{"title":"基于层次分析法的设计阶段人为错误概率估计模型","authors":"Ung-Kyun Lee","doi":"10.3311/ccc2019-028","DOIUrl":null,"url":null,"abstract":"The building information modeling (BIM) technique is used widely in construction. In general, BIM can prevent interference between different types of construction activities in advance, thereby reducing the cost of reconstruction. While it is clear that a decrease in the number of requests for information in the construction stage would have obvious benefits, there is a need to determine the effects of the investment from the planning stage. Therefore, in this study, a procedure for quantifying the design errors that occur at the design stage is proposed considering the probability of the human errors concept. To achieve this, factors for evaluating human errors can arise during the drawing stage. Based on these factors, an analytic-hierarchy-process-based human error probability estimation model is suggested. Based on the factors affecting the error in the design stage, we construct a hierarchy and calculate the relative importance based on the probability and assess the effectiveness of each risk control option. It is expected that if the model presented in this study is linked with the loss cost data for each factor, a loss estimation model at the design stage can be developed. © 2019 The Authors. Published by Budapest University of Technology and Economics & Diamond Congress Ltd. Peer-review under responsibility of the scientific committee of the Creative Construction Conference 2019.","PeriodicalId":231420,"journal":{"name":"Proceedings of the Creative Construction Conference 2019","volume":"256 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytic Hierarchy Process-Based Model for Estimating Probability of Human Error in Design Stage\",\"authors\":\"Ung-Kyun Lee\",\"doi\":\"10.3311/ccc2019-028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The building information modeling (BIM) technique is used widely in construction. In general, BIM can prevent interference between different types of construction activities in advance, thereby reducing the cost of reconstruction. While it is clear that a decrease in the number of requests for information in the construction stage would have obvious benefits, there is a need to determine the effects of the investment from the planning stage. Therefore, in this study, a procedure for quantifying the design errors that occur at the design stage is proposed considering the probability of the human errors concept. To achieve this, factors for evaluating human errors can arise during the drawing stage. Based on these factors, an analytic-hierarchy-process-based human error probability estimation model is suggested. Based on the factors affecting the error in the design stage, we construct a hierarchy and calculate the relative importance based on the probability and assess the effectiveness of each risk control option. It is expected that if the model presented in this study is linked with the loss cost data for each factor, a loss estimation model at the design stage can be developed. © 2019 The Authors. Published by Budapest University of Technology and Economics & Diamond Congress Ltd. Peer-review under responsibility of the scientific committee of the Creative Construction Conference 2019.\",\"PeriodicalId\":231420,\"journal\":{\"name\":\"Proceedings of the Creative Construction Conference 2019\",\"volume\":\"256 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Creative Construction Conference 2019\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3311/ccc2019-028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Creative Construction Conference 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3311/ccc2019-028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Analytic Hierarchy Process-Based Model for Estimating Probability of Human Error in Design Stage
The building information modeling (BIM) technique is used widely in construction. In general, BIM can prevent interference between different types of construction activities in advance, thereby reducing the cost of reconstruction. While it is clear that a decrease in the number of requests for information in the construction stage would have obvious benefits, there is a need to determine the effects of the investment from the planning stage. Therefore, in this study, a procedure for quantifying the design errors that occur at the design stage is proposed considering the probability of the human errors concept. To achieve this, factors for evaluating human errors can arise during the drawing stage. Based on these factors, an analytic-hierarchy-process-based human error probability estimation model is suggested. Based on the factors affecting the error in the design stage, we construct a hierarchy and calculate the relative importance based on the probability and assess the effectiveness of each risk control option. It is expected that if the model presented in this study is linked with the loss cost data for each factor, a loss estimation model at the design stage can be developed. © 2019 The Authors. Published by Budapest University of Technology and Economics & Diamond Congress Ltd. Peer-review under responsibility of the scientific committee of the Creative Construction Conference 2019.