastic network form. 2. Collect the necessary data to describe the transmittances of the network. 3. Apply Mason’s rule to determine the equivalent function or functions of the network. 4. Convert the equivalent function into the following two performance measures of the network: (a) The probability that a specific node is realized. (b) The moment generating function of the time associated with a node, if it is realized. 5. Make inferences concerning the system under study from the information obtained in the Step 4. Results and Discussion In this paper the GERT method has been presented for operations modeling in overhaul sugarcane harvester. Correct scheduling of the agricultural mechanization project (overhaul) is the required condition for the project success therefore the GERT network of overhaul sugarcane harvester was plotted. A network is a powerful tool for scheduling and simulating a project. The project network is defined as a set of activities performed according to the precedence constraint of the activities. The advantage of the GERT network in the present context is two-fold. Firstly, this procedure gives the visual picture of the inspection system and secondly, it enables a thorough characterization of overhaul sugarcane harvester. In this project, after defining activities, we estimate for each activity as a time. Then we solved the network with the GERT method. According to the materials and methods, the probability and mean of the completion time of overhaul sugarcane harvester obtained. The worth of different parts of the network is calculated. For each node, to conclude about the probability and mean can use the above procedure and predict various events during operations. So with due attention to certain events that are occurring in the tracks of operation, good decisions can be adopted. Time completion of overhaul scheduling of the sugarcane harvester is equal to 1164.64 man-hours. Results showed that the network model is increasingly powerful tool to help project manager who could able to make optimum decision. Conclusion Optimized overhaul planning is a fundamental activity in business profitability because it can increase the returns from an operation with low additional costs. In this paper, a specific scheduling model for an overhaul operations scheduling is developed along with an optimal solution GERT method. The purpose of this paper is studying the application of project scheduling in agriculture, for overhaul scheduling of sugarcane harvester using GERT method in Khuzestan province of Iran. Time completion of overhaul scheduling of sugarcane harvester is equal to 1164.64 man-hours.
Agricultural waste management
H. Zaki Dizaji; N. Monjezi
Abstract
Introduction No use of advanced mechanization and weakness in post harvesting technology are the main reasons of agricultural losses. Some of these wastes (agricultural losses) are related to crop growing conditions in field and the remaining to processing of sugar in mill. The most useful priority setting ...
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Introduction No use of advanced mechanization and weakness in post harvesting technology are the main reasons of agricultural losses. Some of these wastes (agricultural losses) are related to crop growing conditions in field and the remaining to processing of sugar in mill. The most useful priority setting methods for agricultural projects are the Analytic Hierarchy Process (AHP). So, this study presents an introduction of application manner of the AHP as a mostly common method of setting agricultural projects priorities. The purpose of this work is studying the sugarcane loss during production process using AHP in Khuzestan province. Materials and Methods The resources of sugarcane waste have been defined based on expert’s opinions. A questionnaire and personal interviews have formed the basis of this research. The study was applied to a panel of qualified informants made up of thirty-two experts. Those interviewed were distributed in Sugarcane Development and By-products Company in 2015-2016. Then, with using the analytical hierarchy process, a questionnaire was designed for defining the weight and importance of parameters effecting on sugarcane waste. For this method of evaluation, three main criteria considered, were yield criteria, cost criteria and income criteria. Criteria and prioritizing of them was done by questionnaire and interview with sophisticated experts. This technique determined and ranked the importance of sugarcane waste resources based on attributing relative weights to factors with respect to comments provided in the questionnaires. Analytical Hierarchy Process was done by using of software (Expert choice) and the inconsistency rate on expert judgments was investigated. Results and Discussion How to use agricultural implements and machinery during planting and harvesting of sugarcane, can increase or decrease the volume of waste. In planting period, the losses mainly consists of loss of setts during cutting them by machine, injury the setts by biological and physical agents, loss of growth in sett field, unsuitable sett covering and replanting the gaps. During cultivation period the losses include late in field harvesting and so late in regrows the cane, unsuitable ratooning and use of cultivator, varying the size of the furrows and ricks in around the field and destroyed the stubbles during rationing. In harvesting the losses easily seen and mainly associated by efficiency of harvester machines. Billets loss of the fleet in the transmission roads toward mill and late in harvest the burnet cane and then transport to mill are main sources of quantities and qualities of losses. The Expert Choice software performed well in conjunction with the panel of experts for choosing the criteria and assigning weights under the AHP methodology. According to the results, effective parameters on sugarcane waste consist of caused by harvesting, transportation, industry, planting, preserve operations, ratooning and land preparation. Weight of effective criteria (yield, cost and income) on losses of sugarcane obtained from paired comparison in the experts’ view which has been calculated with Expert choice software. The result of this survey by AHP techniques showed that yield criteria had the most and income criteria had the least importance for expert in sugarcane production. In this stage of research, alternatives of paired comparison relative to criteria was separately formed and information of questionnaire which relates to paired comparison of criteria was obtained. Between effective parameters on losses of sugarcane, harvesting with 0.243 weighted average was the most effective factor and transportation with 0.187 weighted average, industry with 0.179 weighted average, planting with 0.156 weighted average, preserve operations with 0.109 weighted average, ratooning with 0.071 weighted average, and land preparation with 0.055 weighted average was later, respectively (Inconsistence Rate =0.04). The results are examined by monitoring sensitivity analysis while changing the criteria priorities. Since different judgments are made on comparison of criteria, we use sensitivity analysis in order to provide stability and consistence of analysis. With increasing or decreasing of the criteria, we will conclude that ratio of other indices will not change. Conclusion This paper looks at AHP as a tool used in Sugarcane Agro-Industries to help in decision making. Results show that criteria studied in this research can help prioritizing of loss resources during sugarcane production process. According to the results, effective parameters on sugarcane waste consist of caused by harvesting, transportation, industry, planting, preserve operations, ratooning and land preparation.
N. Monjezi; M. J. Sheikhdavoodi; H. Zaki Dizaji; A. Marzban; M. Shomeili
Abstract
Introduction Planning and scheduling of farming mechanized operations is very important. If the operation is not performed on time, yield will be reduced. Also for sugarcane, any delay in crop planting and harvesting operations reduces the yield. The most useful priority setting method for agricultural ...
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Introduction Planning and scheduling of farming mechanized operations is very important. If the operation is not performed on time, yield will be reduced. Also for sugarcane, any delay in crop planting and harvesting operations reduces the yield. The most useful priority setting method for agricultural projects is the analytic hierarchy process (AHP). So, this article presents an introductry application manner of the Analytical Hierarchy Process (AHP) as a mostly common method of setting agricultural projects priorities. Analytic Hierarchy process (AHP) is a decision making algorithm developed by Dr. Saatyin 1980. It has many applications as documented in Decision Support System literature. Currently, this technique is widely used in complicated management decision makings which AHP was preferred from other established methodologies as it does not demand prior knowledge of the utility function; it is based on a hierarchy of criteria and attributes reflecting the understanding of the problem, and finally, because it allows relative and absolute comparisons, thus making this method a very robust tool. The purpose of this research is to identify and prioritize the effective parameters on lack of timeliness of operations of sugarcane production using AHP in Khuzestan province of Iran. Materials and Methods The effective parameters effecting on lack of timeliness of operations have been defined based on expert’s opinions. A questionnaire and personal interviews have formed the basis of this research. The study was applied to a panel of qualified informants made up of fourteen experts. Those interviewed were distributed in Sugarcane Development and By-products Company in 2013-2014. Then, by using the Analytical hierarchy process, a questionnaire was designed for defining the weight and importance of parameters affecting on lack of timeliness of operations. For this method of evaluation, three main criteria considered were yield criteria, cost criteria and income criteria. Criterions and prioritizing of them was done by questionnaire and interview with sophisticated experts. This technique determined and ranked the importance of criteria affecting on lack of timeliness of operations based on attributing relative weights to factors with respect to comments provided in the questionnaires. By using of software (Expert choice) Analytical Hierarchy Process was done and the inconsistency rate on expert judgments was investigated. Expert Choice software (Expert Choice 1999) was applied to examine the structure of the proposed model and achieve synthesis/ graphical results considering inconsistency ratios. Results and Discussion The Expert Choice software performed well in conjunction with the panel of experts for choosing the criteria and assigning weights under the AHP methodology. According to results, effective parameters on lack of timeliness of operations of sugarcane production consist of delays caused by management, delays caused by human, delays caused by machine and delays caused by procedure (the production process).Weight of criteria effective factors (yield, cost and income) on lack of timeliness of operations obtained from paired comparison in the experts’ view which has been calculated with Expert choice software. The result of this survey by AHP techniques showed that cost criteria had the most and income criteria had the least importance for expert in sugarcane production. In this stage of research, alternatives paired comparison relative to criteria was separately formed and information of questionnaire which relates to paired comparison of criteria was obtained. Between effective parameters on lack of timeliness of operations, machine factors to 0.366 weighted average was the most effective factor and production process to 0.298 weighted average, management factors to 0.177 weighted average and human factors to 0.160 weighted average was later respectively (Inconsistence Rate =0.03). The results are examined by monitoring sensitivity analysis while changing the criteria priorities. Since different judgments are made on comparison of criteria, we use sensitivity analysis in order to provide stability and consistence of analysis. With increase or decrease of the criteria, we will conclude that ratio of other indices will not change. Conclusion The analytic hierarchy process, as developed by Saaty, has been successfully applied in recent research to cases of agricultural project. This paper looks at AHP as a tool used in Sugarcane Agro-Industries to help in decision making. Results showed that criteria studied in this research can help prioritizing the effective parameters on lack of timeliness of operations of sugarcane production. Cost criteria are the main criteria effective on lack of timeliness operations of sugarcane production. The most important factor is machine factor.
