Laser micro-hole processing has been widely used in industry. Many laser processing parameters can affect the processing results. The relationship between the geometrical shapes of micro-holes and the laser processing parameters has not been determined accurately. In this paper, experiments on the femtosecond laser drilling of the nickel-base single-crystal super-alloy (DD6) materials were conducted to determine the relationship between the parameters, such as the laser single-pulse energy, rotation rate, and down-ward focus rate, and the geometrical characteristics of the micro-holes, such as the diameter, and roundness. A group of orthogonal experiments were conducted to determine the effects of the comprehensive influencing factors on the geometrical characteristics of the micro-holes. After the experiments were conducted and analysed, the experimental results were modelled by a backpropagation neural network, and the mapping relationship between the laser parameters and the geometrical morphologies of the micro-holes was constructed. The model established by the backpropagation neural network could obtain accurate prediction results, and the predictions of the diameters of the micro-holes were better than those of the roundness.
{"title":"Femtosecond laser helical drilling of nickel-base single-crystal super-alloy: Effect of machining parameters on geometrical characteristics of micro-holes","authors":"C. Yin, Z. Wu, Y. Dong, Y. You, T. Liao","doi":"10.14743/apem2019.4.337","DOIUrl":"https://doi.org/10.14743/apem2019.4.337","url":null,"abstract":"Laser micro-hole processing has been widely used in industry. Many laser processing parameters can affect the processing results. The relationship between the geometrical shapes of micro-holes and the laser processing parameters has not been determined accurately. In this paper, experiments on the femtosecond laser drilling of the nickel-base single-crystal super-alloy (DD6) materials were conducted to determine the relationship between the parameters, such as the laser single-pulse energy, rotation rate, and down-ward focus rate, and the geometrical characteristics of the micro-holes, such as the diameter, and roundness. A group of orthogonal experiments were conducted to determine the effects of the comprehensive influencing factors on the geometrical characteristics of the micro-holes. After the experiments were conducted and analysed, the experimental results were modelled by a backpropagation neural network, and the mapping relationship between the laser parameters and the geometrical morphologies of the micro-holes was constructed. The model established by the backpropagation neural network could obtain accurate prediction results, and the predictions of the diameters of the micro-holes were better than those of the roundness.","PeriodicalId":48763,"journal":{"name":"Advances in Production Engineering & Management","volume":"97 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2019-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80847328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nenad Medić, Z. Anisic, B. Lalic, U. Marjanović, M. Brezocnik
{"title":"Hybrid fuzzy multi-attribute decision making model for evaluation of advanced digital technologies in manufacturing: Industry 4.0 perspective","authors":"Nenad Medić, Z. Anisic, B. Lalic, U. Marjanović, M. Brezocnik","doi":"10.14743/apem2019.4.343","DOIUrl":"https://doi.org/10.14743/apem2019.4.343","url":null,"abstract":"","PeriodicalId":48763,"journal":{"name":"Advances in Production Engineering & Management","volume":"547 1","pages":"483-493"},"PeriodicalIF":3.6,"publicationDate":"2019-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77138799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Santosi, I. Budak, Mario Šokac, M. Hadzistevic, D. Vukelić
Small and start-up companies that need product quality control can usually only afford low-cost systems. The main goal of this investigation was to estimate the influence of high dynamic range images as input for the low-cost photogrammetric structure from motion 3D digitization. Various industrial products made of metal or polymer suffer from poor visual texture. To overcome the lack of visual texture and ensure appropriate 3D reconstruction, stochastic image in the form of the light pattern was projected on the product surface. During stochastic pattern projection, a set of low dynamic range and sets of high dynamic range images were captured and processed. In this investigation digital single lens reflex camera that supports five different tone-mapping operators to create high dynamic range images were used. Also, high precision measurements on a coordinate measuring machine are performed in order to verify real product geometry. The obtained results showed that reconstructed polygonal 3D models generated from high dynamic range images in this case study don’t have a dominant influence on the accuracy when compared to the polygonal 3D model generated from low dynamic range images. In order to estimate 3D models dimensional accuracy, they were compared using computer-aided inspection analysis. The best achieved standard deviation distance was +0.025 mm for 3D model generated based on high dynamic range images compared to the nominal CAD model.
{"title":"Influence of high dynamic range images on the accuracy of the photogrammetric 3D digitization: A case study","authors":"Z. Santosi, I. Budak, Mario Šokac, M. Hadzistevic, D. Vukelić","doi":"10.14743/apem2019.3.336","DOIUrl":"https://doi.org/10.14743/apem2019.3.336","url":null,"abstract":"Small and start-up companies that need product quality control can usually only afford low-cost systems. The main goal of this investigation was to estimate the influence of high dynamic range images as input for the low-cost photogrammetric structure from motion 3D digitization. Various industrial products made of metal or polymer suffer from poor visual texture. To overcome the lack of visual texture and ensure appropriate 3D reconstruction, stochastic image in the form of the light pattern was projected on the product surface. During stochastic pattern projection, a set of low dynamic range and sets of high dynamic range images were captured and processed. In this investigation digital single lens reflex camera that supports five different tone-mapping operators to create high dynamic range images were used. Also, high precision measurements on a coordinate measuring machine are performed in order to verify real product geometry. The obtained results showed that reconstructed polygonal 3D models generated from high dynamic range images in this case study don’t have a dominant influence on the accuracy when compared to the polygonal 3D model generated from low dynamic range images. In order to estimate 3D models dimensional accuracy, they were compared using computer-aided inspection analysis. The best achieved standard deviation distance was +0.025 mm for 3D model generated based on high dynamic range images compared to the nominal CAD model.","PeriodicalId":48763,"journal":{"name":"Advances in Production Engineering & Management","volume":"122 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74274210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal timing of price change with strategic customers under demand uncertainty: A real option approach","authors":"Y. Lee, J. Lee, S. Kim","doi":"10.14743/apem2019.3.335","DOIUrl":"https://doi.org/10.14743/apem2019.3.335","url":null,"abstract":"","PeriodicalId":48763,"journal":{"name":"Advances in Production Engineering & Management","volume":"2 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84233444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：