Vocational High School (SMK), every practice always requires supporting materials. When the demand for these practice materials coincides between departments, so schools have difficulty in fulfilling them. The purpose of processing data on borrowing practice materials is to optimally meet the practical needs of the department. The data that is processed in this study is the data on demand for practice materials, data on practice needs and data on supply of practice materials. The data is processed using the Monte Carlo method with testing using PHP programming. The results of this study are predictions of the optimal practice material needs in the TKJ department and the materials that are needed and the amount of practice materials needed. 97% accurate. So that this research is very helpful in predicting the material needs of practice, this research is very helpful for the school in improfing services for student praticum.
{"title":"Prediction of Material Requirements For Vocational Practices Using The Monte Carlo Method (Case Study at SMK Dwi Sejahtera Pekanbaru)","authors":"Suandi Daulay, R. Rahmi","doi":"10.37385/jaets.v4i1.936","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.936","url":null,"abstract":"Vocational High School (SMK), every practice always requires supporting materials. When the demand for these practice materials coincides between departments, so schools have difficulty in fulfilling them. The purpose of processing data on borrowing practice materials is to optimally meet the practical needs of the department. The data that is processed in this study is the data on demand for practice materials, data on practice needs and data on supply of practice materials. The data is processed using the Monte Carlo method with testing using PHP programming. The results of this study are predictions of the optimal practice material needs in the TKJ department and the materials that are needed and the amount of practice materials needed. 97% accurate. So that this research is very helpful in predicting the material needs of practice, this research is very helpful for the school in improfing services for student praticum.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48993462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Areca nut (Areca catechu) is a kind of palm plant that grows in Asia and Africa, the eastern part of the Pacific and in Indonesia itself, areca nut can also be found on the islands of Java, Sumatra and Kalimantan. At the stage of classifying the maturity of the betel nut so far, it is still using the manual method which at that stage has subjective weaknesses. Based on these problems, researchers will create a system that is able to classify the level of maturity of areca nut using HSV feature extraction with assistance at the classification stage using the KNN method. In this study, 842 datasets were used which were divided into 3 types of classes, namely ripe, unripe and old fruit. The dataset was divided into 683 training data and 159 test data. In the next stage, the data is tested using the K-Nearest Neighbor method by calculating the closest distance using k = 1. From the results of the calculation of the closest distance k1 produces an accuracy rate of 87.42%. Kata kunci— Matlab, Areca Ripeness, KNN, HSV.
{"title":"Classification of Maturity Levels in Areca Fruit Based on HSV Image Using the KNN Method","authors":"Frencis Matheos Sarimole, Anita Rosiana","doi":"10.37385/jaets.v4i1.951","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.951","url":null,"abstract":"Areca nut (Areca catechu) is a kind of palm plant that grows in Asia and Africa, the eastern part of the Pacific and in Indonesia itself, areca nut can also be found on the islands of Java, Sumatra and Kalimantan. At the stage of classifying the maturity of the betel nut so far, it is still using the manual method which at that stage has subjective weaknesses. Based on these problems, researchers will create a system that is able to classify the level of maturity of areca nut using HSV feature extraction with assistance at the classification stage using the KNN method. In this study, 842 datasets were used which were divided into 3 types of classes, namely ripe, unripe and old fruit. The dataset was divided into 683 training data and 159 test data. In the next stage, the data is tested using the K-Nearest Neighbor method by calculating the closest distance using k = 1. From the results of the calculation of the closest distance k1 produces an accuracy rate of 87.42%.\u0000Kata kunci— Matlab, Areca Ripeness, KNN, HSV.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45784177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The S&R Baby Store store is a Small and Medium Enterprise (SME) that is engaged in baby equipment, but there is a lot of competition between small and medium enterprises (SMEs) who are engaged in the same field, so that many products sold are of course not all sold out, some are lacking. in demand. Therefore the S&R Baby Store store needs a good sales strategy in order to increase sales profit. This study discusses the application of data mining, using the K-Means Clustering algorithm with the CRISP-DM method. Implementation using RapidMiner 9.10 which is done by entering sales transaction data with a total of 4 attributes and forming 4 clusters consisting of very in demand, in demand, moderate in demand and less in demand. the second cluster with 944 products, the third cluster with 2 products, and the fourth cluster with 43 products. The results of the cluster above are the products sold are the best-selling product categories, then the results of the cluster are validated using the Davies-Bouldin Index with a DBI value generated from clustering of 0.560.
{"title":"Implementation of Data Mining Using K-Means Clustering Method to Determine Sales Strategy In S&R Baby Store","authors":"T. Wahyudi, Titi Silfia","doi":"10.37385/jaets.v4i1.913","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.913","url":null,"abstract":"The S&R Baby Store store is a Small and Medium Enterprise (SME) that is engaged in baby equipment, but there is a lot of competition between small and medium enterprises (SMEs) who are engaged in the same field, so that many products sold are of course not all sold out, some are lacking. in demand. Therefore the S&R Baby Store store needs a good sales strategy in order to increase sales profit. This study discusses the application of data mining, using the K-Means Clustering algorithm with the CRISP-DM method. Implementation using RapidMiner 9.10 which is done by entering sales transaction data with a total of 4 attributes and forming 4 clusters consisting of very in demand, in demand, moderate in demand and less in demand. the second cluster with 944 products, the third cluster with 2 products, and the fourth cluster with 43 products. The results of the cluster above are the products sold are the best-selling product categories, then the results of the cluster are validated using the Davies-Bouldin Index with a DBI value generated from clustering of 0.560.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45981225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the current era of modernization, online shopping has become a habit of the people, and is closely related to freight forwarding services in charge of delivering online shopping items from the seller to the buyer. So that buyers need a fast and safe delivery service to ensure the goods sent on time to their destination. Customer satisfaction is one of the most important factors in the shipping business. However, there are several obstacles that occur in the field that cause delays in the delivery of goods. Therefore, one solution that can be used to overcome this problem is to use data mining technology to predict delivery times. Using 1,000 datasets consisting of 4 Attributes, data processing will be carried out with prediction techniques using the Linear Regression algorithm. By utilizing data when the goods are taken, when the goods are on the way, until they reach the buyer, they can produce forecasts or predictions and produce several analyzes so that in the future there will be no delivery delays. Based on the RMSE (Root Mean Square Error) value which serves to generate the level value the error of the prediction results using this method and in an RMSE value of 0.370 %. It can be concluded that using the Linear Regression algorithm is proven to be accurate in predicting delivery times.
{"title":"Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm","authors":"T. Wahyudi, Dava Septya Arroufu","doi":"10.37385/jaets.v4i1.918","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.918","url":null,"abstract":"In the current era of modernization, online shopping has become a habit of the people, and is closely related to freight forwarding services in charge of delivering online shopping items from the seller to the buyer. So that buyers need a fast and safe delivery service to ensure the goods sent on time to their destination. Customer satisfaction is one of the most important factors in the shipping business. However, there are several obstacles that occur in the field that cause delays in the delivery of goods. Therefore, one solution that can be used to overcome this problem is to use data mining technology to predict delivery times. Using 1,000 datasets consisting of 4 Attributes, data processing will be carried out with prediction techniques using the Linear Regression algorithm. By utilizing data when the goods are taken, when the goods are on the way, until they reach the buyer, they can produce forecasts or predictions and produce several analyzes so that in the future there will be no delivery delays. Based on the RMSE (Root Mean Square Error) value which serves to generate the level value the error of the prediction results using this method and in an RMSE value of 0.370 %. It can be concluded that using the Linear Regression algorithm is proven to be accurate in predicting delivery times.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43856817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of technology in Indonesia is currently increasingly advanced in people's lives and cannot be avoided. The use of Artificial Intelligence in helping humans in dealing with problems is growing. Humans can take advantage of computer/smartphone media in today's technological era. One of its uses is Optical Character Recognition. This research is motivated by the problem where the running system requires development in terms of technology to detect characters in the quote text image, because the previous system still performs manual input. Optical Character Recognition has been widely used to extract characters contained in digital image media. The ability of OCR methods and techniques is very dependent on the normalization process as an initial process before entering into the next stages such as segmentation and identification. The image normalization process aims to obtain a better input image so that the segmentation and identification process can produce optimal accuracy. To get maximum results, it takes several pre-processing stages on the image to be used. To achieve this, it is necessary to perform Optical Character Recognition which can be done using Tesseract-OCR. The OCR program that was created was successfully used to scan or scan a quote text image if the document was lost or damaged, and it could save time for creating, processing and typing documents.
{"title":"Implementation of OCR (Optical Character Recognition) Using Tesseract in Detecting Character in Quotes Text Images","authors":"Ikha Novie Tri Lestari, Dadang Iskandar Mulyana","doi":"10.37385/jaets.v4i1.905","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.905","url":null,"abstract":"The development of technology in Indonesia is currently increasingly advanced in people's lives and cannot be avoided. The use of Artificial Intelligence in helping humans in dealing with problems is growing. Humans can take advantage of computer/smartphone media in today's technological era. One of its uses is Optical Character Recognition. This research is motivated by the problem where the running system requires development in terms of technology to detect characters in the quote text image, because the previous system still performs manual input. Optical Character Recognition has been widely used to extract characters contained in digital image media. The ability of OCR methods and techniques is very dependent on the normalization process as an initial process before entering into the next stages such as segmentation and identification. The image normalization process aims to obtain a better input image so that the segmentation and identification process can produce optimal accuracy. To get maximum results, it takes several pre-processing stages on the image to be used. To achieve this, it is necessary to perform Optical Character Recognition which can be done using Tesseract-OCR. The OCR program that was created was successfully used to scan or scan a quote text image if the document was lost or damaged, and it could save time for creating, processing and typing documents.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44646571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In administrative tasks, computers really need help so they can get the job done quickly and efficiently. Computers in the administration department are managed by a job that runs continuously for eight hours. Improper work posture and posture can cause fatigue and discomfort at work. One of the influencing factors is the working posture and body posture during these activities. This study aims to reduce the level of risk gained by performing Rapid Office Strain Assessments (ROSA) and Rapid Entire Body Assessments (REBA) for clerical staff in engineering departments. Posture analysis data processing using the ROSA (Rapid Office Strain Assessment) method found that five of her employees surveyed were at risk levels and needed to be corrected immediately. The Rapid Entire Body Assessment (REBA) method shows that five employees are currently at risk of urgent needs and requirements.
{"title":"Ergonomic Risk Analysis of Musculoskeletal Disorders (MSDs) Using ROSA and REBA Methods On Administrative Employees Faculty Of Science","authors":"Achmad Nuzul Amri, B. I. Putra","doi":"10.37385/jaets.v4i1.954","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.954","url":null,"abstract":"In administrative tasks, computers really need help so they can get the job done quickly and efficiently. Computers in the administration department are managed by a job that runs continuously for eight hours. Improper work posture and posture can cause fatigue and discomfort at work. One of the influencing factors is the working posture and body posture during these activities. This study aims to reduce the level of risk gained by performing Rapid Office Strain Assessments (ROSA) and Rapid Entire Body Assessments (REBA) for clerical staff in engineering departments. Posture analysis data processing using the ROSA (Rapid Office Strain Assessment) method found that five of her employees surveyed were at risk levels and needed to be corrected immediately. The Rapid Entire Body Assessment (REBA) method shows that five employees are currently at risk of urgent needs and requirements.\u0000 ","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49513718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
During the COVID-19 pandemic, all activities must be carried out at home as a result of the policy of restricting people's movement. As a result of this policy, all learning at the school and university levels must be carried out remotely or online. In particular, universities have not been able to carry out distance or online learning for all courses and all meetings. Of course, during the pandemic, it is a challenge for all universities to be able to carry out distance learning or online learning. So far, all universities in Indonesia are still implementing a blended learning system, or mixed learning between face-to-face meetings and online meetings. Usually 30% of face-to-face meetings and 70% online use e-learning. At University of Pembangunan Panca Budi, e-learning-based blended learning has been implemented and developed since 2012. Even though UNPAB's infrastructure and human resources are quite ready to carry out fully online learning during a pandemic, there are challenges that must be anticipated, namely student readiness. because most of the students are in the area. Keywords : (e-learning, distance learning, covid-19)
{"title":"Application of E-Learning for Online Learning During the Covid-19 Pandemic at University of Pembangunan Panca Budi","authors":"Heri Kurniawan","doi":"10.37385/jaets.v4i1.973","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.973","url":null,"abstract":"During the COVID-19 pandemic, all activities must be carried out at home as a result of the policy of restricting people's movement. As a result of this policy, all learning at the school and university levels must be carried out remotely or online. In particular, universities have not been able to carry out distance or online learning for all courses and all meetings. Of course, during the pandemic, it is a challenge for all universities to be able to carry out distance learning or online learning. So far, all universities in Indonesia are still implementing a blended learning system, or mixed learning between face-to-face meetings and online meetings. Usually 30% of face-to-face meetings and 70% online use e-learning. At University of Pembangunan Panca Budi, e-learning-based blended learning has been implemented and developed since 2012. Even though UNPAB's infrastructure and human resources are quite ready to carry out fully online learning during a pandemic, there are challenges that must be anticipated, namely student readiness. because most of the students are in the area. \u0000Keywords : (e-learning, distance learning, covid-19)","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44110504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guava bol is one of the fruits from Indonesia that is favored by many Indonesian people. The guava itself has a soft and dense flesh texture compared to water guava. The guava itself has a pink color if it is raw but if the guava is ripe it will be dark red. From a glance, when viewed from human vision, it is very easy to distinguish between them, but from most people it is still difficult to distinguish which guava is ripe, half-ripe and unripe guava because of differences in opinion from one human eye to another. Based on these problems, researchers have developed a system that is able to detect the maturity level of guava fruit by utilizing the Hue Saturation Value (HSV) feature extraction with K-Nearest Neighbor (KNN). The data used in this study were 465 datasets which were divided into 324 training data and 141 test data. The data had classes, namely ripe, half-cooked, and raw. The data is then classified using the K-Nearest Neighbor method by calculating the closest distance with a value of K = 3. From this study resulted in an accuracy of 97.16%.
{"title":"Classification Of Guarantee Fruit Murability Based on HSV Image With K-Nearest Neighbor","authors":"Frencis Matheos Sarimole, Muhammad Ilham Fadillah","doi":"10.37385/jaets.v4i1.929","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.929","url":null,"abstract":"Guava bol is one of the fruits from Indonesia that is favored by many Indonesian people. The guava itself has a soft and dense flesh texture compared to water guava. The guava itself has a pink color if it is raw but if the guava is ripe it will be dark red. From a glance, when viewed from human vision, it is very easy to distinguish between them, but from most people it is still difficult to distinguish which guava is ripe, half-ripe and unripe guava because of differences in opinion from one human eye to another. Based on these problems, researchers have developed a system that is able to detect the maturity level of guava fruit by utilizing the Hue Saturation Value (HSV) feature extraction with K-Nearest Neighbor (KNN). The data used in this study were 465 datasets which were divided into 324 training data and 141 test data. The data had classes, namely ripe, half-cooked, and raw. The data is then classified using the K-Nearest Neighbor method by calculating the closest distance with a value of K = 3. From this study resulted in an accuracy of 97.16%.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41565092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Disease is an abnormal condition in the body that causes body misalignment. There are various types of diseases that threaten humans, both parents and children. This disease can be caused by germs, bacteria, viruses, toxins, organ failure to function, and also by inherited/hereditary diseases. The difficulty of parents to find out the disease suffered by their children is one of the problems of parents today. So, we need a system to help with this predicament. The purpose of making this application is to provide information quickly and accurately in solving problems to help consult about diseases in toddlers aged 0-5 years. In addition, to find out ways to make programs that are expert systems using programming languages for artificial intelligence applications, namely PHP and Mysql, the certainty factor method is applied in web form. Using the certainty factor method is a decision-making strategy that starts from the section premise to conclusion. The result of system implementation is that the user chooses from the symptoms that already exist in the system based on the existing symptoms then processed, from the process the system provides information on diseases in children suffered by toddlers. From the results of testing this expert system has been able to diagnose diseases in children. After the diagnosis, the types of diseases and solutions will appear. Diagnosing disease in children by using this certainty factor is expected to make it easier to diagnose disease in children
{"title":"Expert System For Diagnosing Diseases in Toddlers Using The Certainty Factor Method","authors":"Bayu Saputra, Agnita Utami, Edriyansyah Edriyansyah, Yuda Irawan","doi":"10.37385/jaets.v4i1.916","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.916","url":null,"abstract":"Disease is an abnormal condition in the body that causes body misalignment. There are various types of diseases that threaten humans, both parents and children. This disease can be caused by germs, bacteria, viruses, toxins, organ failure to function, and also by inherited/hereditary diseases. The difficulty of parents to find out the disease suffered by their children is one of the problems of parents today. So, we need a system to help with this predicament. The purpose of making this application is to provide information quickly and accurately in solving problems to help consult about diseases in toddlers aged 0-5 years. In addition, to find out ways to make programs that are expert systems using programming languages for artificial intelligence applications, namely PHP and Mysql, the certainty factor method is applied in web form. Using the certainty factor method is a decision-making strategy that starts from the section premise to conclusion. The result of system implementation is that the user chooses from the symptoms that already exist in the system based on the existing symptoms then processed, from the process the system provides information on diseases in children suffered by toddlers. From the results of testing this expert system has been able to diagnose diseases in children. After the diagnosis, the types of diseases and solutions will appear. Diagnosing disease in children by using this certainty factor is expected to make it easier to diagnose disease in children","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43699818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Y. Andoh, L. Mensah, D. E. Dzebre, K. Amoabeng, C. Sekyere
This study investigates the failure of leaf springs used in the suspension system of heavy-duty vehicles in Ghana. Primary and secondary data were collected using both open and closed-ended questionnaires. Welders and fabricators of Sarkyoyo enterprise at the Suame Spare parts dealership area in Kumasi were engaged in the survey. The elastic strain and stress mathematical models were used to determine the stress points in a loaded leaf spring with the aid of ANSYS. The factors considered in the analysis were the leaf spring SAE design specification, the recommended Ghana Highway Authority load limit for heavy-duty vehicles, and the terrain. Analysis was done for both the standard and variable curvature leaf springs. The mode of failure was found to be fatigue loading. The causes of failure were determined to be loaded beyond the recommended 43 tons per wheel limit, bad roads, and reckless driving. It was also observed that loading causes the edges of the leaf spring to bend outwardly from the top, making the edges more prone to failure. Results further showed that the leaf spring with variable curvature recorded strain energy 2.5 times higher than the standards leaf spring.
{"title":"Investigating The Failure of Leaf Springs in Automobile Suspension on Ghana Road","authors":"P. Y. Andoh, L. Mensah, D. E. Dzebre, K. Amoabeng, C. Sekyere","doi":"10.37385/jaets.v4i1.508","DOIUrl":"https://doi.org/10.37385/jaets.v4i1.508","url":null,"abstract":"This study investigates the failure of leaf springs used in the suspension system of heavy-duty vehicles in Ghana. Primary and secondary data were collected using both open and closed-ended questionnaires. Welders and fabricators of Sarkyoyo enterprise at the Suame Spare parts dealership area in Kumasi were engaged in the survey. The elastic strain and stress mathematical models were used to determine the stress points in a loaded leaf spring with the aid of ANSYS. The factors considered in the analysis were the leaf spring SAE design specification, the recommended Ghana Highway Authority load limit for heavy-duty vehicles, and the terrain. Analysis was done for both the standard and variable curvature leaf springs. The mode of failure was found to be fatigue loading. The causes of failure were determined to be loaded beyond the recommended 43 tons per wheel limit, bad roads, and reckless driving. It was also observed that loading causes the edges of the leaf spring to bend outwardly from the top, making the edges more prone to failure. Results further showed that the leaf spring with variable curvature recorded strain energy 2.5 times higher than the standards leaf spring.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43958589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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