Waste reduction via image classification algorithms: beyond the human eye with an AI-based vision
Modern manufacturing is the world's largest and most automated industrial sector. The rise of Industry 4.0 technologies such as Big Data, Internet of Things (IoT) devices, and Machine Learning has enabled a better connection with machines and factory systems. Data harvesting allowed for a more...
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| Vydané v: | International journal of production research Ročník 62; číslo 9; s. 3193 - 3211 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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London
Taylor & Francis
02.05.2024
Taylor & Francis LLC |
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| ISSN: | 0020-7543, 1366-588X |
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| Abstract | Modern manufacturing is the world's largest and most automated industrial sector. The rise of Industry 4.0 technologies such as Big Data, Internet of Things (IoT) devices, and Machine Learning has enabled a better connection with machines and factory systems. Data harvesting allowed for a more seamless and comprehensive implementation of the knowledge-based decision-making process. New models that provide a competitive edge must be created by combining the Lean paradigm with the new technologies of Industry 4.0. This paper presents novel computer-based vision models for automated detection and classification of damaged packages from intact packages. In high-volume production environments, the package manual inspection process through the human eye consumes inordinate amounts of time poring over physical packages. Our proposed three different computer-based vision approaches detect damaged packages to prevent them from moving to shipping operations that would otherwise incur waste in the form of wasted operating hours, wasted resources and lost customer satisfaction. The proposed approaches were carried out on a data set consisting of package images and achieved high precision, accuracy, and recall values during the training and validation stage, with the resultant trained YOLO v7 model. |
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| AbstractList | Modern manufacturing is the world's largest and most automated industrial sector. The rise of Industry 4.0 technologies such as Big Data, Internet of Things (IoT) devices, and Machine Learning has enabled a better connection with machines and factory systems. Data harvesting allowed for a more seamless and comprehensive implementation of the knowledge-based decision-making process. New models that provide a competitive edge must be created by combining the Lean paradigm with the new technologies of Industry 4.0. This paper presents novel computer-based vision models for automated detection and classification of damaged packages from intact packages. In high-volume production environments, the package manual inspection process through the human eye consumes inordinate amounts of time poring over physical packages. Our proposed three different computer-based vision approaches detect damaged packages to prevent them from moving to shipping operations that would otherwise incur waste in the form of wasted operating hours, wasted resources and lost customer satisfaction. The proposed approaches were carried out on a data set consisting of package images and achieved high precision, accuracy, and recall values during the training and validation stage, with the resultant trained YOLO v7 model. Not provided. |
| Author | Bouzary, Hamed Shahin, Mohammad Hosseinzadeh, Ali Shahin, Awni Chen, F. Frank |
| Author_xml | – sequence: 1 givenname: Mohammad surname: Shahin fullname: Shahin, Mohammad organization: The University of Texas at San Antonio – sequence: 2 givenname: F. Frank surname: Chen fullname: Chen, F. Frank email: FF.Chen@utsa.edu organization: The University of Texas at San Antonio – sequence: 3 givenname: Ali surname: Hosseinzadeh fullname: Hosseinzadeh, Ali organization: The University of Texas at San Antonio – sequence: 4 givenname: Hamed surname: Bouzary fullname: Bouzary, Hamed organization: The University of Texas at San Antonio – sequence: 5 givenname: Awni surname: Shahin fullname: Shahin, Awni organization: Mu'tah University |
| BackLink | https://www.osti.gov/biblio/2578642$$D View this record in Osti.gov |
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| Cites_doi | 10.1111/exsy.12800 10.1109/ACCESS.2021.3077499 10.1080/00207543.2022.2100840 10.1101/2020.05.03.075184 10.1080/09537287.2021.1917720 10.1080/00207543.2022.2056860 10.1109/ACCESS.2022.3193250 10.1007/s41315-021-00180-5 10.12776/qip.v25i3.1613 10.1109/JSTARS.2021.3130238 10.12709/mest.10.10.01.01 10.1109/ITOEC53115.2022.9734594 10.1080/19397038.2019.1566411 10.1007/978-3-319-46448-0_2 10.1108/IJLSS-06-2020-0075 10.1109/5.726791 10.1016/j.cie.2019.106099 10.1080/00207543.2020.1832274 10.1007/s00170-022-10259-3 10.1080/00207543.2022.2153943 10.1016/j.jclepro.2019.119903 10.1007/978-3-319-56871-3_8 10.1080/00207543.2020.1824085 10.1108/IJCHM-03-2022-0304 10.1108/IJLSS-05-2020-0067 10.3390/w10121712 10.1109/ICCV.2015.169 10.1109/ICNISC54316.2021.00084 10.3390/logistics5040066 10.1007/s11042-022-12962-5 10.2478/mspe-2022-0013 10.1108/IJLSS-11-2015-0042 10.1108/IJLSS-03-2013-0019 10.1007/s12553-022-00691-6 10.1109/ICTA50426.2020.9332115 10.1109/ACCESS.2021.3077567 10.1109/ACCESS.2022.3144433 10.29119/1641-3466.2022.156.27 10.1016/j.autcon.2017.11.002 10.1155/2021/5597337 10.1108/IJPPM-05-2020-0223 10.1109/TIFS.2019.2907184 10.1007/s11042-022-12916-x 10.1109/CVPR.2016.90 10.1007/978-3-031-18326-3_11 10.1109/ACCESS.2020.3021508 10.1109/ACCESS.2020.3012701 10.1007/s42486-021-00057-3 10.1007/s00170-022-10329-6 10.1016/j.asoc.2022.108942 10.1088/1757-899X/271/1/012037 10.1109/TCBB.2022.3199572 10.1109/ACCESS.2022.3160179 10.1007/s00170-020-05822-9 10.1007/s00170-021-06748-6 10.1109/DICTA51227.2020.9363372 10.1080/00207543.2019.1651458 10.1080/00207543.2021.1946192 10.3390/su131810029 10.1109/ICCV.2017.322 10.1117/1.JEI.28.1.013023 10.1007/s11263-007-0090-8 10.1007/s11042-022-13451-5 10.1109/UEMCON53757.2021.9666552 10.1109/ACCESS.2021.3064040 10.1007/s00170-020-05124-0 10.1007/s00170-023-10970-9 10.1109/AISP53593.2022.9760665 10.1155/2022/1070405 10.1109/LGRS.2020.3038901 10.1016/j.ijproman.2006.11.007 10.22381/emfm16320215 10.1007/s40313-019-00551-1 10.1080/00207543.2023.2179346 10.1162/neco.1997.9.8.1735 10.1080/00207543.2020.1740342 10.1080/00207543.2019.1672902 10.1108/IJLSS-02-2014-0004 10.1016/j.ijpe.2019.04.036 10.1109/RIVF51545.2021.9642128 10.1109/CVPR.2014.81 10.21203/rs.3.rs-2782987/v1 10.1108/IJLSS-06-2017-0063 10.1016/j.jmsy.2021.03.005 10.1108/IJLSS-06-2015-0024 10.48550/arXiv.1905.11946 10.1142/S0218001421600089 10.1109/CAC48633.2019.8997382 10.29207/resti.v5i4.3175 10.1109/ACCESS.2020.3029555 10.1007/s13198-021-01514-z 10.1016/j.array.2022.100220 10.17512/pjms.2022.25.2.24 10.1109/ACCESS.2021.3113337 10.1080/002075400189509 10.1016/j.autcon.2013.08.009 10.1109/ACCESS.2022.3184113 10.1145/3065386 10.1108/IJCHM-01-2022-0103 |
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| References | e_1_3_3_50_1 e_1_3_3_77_1 e_1_3_3_39_1 e_1_3_3_16_1 e_1_3_3_35_1 e_1_3_3_58_1 e_1_3_3_92_1 e_1_3_3_12_1 e_1_3_3_31_1 e_1_3_3_54_1 e_1_3_3_73_1 e_1_3_3_96_1 e_1_3_3_113_1 e_1_3_3_61_1 e_1_3_3_88_1 e_1_3_3_9_1 e_1_3_3_105_1 e_1_3_3_109_1 e_1_3_3_27_1 e_1_3_3_46_1 e_1_3_3_69_1 e_1_3_3_80_1 e_1_3_3_5_1 e_1_3_3_23_1 e_1_3_3_42_1 e_1_3_3_65_1 e_1_3_3_84_1 e_1_3_3_101_1 e_1_3_3_30_1 e_1_3_3_76_1 e_1_3_3_99_1 Devitt Caitlin. (e_1_3_3_22_1) 2022; 394 e_1_3_3_116_1 e_1_3_3_19_1 e_1_3_3_38_1 e_1_3_3_91_1 e_1_3_3_34_1 e_1_3_3_72_1 e_1_3_3_95_1 e_1_3_3_112_1 e_1_3_3_11_1 e_1_3_3_53_1 e_1_3_3_41_1 e_1_3_3_87_1 e_1_3_3_60_1 e_1_3_3_108_1 e_1_3_3_8_1 Ohno T. (e_1_3_3_57_1) 1991 Ciaburro Giuseppe (e_1_3_3_15_1) 2017 e_1_3_3_49_1 e_1_3_3_100_1 e_1_3_3_26_1 e_1_3_3_68_1 e_1_3_3_45_1 e_1_3_3_83_1 e_1_3_3_104_1 e_1_3_3_4_1 e_1_3_3_64_1 e_1_3_3_52_1 e_1_3_3_75_1 e_1_3_3_98_1 e_1_3_3_71_1 e_1_3_3_79_1 e_1_3_3_18_1 e_1_3_3_14_1 e_1_3_3_37_1 e_1_3_3_90_1 e_1_3_3_111_1 e_1_3_3_10_1 e_1_3_3_33_1 e_1_3_3_56_1 e_1_3_3_94_1 Womack J. (e_1_3_3_106_1) 2003 e_1_3_3_115_1 e_1_3_3_40_1 e_1_3_3_63_1 e_1_3_3_86_1 e_1_3_3_7_1 e_1_3_3_107_1 e_1_3_3_29_1 e_1_3_3_25_1 e_1_3_3_48_1 e_1_3_3_3_1 e_1_3_3_21_1 e_1_3_3_44_1 e_1_3_3_67_1 e_1_3_3_82_1 e_1_3_3_103_1 e_1_3_3_97_1 e_1_3_3_51_1 e_1_3_3_78_1 e_1_3_3_70_1 e_1_3_3_17_1 e_1_3_3_110_1 e_1_3_3_13_1 e_1_3_3_59_1 e_1_3_3_36_1 e_1_3_3_93_1 e_1_3_3_114_1 e_1_3_3_74_1 Hiremath Chetan V. (e_1_3_3_32_1) 2021; 18 e_1_3_3_62_1 e_1_3_3_89_1 e_1_3_3_6_1 e_1_3_3_28_1 e_1_3_3_24_1 e_1_3_3_47_1 Murugesan T. K. (e_1_3_3_55_1) 2012; 29 e_1_3_3_81_1 e_1_3_3_2_1 e_1_3_3_20_1 e_1_3_3_66_1 e_1_3_3_43_1 e_1_3_3_85_1 e_1_3_3_102_1 |
| References_xml | – ident: e_1_3_3_63_1 doi: 10.1111/exsy.12800 – ident: e_1_3_3_109_1 doi: 10.1109/ACCESS.2021.3077499 – ident: e_1_3_3_91_1 doi: 10.1080/00207543.2022.2100840 – ident: e_1_3_3_25_1 – ident: e_1_3_3_112_1 doi: 10.1101/2020.05.03.075184 – ident: e_1_3_3_101_1 doi: 10.1080/09537287.2021.1917720 – ident: e_1_3_3_52_1 doi: 10.1080/00207543.2022.2056860 – ident: e_1_3_3_61_1 doi: 10.1109/ACCESS.2022.3193250 – ident: e_1_3_3_69_1 doi: 10.1007/s41315-021-00180-5 – ident: e_1_3_3_80_1 doi: 10.12776/qip.v25i3.1613 – ident: e_1_3_3_110_1 doi: 10.1109/JSTARS.2021.3130238 – ident: e_1_3_3_12_1 doi: 10.12709/mest.10.10.01.01 – volume: 29 start-page: 295 issue: 2 year: 2012 ident: e_1_3_3_55_1 article-title: Competitive Advantage of World Class Manufacturing System (WCMS)–A Study of Manufacturing Companies in South India publication-title: European Journal of Social Sciences – ident: e_1_3_3_104_1 – ident: e_1_3_3_48_1 doi: 10.1109/ITOEC53115.2022.9734594 – ident: e_1_3_3_100_1 doi: 10.1080/19397038.2019.1566411 – ident: e_1_3_3_51_1 doi: 10.1007/978-3-319-46448-0_2 – ident: e_1_3_3_5_1 doi: 10.1108/IJLSS-06-2020-0075 – ident: e_1_3_3_47_1 doi: 10.1109/5.726791 – ident: e_1_3_3_8_1 doi: 10.1016/j.cie.2019.106099 – ident: e_1_3_3_9_1 doi: 10.1080/00207543.2020.1832274 – ident: e_1_3_3_82_1 doi: 10.1007/s00170-022-10259-3 – ident: e_1_3_3_98_1 doi: 10.1080/00207543.2022.2153943 – ident: e_1_3_3_7_1 doi: 10.1016/j.jclepro.2019.119903 – ident: e_1_3_3_102_1 – volume-title: Neural Networks with R: Smart Models Using CNN, RNN, Deep Learning, and Artificial Intelligence Principles year: 2017 ident: e_1_3_3_15_1 – ident: e_1_3_3_71_1 – ident: e_1_3_3_19_1 doi: 10.1007/978-3-319-56871-3_8 – ident: e_1_3_3_116_1 doi: 10.1080/00207543.2020.1824085 – ident: e_1_3_3_54_1 doi: 10.1108/IJCHM-03-2022-0304 – ident: e_1_3_3_97_1 doi: 10.1108/IJLSS-05-2020-0067 – ident: e_1_3_3_115_1 doi: 10.3390/w10121712 – ident: e_1_3_3_26_1 doi: 10.1109/ICCV.2015.169 – ident: e_1_3_3_108_1 doi: 10.1109/ICNISC54316.2021.00084 – ident: e_1_3_3_89_1 doi: 10.3390/logistics5040066 – ident: e_1_3_3_28_1 – ident: e_1_3_3_23_1 doi: 10.1007/s11042-022-12962-5 – ident: e_1_3_3_56_1 doi: 10.2478/mspe-2022-0013 – ident: e_1_3_3_72_1 doi: 10.1108/IJLSS-11-2015-0042 – ident: e_1_3_3_44_1 doi: 10.1108/IJLSS-03-2013-0019 – ident: e_1_3_3_66_1 doi: 10.1007/s12553-022-00691-6 – ident: e_1_3_3_93_1 doi: 10.1109/ICTA50426.2020.9332115 – ident: e_1_3_3_92_1 doi: 10.1109/ACCESS.2021.3077567 – ident: e_1_3_3_75_1 doi: 10.1109/ACCESS.2022.3144433 – ident: e_1_3_3_39_1 doi: 10.29119/1641-3466.2022.156.27 – ident: e_1_3_3_24_1 doi: 10.1016/j.autcon.2017.11.002 – ident: e_1_3_3_77_1 doi: 10.1155/2021/5597337 – ident: e_1_3_3_88_1 doi: 10.1108/IJPPM-05-2020-0223 – ident: e_1_3_3_59_1 doi: 10.1109/TIFS.2019.2907184 – ident: e_1_3_3_14_1 doi: 10.1007/s11042-022-12916-x – ident: e_1_3_3_31_1 doi: 10.1109/CVPR.2016.90 – ident: e_1_3_3_94_1 – ident: e_1_3_3_83_1 doi: 10.1007/978-3-031-18326-3_11 – ident: e_1_3_3_6_1 doi: 10.1109/ACCESS.2020.3021508 – ident: e_1_3_3_53_1 – ident: e_1_3_3_114_1 doi: 10.1109/ACCESS.2020.3012701 – ident: e_1_3_3_68_1 doi: 10.1007/s42486-021-00057-3 – ident: e_1_3_3_85_1 doi: 10.1007/s00170-022-10329-6 – ident: e_1_3_3_38_1 doi: 10.1016/j.asoc.2022.108942 – ident: e_1_3_3_70_1 doi: 10.1088/1757-899X/271/1/012037 – ident: e_1_3_3_34_1 doi: 10.1109/TCBB.2022.3199572 – ident: e_1_3_3_95_1 doi: 10.1109/ACCESS.2022.3160179 – ident: e_1_3_3_105_1 doi: 10.1007/s00170-020-05822-9 – ident: e_1_3_3_107_1 doi: 10.1007/s00170-021-06748-6 – ident: e_1_3_3_90_1 doi: 10.1109/DICTA51227.2020.9363372 – ident: e_1_3_3_79_1 doi: 10.1080/00207543.2019.1651458 – ident: e_1_3_3_65_1 doi: 10.1080/00207543.2021.1946192 – ident: e_1_3_3_20_1 doi: 10.3390/su131810029 – ident: e_1_3_3_30_1 doi: 10.1109/ICCV.2017.322 – ident: e_1_3_3_46_1 doi: 10.1117/1.JEI.28.1.013023 – ident: e_1_3_3_74_1 doi: 10.1007/s11263-007-0090-8 – ident: e_1_3_3_67_1 doi: 10.1007/s11042-022-13451-5 – 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article-title: Projects Face Labor Shortage publication-title: Bond Buyer – ident: e_1_3_3_10_1 doi: 10.1109/RIVF51545.2021.9642128 – ident: e_1_3_3_27_1 doi: 10.1109/CVPR.2014.81 – ident: e_1_3_3_87_1 doi: 10.21203/rs.3.rs-2782987/v1 – ident: e_1_3_3_29_1 doi: 10.1108/IJLSS-06-2017-0063 – ident: e_1_3_3_103_1 doi: 10.1016/j.jmsy.2021.03.005 – ident: e_1_3_3_64_1 doi: 10.1108/IJLSS-06-2015-0024 – ident: e_1_3_3_96_1 doi: 10.48550/arXiv.1905.11946 – ident: e_1_3_3_41_1 doi: 10.1142/S0218001421600089 – ident: e_1_3_3_111_1 doi: 10.1109/CAC48633.2019.8997382 – ident: e_1_3_3_35_1 doi: 10.29207/resti.v5i4.3175 – volume-title: Lean Thinking: Banish Waste and Create Wealth in Your Corporation year: 2003 ident: e_1_3_3_106_1 – ident: e_1_3_3_37_1 doi: 10.1109/ACCESS.2020.3029555 – ident: e_1_3_3_13_1 doi: 10.1007/s13198-021-01514-z – ident: e_1_3_3_17_1 doi: 10.1016/j.array.2022.100220 – ident: e_1_3_3_16_1 doi: 10.1016/j.array.2022.100220 – ident: e_1_3_3_99_1 doi: 10.17512/pjms.2022.25.2.24 – ident: e_1_3_3_2_1 doi: 10.1109/ACCESS.2021.3113337 – ident: e_1_3_3_21_1 doi: 10.1080/002075400189509 – ident: e_1_3_3_40_1 doi: 10.1016/j.autcon.2013.08.009 – ident: e_1_3_3_81_1 doi: 10.1109/ACCESS.2022.3184113 – ident: e_1_3_3_42_1 doi: 10.1145/3065386 – volume: 18 start-page: 21 issue: 3 year: 2021 ident: e_1_3_3_32_1 article-title: Unveiling the Linkages Between Enablers for On-Time Dispatch of Finished Goods in SMEs: An Integrative TISM-Fuzzy MICMAC Analysis publication-title: IUP Journal of Supply Chain Management – volume-title: El Sistema de Produccion Toyota: Más Allá de La Produccion a Gran Escala [Internet] year: 1991 ident: e_1_3_3_57_1 – ident: e_1_3_3_45_1 doi: 10.1108/IJCHM-01-2022-0103 |
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| SubjectTerms | Algorithms Artificial intelligence Automation Big Data Customer satisfaction Damage detection Decision making Engineering Image classification Industrial applications Industry 4.0 Internet of Things Lean manufacturing Machine learning New technology Operations Research & Management Science Packages waste reduction |
| Title | Waste reduction via image classification algorithms: beyond the human eye with an AI-based vision |
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