Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021259
Jiantao Li, Yue Wang, Huanan Cui, Dayu Zhang, Hongqi Zhang, Song Zhang, He Wang
There are extensive applications of accelerated degradation test in predicting the lifetime distribution of highly reliable products. The precision of the estimation can be improved by optimizing the experimental design of the accelerated degradation test. However, the complexity of the analytical method prevents the optimization algorithm from extensive application. In this work, a two-step method, based on Monte Carlo simulation and multi-objective genetic algorithm, is presented to optimize the accelerated degradation test, where the degradation rate follows a lognormal distribution. Then, a numerical example is provided to illustrate the method. The result of simulation and sensitivity analysis shows the optimized sample allocation ratio is closely related to the random measurement error.
{"title":"Optimal Design of-the Accelerated Degradation Experiment by Monte Carlo Method and Genetic Algorithm","authors":"Jiantao Li, Yue Wang, Huanan Cui, Dayu Zhang, Hongqi Zhang, Song Zhang, He Wang","doi":"10.1109/QR2MSE46217.2019.9021259","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021259","url":null,"abstract":"There are extensive applications of accelerated degradation test in predicting the lifetime distribution of highly reliable products. The precision of the estimation can be improved by optimizing the experimental design of the accelerated degradation test. However, the complexity of the analytical method prevents the optimization algorithm from extensive application. In this work, a two-step method, based on Monte Carlo simulation and multi-objective genetic algorithm, is presented to optimize the accelerated degradation test, where the degradation rate follows a lognormal distribution. Then, a numerical example is provided to illustrate the method. The result of simulation and sensitivity analysis shows the optimized sample allocation ratio is closely related to the random measurement error.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115203435","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021219
Zhi-gang Liu, Zhongxiang Ma, C. Pei, Gengjin Sui, Zhen Ji
Aiming at the Salix sawing process because of the unreasonable parameters caused by the cutting effect is poor, saw severe wear and due to the high-speed rotation of the safety problem of high energy consumption, the use of indoor cutting test bench simulation of field work in low speed circumstances. Based on Box-Behnken central combination test method, a multivariate mathematical regression model was established by taking the sawing speed, feed speed and the number of saw blade teeth as the influencing factors, and the sawing power and the sawing surface quality score as the objective function. The results show that the notable order of sawing power influence is sawing speed, feed speed and number of saw blade teeth; the notable order of sawing surface quality score is feed speed, sawing speed and number of saw blade teeth; the optimal combination of working parameters is sawing speed 850 r/min, feed speed 15 mm/s and number of teeth 100 T. Under this combination, sawing power and sawing surface quality score are 156.6W and 81 points. The reliability of the mathematical model is described by probability and data statistics. The relative error of reliability test is used as the evaluation index. The optimized parameter combination is basically accurate, and the established mathematical model meets the reliability requirements.
{"title":"Sawing Test Analysis and Reliability Verification of Salix","authors":"Zhi-gang Liu, Zhongxiang Ma, C. Pei, Gengjin Sui, Zhen Ji","doi":"10.1109/QR2MSE46217.2019.9021219","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021219","url":null,"abstract":"Aiming at the Salix sawing process because of the unreasonable parameters caused by the cutting effect is poor, saw severe wear and due to the high-speed rotation of the safety problem of high energy consumption, the use of indoor cutting test bench simulation of field work in low speed circumstances. Based on Box-Behnken central combination test method, a multivariate mathematical regression model was established by taking the sawing speed, feed speed and the number of saw blade teeth as the influencing factors, and the sawing power and the sawing surface quality score as the objective function. The results show that the notable order of sawing power influence is sawing speed, feed speed and number of saw blade teeth; the notable order of sawing surface quality score is feed speed, sawing speed and number of saw blade teeth; the optimal combination of working parameters is sawing speed 850 r/min, feed speed 15 mm/s and number of teeth 100 T. Under this combination, sawing power and sawing surface quality score are 156.6W and 81 points. The reliability of the mathematical model is described by probability and data statistics. The relative error of reliability test is used as the evaluation index. The optimized parameter combination is basically accurate, and the established mathematical model meets the reliability requirements.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123763454","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021262
Yu-hang Wang, Zhen Zhang, S. Si, Z. Cai
The aero turboshaft engine is mainly used in helicopters. As a power unit that drives the rotor to generate lift and propulsion, it has been rapidly developed in recent years. When the power of the turboshaft engine meets the conditions of use, the key section temperature often exceeds the threshold. As another important indicator of engine performance, it will affect the safety of the whole machine. This situation has become the primary problem for the current turboshaft engine manufacturers. In this paper, based on the collected data of a certain type of turboshaft engines, according to the manufacturer’s suggestions, three component size variables are extracted firstly. They have been confirmed to affect the engine power and the key section temperature. Then, based on Bayesian network, the engine performance models are established for power and the key section temperature respectively. Finally, after validity verification, the production optimization table and transition optimization matrix are proposed. From them, some effective suggestions are also given for the optimization of engine performance.
{"title":"Performance Optimization of Aero Turboshaft Engine Based on Bayesian Network","authors":"Yu-hang Wang, Zhen Zhang, S. Si, Z. Cai","doi":"10.1109/QR2MSE46217.2019.9021262","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021262","url":null,"abstract":"The aero turboshaft engine is mainly used in helicopters. As a power unit that drives the rotor to generate lift and propulsion, it has been rapidly developed in recent years. When the power of the turboshaft engine meets the conditions of use, the key section temperature often exceeds the threshold. As another important indicator of engine performance, it will affect the safety of the whole machine. This situation has become the primary problem for the current turboshaft engine manufacturers. In this paper, based on the collected data of a certain type of turboshaft engines, according to the manufacturer’s suggestions, three component size variables are extracted firstly. They have been confirmed to affect the engine power and the key section temperature. Then, based on Bayesian network, the engine performance models are established for power and the key section temperature respectively. Finally, after validity verification, the production optimization table and transition optimization matrix are proposed. From them, some effective suggestions are also given for the optimization of engine performance.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121305622","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021267
Peng Yang, Guishan Wang, Weiguo Wu, J. Qiu
The signatures and trend of degradation of 830 nm coaxial double heterojunction laser diode (DHLD) are studied by PSpice model simulation and accelerated degradation test. The relationships among temperature rise, degradation modes and signatures are revealed. Firstly, the mechanism of active region defect growth (ARDG) and cavity surface oxidation (CSO) are analyzed, and the causal relationship between temperature rise and CSO is revealed. Then, an equivalent circuit model of LD is constructed by PSpice software, and the simulation results show that the ARDG will cause the threshold current of P(I) curve to increase and the CSO will cause the slope to decrease. Finally, an accelerated degradation experimental platform is constructed, and the accelerated degradation tests are carried out on Sharp's 830 nm LD. The experimental results show that the temperature rise will cause the deterioration of CSO, but has no significant effect on ARDG.
{"title":"Degradation Study of 830nm Laser Diodes Based on PSpice Model and Accelerated Tests","authors":"Peng Yang, Guishan Wang, Weiguo Wu, J. Qiu","doi":"10.1109/QR2MSE46217.2019.9021267","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021267","url":null,"abstract":"The signatures and trend of degradation of 830 nm coaxial double heterojunction laser diode (DHLD) are studied by PSpice model simulation and accelerated degradation test. The relationships among temperature rise, degradation modes and signatures are revealed. Firstly, the mechanism of active region defect growth (ARDG) and cavity surface oxidation (CSO) are analyzed, and the causal relationship between temperature rise and CSO is revealed. Then, an equivalent circuit model of LD is constructed by PSpice software, and the simulation results show that the ARDG will cause the threshold current of P(I) curve to increase and the CSO will cause the slope to decrease. Finally, an accelerated degradation experimental platform is constructed, and the accelerated degradation tests are carried out on Sharp's 830 nm LD. The experimental results show that the temperature rise will cause the deterioration of CSO, but has no significant effect on ARDG.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124403863","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021220
Zhimao Ming, Mingjun Liang, Genxin Huang, Yudong Lu
The crosstalk simulation analysis model complete transmission path is established by HFSS. Based on this model, the near end crosstalk S13 and far end crosstalk S14 of each frequency are obtained. The influence of the maximum radial size of the BGA solder joint, the height of BGA solder joint, the size of the BGA welding disk on the near end crosstalk S13 and the far end crosstalk S14 of the complete transmission path are analyzed. It is found that the crosstalk between two complete transmission paths varies with signal frequency, the maximum radial size of BGA solder joint, solder height and diameter of solder pads.
{"title":"Crosstalk Simulation Analysis of Complete Transmission Path Based on HFSS","authors":"Zhimao Ming, Mingjun Liang, Genxin Huang, Yudong Lu","doi":"10.1109/QR2MSE46217.2019.9021220","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021220","url":null,"abstract":"The crosstalk simulation analysis model complete transmission path is established by HFSS. Based on this model, the near end crosstalk S13 and far end crosstalk S14 of each frequency are obtained. The influence of the maximum radial size of the BGA solder joint, the height of BGA solder joint, the size of the BGA welding disk on the near end crosstalk S13 and the far end crosstalk S14 of the complete transmission path are analyzed. It is found that the crosstalk between two complete transmission paths varies with signal frequency, the maximum radial size of BGA solder joint, solder height and diameter of solder pads.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128590014","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021187
Arpita Dutta, Nishant Pant, Pabitra Mitra, R. Mall
Fault localization is possibly the most time consuming and tedious task in the process of program debugging. To alleviate this issue, we propose an ensemble of fault localization techniques. In our proposed ensemble technique, we have used DStar and Tarantula from the spectrum based fault localization family. Along with these two methods, BPNN and RBFNN are used from neural network based fault localization techniques. We also propose a novel CNN based fault localization method to strengthen the proposed ensemble classifier. We have proposed a new metric to measure the effectiveness of fault localization techniques more accurately. On an average, our proposed ensemble method is 16.76% to 38.47% more effective than the existing fault localization techniques.
{"title":"Effective Fault Localization using an Ensemble Classifier","authors":"Arpita Dutta, Nishant Pant, Pabitra Mitra, R. Mall","doi":"10.1109/QR2MSE46217.2019.9021187","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021187","url":null,"abstract":"Fault localization is possibly the most time consuming and tedious task in the process of program debugging. To alleviate this issue, we propose an ensemble of fault localization techniques. In our proposed ensemble technique, we have used DStar and Tarantula from the spectrum based fault localization family. Along with these two methods, BPNN and RBFNN are used from neural network based fault localization techniques. We also propose a novel CNN based fault localization method to strengthen the proposed ensemble classifier. We have proposed a new metric to measure the effectiveness of fault localization techniques more accurately. On an average, our proposed ensemble method is 16.76% to 38.47% more effective than the existing fault localization techniques.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129042136","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}
Accurate reliability evaluation method play a vital role in production scheduling and equipment science maintenance decisions. However, with the advent of Industry 4.0, the structure and function of modern industrial systems have become more complex. The traditional reliability evaluation method cannot accurately describe the operating state of the production system because it cannot accurately reflect the multistate characteristics. To solve this phenomenon, a novel operational reliability evaluation method for production systems was proposed. Firstly, according to the multistate characteristics of the production system, the new concept of operational reliability is proposed. Secondly, based on the operating characteristics of the production system, a multistate production network that comprehensively analyzes the machine performance state, task execution state and product quality state is proposed, to reduce the complexity of the operation. Third, an operational reliability evaluation process for multistate production systems is proposed based on multistate production network and Markov model. Finally, the effectiveness of the proposed method is demonstrated using the case of the ferrite phase shifting unit production system.
{"title":"Operational Reliability Evaluation Method of Production Systems Based on Multistate Production Network","authors":"Xiaodong Wang, Jin-Cheng Wang, Tiejun Ma, Hangong Wang, Zhaojun Hao","doi":"10.1109/QR2MSE46217.2019.9021125","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021125","url":null,"abstract":"Accurate reliability evaluation method play a vital role in production scheduling and equipment science maintenance decisions. However, with the advent of Industry 4.0, the structure and function of modern industrial systems have become more complex. The traditional reliability evaluation method cannot accurately describe the operating state of the production system because it cannot accurately reflect the multistate characteristics. To solve this phenomenon, a novel operational reliability evaluation method for production systems was proposed. Firstly, according to the multistate characteristics of the production system, the new concept of operational reliability is proposed. Secondly, based on the operating characteristics of the production system, a multistate production network that comprehensively analyzes the machine performance state, task execution state and product quality state is proposed, to reduce the complexity of the operation. Third, an operational reliability evaluation process for multistate production systems is proposed based on multistate production network and Markov model. Finally, the effectiveness of the proposed method is demonstrated using the case of the ferrite phase shifting unit production system.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123184640","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021242
B. Pang, Shijie Guo, Jing-Lei Wang, Hai-Bin Li
Aeronautical parts, especially aircraft structures such as landing gear, are usually made of TC18 titanium alloys and other difficult-to-machine materials. The requirements for milling cutters are very high, so the price of cutters is relatively high. However, most of the blanks of aircraft structural parts are made of imported aluminium and titanium alloys, which have high cost. In order to ensure the processing accuracy, the cutting tools have to be replaced frequently. This will cause waste and increase the manufacturing cost because the actual life of the cutting tools is not fully utilized. At the same time, due to the closed high-end CNC milling machine or processing center processing, operators can not observe the actual cutting tool processing situation, can only judge the timing of tool change by experience, can not guarantee the high-quality and efficient processing of parts. So tool wear condition monitoring is a key technology in aircraft structural parts processing. Aiming at the situation that there is no theoretical data to guide tool changing in the process of high efficiency milling of aircraft structural parts, the tool wear monitoring system based on acoustic emission technology is designed according to the characteristics of acoustic emission signal. In this paper, the effects of spindle speed, feed speed, cutting width and tool wear on AE signal are studied by orthogonal experiment. The results show that tool wear has the greatest influence on the signal, followed by spindle speed and feed, and cutting width has the least influence on the signal.
{"title":"Real-Time Monitoring of Tool Wear in High-Speed Milling of Aircraft Structural Parts","authors":"B. Pang, Shijie Guo, Jing-Lei Wang, Hai-Bin Li","doi":"10.1109/QR2MSE46217.2019.9021242","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021242","url":null,"abstract":"Aeronautical parts, especially aircraft structures such as landing gear, are usually made of TC18 titanium alloys and other difficult-to-machine materials. The requirements for milling cutters are very high, so the price of cutters is relatively high. However, most of the blanks of aircraft structural parts are made of imported aluminium and titanium alloys, which have high cost. In order to ensure the processing accuracy, the cutting tools have to be replaced frequently. This will cause waste and increase the manufacturing cost because the actual life of the cutting tools is not fully utilized. At the same time, due to the closed high-end CNC milling machine or processing center processing, operators can not observe the actual cutting tool processing situation, can only judge the timing of tool change by experience, can not guarantee the high-quality and efficient processing of parts. So tool wear condition monitoring is a key technology in aircraft structural parts processing. Aiming at the situation that there is no theoretical data to guide tool changing in the process of high efficiency milling of aircraft structural parts, the tool wear monitoring system based on acoustic emission technology is designed according to the characteristics of acoustic emission signal. In this paper, the effects of spindle speed, feed speed, cutting width and tool wear on AE signal are studied by orthogonal experiment. The results show that tool wear has the greatest influence on the signal, followed by spindle speed and feed, and cutting width has the least influence on the signal.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127621076","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021157
Juan Du, Haibin Li
Rosenblatt transformation is a general method for transforming a group of non-normal random variables into a group of equivalent independent normal random variables. However, this method is not suitable for the problem of unknown joint distribution function. In view of the above problems, the joint distribution function is constructed by the Copula function in this paper, and the transformation problem of correlation non-normal variables to independent normal variables is solved. Firstly, the Copula function is used to construct the joint distribution function of correlation variables. It includes the solution of Copula function correlation parameters and the selection of correlation structure types between variables. Secondly, the Copula function is introduced into Rosenblatt transformation to obtain the conditional distribution function of variables,. The correlation variables can be transformed into independent variables. Finally, the structural reliability problem with correlation random variables is analyzed. The feasibility of the proposed method is verified by the specific examples.
{"title":"A Rosenblatt Transformation Method Based on Copula Function for Solving Structural Reliability","authors":"Juan Du, Haibin Li","doi":"10.1109/QR2MSE46217.2019.9021157","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021157","url":null,"abstract":"Rosenblatt transformation is a general method for transforming a group of non-normal random variables into a group of equivalent independent normal random variables. However, this method is not suitable for the problem of unknown joint distribution function. In view of the above problems, the joint distribution function is constructed by the Copula function in this paper, and the transformation problem of correlation non-normal variables to independent normal variables is solved. Firstly, the Copula function is used to construct the joint distribution function of correlation variables. It includes the solution of Copula function correlation parameters and the selection of correlation structure types between variables. Secondly, the Copula function is introduced into Rosenblatt transformation to obtain the conditional distribution function of variables,. The correlation variables can be transformed into independent variables. Finally, the structural reliability problem with correlation random variables is analyzed. The feasibility of the proposed method is verified by the specific examples.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"204 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113953245","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}
Pub Date : 2019-08-01DOI: 10.1109/QR2MSE46217.2019.9021241
Khaldoon Hijazin, Tieling Zhang
The internet of things (IoT) has become an important technology in our life. It is considered as an enhancing feature which could improve the quality of communications if it is applied in the right way. However, if the IoT is not well designed or designed with complicated models, it will result in not easy application so that technicians and engineers will avoid using it. In this paper, a model of IoT utilized in manufacturing industry is illustrated to show the importance of its application. It shows how the IoT is applied in its simplest form through developing a production system in a food factory. One manufacturing line is studied, which is a teacake manufacturing line in a factory in Jordan. After analyzing the production data of the production system and considering the minimum resources required for the production, a model is introduced with programming to show how a proper design of the IoT can help reduce the cost of the production with appropriate human resource planning and reduced cycle time in producing each batch of the Sambo teacakes. Finally, this paper indicates that IoT is a critical technology in manufacturing, which could help the industry to make the entire strategy in order to build and maintain a sustainable and competitive position in the market.
{"title":"The Application of IoT Technology to a Manufacturing Process: Case Study","authors":"Khaldoon Hijazin, Tieling Zhang","doi":"10.1109/QR2MSE46217.2019.9021241","DOIUrl":"https://doi.org/10.1109/QR2MSE46217.2019.9021241","url":null,"abstract":"The internet of things (IoT) has become an important technology in our life. It is considered as an enhancing feature which could improve the quality of communications if it is applied in the right way. However, if the IoT is not well designed or designed with complicated models, it will result in not easy application so that technicians and engineers will avoid using it. In this paper, a model of IoT utilized in manufacturing industry is illustrated to show the importance of its application. It shows how the IoT is applied in its simplest form through developing a production system in a food factory. One manufacturing line is studied, which is a teacake manufacturing line in a factory in Jordan. After analyzing the production data of the production system and considering the minimum resources required for the production, a model is introduced with programming to show how a proper design of the IoT can help reduce the cost of the production with appropriate human resource planning and reduced cycle time in producing each batch of the Sambo teacakes. Finally, this paper indicates that IoT is a critical technology in manufacturing, which could help the industry to make the entire strategy in order to build and maintain a sustainable and competitive position in the market.","PeriodicalId":233855,"journal":{"name":"2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123339592","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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