Research on quality traceability of cigarette by combining PDCA quality cycle with information strategy based on fuzzy classification

For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA qu...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of intelligent & fuzzy systems 2021-01, Vol.40 (4), p.8217-8226
Hauptverfasser: Wang, Xiaodong, Wang, Xiaoming, Wu, Junfeng, Zheng, Kai, Pang, Yanhong, Gang, Song
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 8226
container_issue 4
container_start_page 8217
container_title Journal of intelligent & fuzzy systems
container_volume 40
creator Wang, Xiaodong
Wang, Xiaoming
Wu, Junfeng
Zheng, Kai
Pang, Yanhong
Gang, Song
description For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA quality cycle process, and then constructs IS-PDCA process based on information strategy (IS) to analyze the quality traceability process of cigarette products. The key links are determined according to the traceability process of cigarette logistics, and the traceability resource scheduling function is determined through the product. Then, according to the determined scheduling function and RFID technology, the optimal allocation strategy is constructed to complete the feature extraction and classification identification of cigarette quality labels. For assessing the quality of cigarette evaluation, classification based on fuzzy is proposed and artificial neural network are utilized for calculating the grade of cigarette. Finally, a process of cigarette quality traceability combining PDCA quality cycle and information strategy is formed, and the quality traceability results are constructed by means of QR code technology, so as to realize the process system of cigarette quality traceability and improve the quality control ability of cigarettes. The simulation results show that the cigarette quality traceability method constructed in this paper can obtain the cigarette quality control with good adaptive performance, and the control process shows a strong ability, which improves the feasibility and effectiveness of the cigarette quality traceability.
doi_str_mv 10.3233/JIFS-189644
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2511974130</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2511974130</sourcerecordid><originalsourceid>FETCH-LOGICAL-c261t-d406a257ecd092ea7846e5bf595ab30c41c608b3fd56991978d32c49d6967193</originalsourceid><addsrcrecordid>eNo9kM1KAzEURoMoWKsrXyDgUkbzP5NlqVYrBUW7HzKZpE2ZzrRJikz3vrdpK67u_eDc78IB4BajB0oofXybTr4yXEjB2BkY4CLnWQr5edqRYBkmTFyCqxBWCOGcEzQAP58mGOX1EnYt3O5U42IPo1faqModQ2ehdgvlTYwGVj3U3bpyrWsX8ONpPPq_0b1uDPx2cQldazu_VtGlypC6oln0sFLB1IcndrffJ7xRITjr9BG7BhdWNcHc_M0hmE-e5-PXbPb-Mh2PZpkmAsesZkgownOjaySJUXnBhOGV5ZKriiLNsBaoqKituZASy7yoKdFM1iJJwJIOwd2pduO77c6EWK66nW_Tx5JwnHiGKUrU_YnSvgvBG1tuvFsr35cYlQfN5UFzedJMfwG5h3Hi</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2511974130</pqid></control><display><type>article</type><title>Research on quality traceability of cigarette by combining PDCA quality cycle with information strategy based on fuzzy classification</title><source>EBSCOhost Business Source Complete</source><creator>Wang, Xiaodong ; Wang, Xiaoming ; Wu, Junfeng ; Zheng, Kai ; Pang, Yanhong ; Gang, Song</creator><contributor>Gonzalez Crespo, Ruben ; Sanjuán Martínez, Oscar ; Fenza, Giuseppe</contributor><creatorcontrib>Wang, Xiaodong ; Wang, Xiaoming ; Wu, Junfeng ; Zheng, Kai ; Pang, Yanhong ; Gang, Song ; Gonzalez Crespo, Ruben ; Sanjuán Martínez, Oscar ; Fenza, Giuseppe</creatorcontrib><description>For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA quality cycle process, and then constructs IS-PDCA process based on information strategy (IS) to analyze the quality traceability process of cigarette products. The key links are determined according to the traceability process of cigarette logistics, and the traceability resource scheduling function is determined through the product. Then, according to the determined scheduling function and RFID technology, the optimal allocation strategy is constructed to complete the feature extraction and classification identification of cigarette quality labels. For assessing the quality of cigarette evaluation, classification based on fuzzy is proposed and artificial neural network are utilized for calculating the grade of cigarette. Finally, a process of cigarette quality traceability combining PDCA quality cycle and information strategy is formed, and the quality traceability results are constructed by means of QR code technology, so as to realize the process system of cigarette quality traceability and improve the quality control ability of cigarettes. The simulation results show that the cigarette quality traceability method constructed in this paper can obtain the cigarette quality control with good adaptive performance, and the control process shows a strong ability, which improves the feasibility and effectiveness of the cigarette quality traceability.</description><identifier>ISSN: 1064-1246</identifier><identifier>EISSN: 1875-8967</identifier><identifier>DOI: 10.3233/JIFS-189644</identifier><language>eng</language><publisher>Amsterdam: IOS Press BV</publisher><subject>Adaptive control ; Artificial neural networks ; Cigarettes ; Classification ; Feature extraction ; Logistics ; Quality assessment ; Quality control ; Resource scheduling</subject><ispartof>Journal of intelligent &amp; fuzzy systems, 2021-01, Vol.40 (4), p.8217-8226</ispartof><rights>Copyright IOS Press BV 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c261t-d406a257ecd092ea7846e5bf595ab30c41c608b3fd56991978d32c49d6967193</citedby><cites>FETCH-LOGICAL-c261t-d406a257ecd092ea7846e5bf595ab30c41c608b3fd56991978d32c49d6967193</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><contributor>Gonzalez Crespo, Ruben</contributor><contributor>Sanjuán Martínez, Oscar</contributor><contributor>Fenza, Giuseppe</contributor><creatorcontrib>Wang, Xiaodong</creatorcontrib><creatorcontrib>Wang, Xiaoming</creatorcontrib><creatorcontrib>Wu, Junfeng</creatorcontrib><creatorcontrib>Zheng, Kai</creatorcontrib><creatorcontrib>Pang, Yanhong</creatorcontrib><creatorcontrib>Gang, Song</creatorcontrib><title>Research on quality traceability of cigarette by combining PDCA quality cycle with information strategy based on fuzzy classification</title><title>Journal of intelligent &amp; fuzzy systems</title><description>For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA quality cycle process, and then constructs IS-PDCA process based on information strategy (IS) to analyze the quality traceability process of cigarette products. The key links are determined according to the traceability process of cigarette logistics, and the traceability resource scheduling function is determined through the product. Then, according to the determined scheduling function and RFID technology, the optimal allocation strategy is constructed to complete the feature extraction and classification identification of cigarette quality labels. For assessing the quality of cigarette evaluation, classification based on fuzzy is proposed and artificial neural network are utilized for calculating the grade of cigarette. Finally, a process of cigarette quality traceability combining PDCA quality cycle and information strategy is formed, and the quality traceability results are constructed by means of QR code technology, so as to realize the process system of cigarette quality traceability and improve the quality control ability of cigarettes. The simulation results show that the cigarette quality traceability method constructed in this paper can obtain the cigarette quality control with good adaptive performance, and the control process shows a strong ability, which improves the feasibility and effectiveness of the cigarette quality traceability.</description><subject>Adaptive control</subject><subject>Artificial neural networks</subject><subject>Cigarettes</subject><subject>Classification</subject><subject>Feature extraction</subject><subject>Logistics</subject><subject>Quality assessment</subject><subject>Quality control</subject><subject>Resource scheduling</subject><issn>1064-1246</issn><issn>1875-8967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9kM1KAzEURoMoWKsrXyDgUkbzP5NlqVYrBUW7HzKZpE2ZzrRJikz3vrdpK67u_eDc78IB4BajB0oofXybTr4yXEjB2BkY4CLnWQr5edqRYBkmTFyCqxBWCOGcEzQAP58mGOX1EnYt3O5U42IPo1faqModQ2ehdgvlTYwGVj3U3bpyrWsX8ONpPPq_0b1uDPx2cQldazu_VtGlypC6oln0sFLB1IcndrffJ7xRITjr9BG7BhdWNcHc_M0hmE-e5-PXbPb-Mh2PZpkmAsesZkgownOjaySJUXnBhOGV5ZKriiLNsBaoqKituZASy7yoKdFM1iJJwJIOwd2pduO77c6EWK66nW_Tx5JwnHiGKUrU_YnSvgvBG1tuvFsr35cYlQfN5UFzedJMfwG5h3Hi</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Wang, Xiaodong</creator><creator>Wang, Xiaoming</creator><creator>Wu, Junfeng</creator><creator>Zheng, Kai</creator><creator>Pang, Yanhong</creator><creator>Gang, Song</creator><general>IOS Press BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20210101</creationdate><title>Research on quality traceability of cigarette by combining PDCA quality cycle with information strategy based on fuzzy classification</title><author>Wang, Xiaodong ; Wang, Xiaoming ; Wu, Junfeng ; Zheng, Kai ; Pang, Yanhong ; Gang, Song</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c261t-d406a257ecd092ea7846e5bf595ab30c41c608b3fd56991978d32c49d6967193</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptive control</topic><topic>Artificial neural networks</topic><topic>Cigarettes</topic><topic>Classification</topic><topic>Feature extraction</topic><topic>Logistics</topic><topic>Quality assessment</topic><topic>Quality control</topic><topic>Resource scheduling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Xiaodong</creatorcontrib><creatorcontrib>Wang, Xiaoming</creatorcontrib><creatorcontrib>Wu, Junfeng</creatorcontrib><creatorcontrib>Zheng, Kai</creatorcontrib><creatorcontrib>Pang, Yanhong</creatorcontrib><creatorcontrib>Gang, Song</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of intelligent &amp; fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Xiaodong</au><au>Wang, Xiaoming</au><au>Wu, Junfeng</au><au>Zheng, Kai</au><au>Pang, Yanhong</au><au>Gang, Song</au><au>Gonzalez Crespo, Ruben</au><au>Sanjuán Martínez, Oscar</au><au>Fenza, Giuseppe</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Research on quality traceability of cigarette by combining PDCA quality cycle with information strategy based on fuzzy classification</atitle><jtitle>Journal of intelligent &amp; fuzzy systems</jtitle><date>2021-01-01</date><risdate>2021</risdate><volume>40</volume><issue>4</issue><spage>8217</spage><epage>8226</epage><pages>8217-8226</pages><issn>1064-1246</issn><eissn>1875-8967</eissn><abstract>For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA quality cycle process, and then constructs IS-PDCA process based on information strategy (IS) to analyze the quality traceability process of cigarette products. The key links are determined according to the traceability process of cigarette logistics, and the traceability resource scheduling function is determined through the product. Then, according to the determined scheduling function and RFID technology, the optimal allocation strategy is constructed to complete the feature extraction and classification identification of cigarette quality labels. For assessing the quality of cigarette evaluation, classification based on fuzzy is proposed and artificial neural network are utilized for calculating the grade of cigarette. Finally, a process of cigarette quality traceability combining PDCA quality cycle and information strategy is formed, and the quality traceability results are constructed by means of QR code technology, so as to realize the process system of cigarette quality traceability and improve the quality control ability of cigarettes. The simulation results show that the cigarette quality traceability method constructed in this paper can obtain the cigarette quality control with good adaptive performance, and the control process shows a strong ability, which improves the feasibility and effectiveness of the cigarette quality traceability.</abstract><cop>Amsterdam</cop><pub>IOS Press BV</pub><doi>10.3233/JIFS-189644</doi><tpages>10</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1064-1246
ispartof Journal of intelligent & fuzzy systems, 2021-01, Vol.40 (4), p.8217-8226
issn 1064-1246
1875-8967
language eng
recordid cdi_proquest_journals_2511974130
source EBSCOhost Business Source Complete
subjects Adaptive control
Artificial neural networks
Cigarettes
Classification
Feature extraction
Logistics
Quality assessment
Quality control
Resource scheduling
title Research on quality traceability of cigarette by combining PDCA quality cycle with information strategy based on fuzzy classification
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T01%3A17%3A42IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Research%20on%20quality%20traceability%20of%20cigarette%20by%20combining%20PDCA%20quality%20cycle%20with%20information%20strategy%20based%20on%20fuzzy%20classification&rft.jtitle=Journal%20of%20intelligent%20&%20fuzzy%20systems&rft.au=Wang,%20Xiaodong&rft.date=2021-01-01&rft.volume=40&rft.issue=4&rft.spage=8217&rft.epage=8226&rft.pages=8217-8226&rft.issn=1064-1246&rft.eissn=1875-8967&rft_id=info:doi/10.3233/JIFS-189644&rft_dat=%3Cproquest_cross%3E2511974130%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2511974130&rft_id=info:pmid/&rfr_iscdi=true