Repetitive tasks carried out by packaging workers of fertilizer producer company. These task led to some complains of pain and fatigue on upper body part of the workers based on Nordic Body Maps (NBM) questionnaire. This is because the workers work continuously for eight hours per shift and no recovery period. This study aims to determine risk level of musculoskeletal disorders and break time calculation. In this study, using Occupational Repetitive Actions (OCRA) index to reduce the risk level. The samples according to expert judgement criteria are three workers (packer clamper, packer tailor and loader). The improvement in this study is designing work methods with break time calculation. This improvement shows the risk reduction on the left hand of the packer clamper from 4,2 to 3,4 and the right hand from 9,9 to 8,2. Risk reduction on the left hand of the packer tailor from 3,44 to 2,2 and the right hand from 5,7 to 2,26 while the risk level on the left hand of loader from 1,4 to 0,87 and in the right hand from 2,17 to 1,18.
Indonesian Basic Health Research in 2018 showed the prevalence of pneumonia, pulmonary tuberculosis (TB) and lung cancer in Indonesia 4.0% 0.4% and 0.18%, respectively. However, the number of lung specialists is small. According to the Indonesian Lung Specialist Association webpage, the number of doctors joined in the association up to 2008 were 452. This amount is very less when compared with existing lung disease cases. Thus, the handling of lung disease will be too late. The use of ANFIS for early detection of lung disease is growing. However, the systems designed are need preprocessing data to be executed and still applied for one type of disease. This paper will design a desktop application based on ANFIS expert system to detect lung disease early, i.e. for pneumonia, pulmonary TB and lung cancer. The system will work based on simple symptoms expressed by the patient. Subtractive clustering is used for clustering process. The results of the training showed that the models were able to give better performance compared to the model built using conventional clustering methods. The test results show that those three models have comparable performance compared to their counterpart. Software validation shows that the it gives 94.00% succeed for training data and up to 100% for testing data. This application is not intended to replace the role of a doctor, but to help diagnose the patient's condition earlier.
The accident record from a steel fabrication company in [2014][2015][2016][2017] shows that the most frequent accidents take place in overhead crane operation with a percentage of 42%. The overhead crane operation has the greatest potential of accidents with human error as the main cause. The purpose of this study is to determine what factors affect the occurrence of errors, to know how much HEPs, and to determine recommendations. The method used in this research is Success Likelihood Index Method (SLIM) with qualitative development using Decision Making Trial and Evaluation Laboratory (DEMATEL) which aims to establish the relationship among PSFs to be an easily comprehensible structured model by considering expert judgements and to solve dependency in a set of criteria. Analytic Network Process (ANP) is used to overcome the inconsistency of expert judgements and difficulty in selection and weighting. The calculation and analysis reveal that the highest Human Error Probability (HEP) value is shown by the task to handling or lifting with the value 0.000485. Impact assessment using the HEP value to determine probability and consequence is performed by expert judgements. Improvement recommendations are prioritized for high rating error tasks using Error Reduction Analysis.
The results of Basic Health Research in 2018 showed the prevalence of pneumonia and pulmonary tuberculosis (TB) in Indonesia 4.0 percent and 0.4 percent, respectively. However, with a minimal number of lung specialists, the handling of lung disease will be too late. There are only 600-700 lung specialists in Indonesia. This amount is very less when compared with existing lung disease cases. The use of ANFIS for early detection of lung disease is growing. However, the system designed is still used for one type of disease. This research will design an expert system based on ANFIS to detect lung disease early, i.e. for pneumonia and pulmonary TB. Subtractive clustering is used for clustering process. The results of the training showed that both models were able to give better performance compared to the model built using conventional clustering methods. The test results show that both models have comparable performance compared to their counterpart.
Argon Purification Unit is a processing unit to purify the crude argon using hydrogen gas through an automatic machinery process. Based on the hazardous material and its automatic machinery process, the argon purification unit needs to be assessed for risk control consideration and business performance. This research proposed risk assessment of argon purification unit based on the failure modes using Failure Modes, Effects and Criticality Analysis (FMECA) with Fuzzy Analytical Hierarchy Process (Fuzzy-AHP) approach to minimize the risks and losses. In this research, FMECA is used to identify the potential failure modes, failure mechanism (causes), potential failure effects for each unit component and evaluate the risk by determining risk priority number (RPN). The RPN is the product of severity, occurrence, and detection variables. Then, Fuzzy-AHP is used to determine the weight of each variable based on its hierarchy. The fuzzy-AHP approach aims to increase validity and decrease expert judgment subjectivity in the risk assessment process for each failure mode by considering variables' weight. The result of RPN is gained by multiplying each failure mode's variables by considering the importance of variables. This research results weight of severity is 0.43, which is the highest of all variables. The highest RPN is 8.76, shown by the leaked joint of the argon compressor. This research indicates that the application of the fuzzy-AHP approach in FMECA can identify and evaluate the potential risk of the Argon Purification Unit validly and objectively, which provides the different weight of RPN variables.
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