The product quality improvement evaluation based on linguistic information processing
The product continual quality improvement is the effective approach for the enterprise to enhance its product competitiveness. This paper introduces a systematic method based on linguistic information processing to evaluate product quality improvement. Firstly, a quality improvement structure model...
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creator | Zhang Dongling Li Zhao ling Gao Qisheng |
description | The product continual quality improvement is the effective approach for the enterprise to enhance its product competitiveness. This paper introduces a systematic method based on linguistic information processing to evaluate product quality improvement. Firstly, a quality improvement structure model is built, and its evaluation index system is proposed, which is composed of five aspects such as quality stratagem, quality resources, quality capability, and customers' value and quality economics. The weights of evaluation indexes are decided by using the analytic hierarchy process approach. Secondly, the linguistic information from evaluation is transformed into two-tuple linguistic information representation, and the linguistic information of multi-attribute is aggregated to obtain evaluation outcome of the quality improvement at various periods. Thirdly, according recognition degree to the present data from decision-makers, the weights of time are determined with entropy method, and T-TOWA, aggregation operators based on sequential characteristic linguistic information are proposed, and the systematic evaluation result is reached. Finally, an example is shown to illustrate above method. |
doi_str_mv | 10.1109/CCDC.2009.5192519 |
format | Conference Proceeding |
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This paper introduces a systematic method based on linguistic information processing to evaluate product quality improvement. Firstly, a quality improvement structure model is built, and its evaluation index system is proposed, which is composed of five aspects such as quality stratagem, quality resources, quality capability, and customers' value and quality economics. The weights of evaluation indexes are decided by using the analytic hierarchy process approach. Secondly, the linguistic information from evaluation is transformed into two-tuple linguistic information representation, and the linguistic information of multi-attribute is aggregated to obtain evaluation outcome of the quality improvement at various periods. Thirdly, according recognition degree to the present data from decision-makers, the weights of time are determined with entropy method, and T-TOWA, aggregation operators based on sequential characteristic linguistic information are proposed, and the systematic evaluation result is reached. Finally, an example is shown to illustrate above method.</description><identifier>ISSN: 1948-9439</identifier><identifier>ISBN: 9781424427222</identifier><identifier>ISBN: 1424427223</identifier><identifier>EISSN: 1948-9447</identifier><identifier>EISBN: 9781424427239</identifier><identifier>EISBN: 1424427231</identifier><identifier>DOI: 10.1109/CCDC.2009.5192519</identifier><identifier>LCCN: 2008906016</identifier><language>eng</language><publisher>IEEE</publisher><subject>Aggregates ; aggregation operators ; AHP ; Character recognition ; Entropy ; Environmental economics ; group decision ; Information processing ; Information representation ; linguistic information ; linguistic information processing ; Process control ; Q factor ; quality improvement ; Quality management ; systematic evaluation ; Two-tuple ; Uncertainty</subject><ispartof>2009 Chinese Control and Decision Conference, 2009, p.2452-2456</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5192519$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,27923,54918</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5192519$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhang Dongling</creatorcontrib><creatorcontrib>Li Zhao ling</creatorcontrib><creatorcontrib>Gao Qisheng</creatorcontrib><title>The product quality improvement evaluation based on linguistic information processing</title><title>2009 Chinese Control and Decision Conference</title><addtitle>CCDC</addtitle><description>The product continual quality improvement is the effective approach for the enterprise to enhance its product competitiveness. This paper introduces a systematic method based on linguistic information processing to evaluate product quality improvement. Firstly, a quality improvement structure model is built, and its evaluation index system is proposed, which is composed of five aspects such as quality stratagem, quality resources, quality capability, and customers' value and quality economics. The weights of evaluation indexes are decided by using the analytic hierarchy process approach. Secondly, the linguistic information from evaluation is transformed into two-tuple linguistic information representation, and the linguistic information of multi-attribute is aggregated to obtain evaluation outcome of the quality improvement at various periods. Thirdly, according recognition degree to the present data from decision-makers, the weights of time are determined with entropy method, and T-TOWA, aggregation operators based on sequential characteristic linguistic information are proposed, and the systematic evaluation result is reached. Finally, an example is shown to illustrate above method.</description><subject>Aggregates</subject><subject>aggregation operators</subject><subject>AHP</subject><subject>Character recognition</subject><subject>Entropy</subject><subject>Environmental economics</subject><subject>group decision</subject><subject>Information processing</subject><subject>Information representation</subject><subject>linguistic information</subject><subject>linguistic information processing</subject><subject>Process control</subject><subject>Q factor</subject><subject>quality improvement</subject><subject>Quality management</subject><subject>systematic evaluation</subject><subject>Two-tuple</subject><subject>Uncertainty</subject><issn>1948-9439</issn><issn>1948-9447</issn><isbn>9781424427222</isbn><isbn>1424427223</isbn><isbn>9781424427239</isbn><isbn>1424427231</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkNtqwzAMhr1DYV2XBxi78Qskk2wnsS9HdoTCbrLr4iTK5pGkXZwU-vYztAwmEPrRh34kMXaLkCCCuS-KxyIRACZJ0YiQZywyuUYllBK5kOacLdEoHRul8ot_TIjLPybNgl0HG20gA8yuWOT9N4RQqUwlLtlH-UV8N26buZ74z2w7Nx2460NnTz0NE6e97WY7ue3AK-up4UF0bvicnZ9czd3Qbsf-yMNQTd4HeMMWre08Rae6YuXzU1m8xuv3l7fiYR07zNMpRluFVZrcylppBQ2EKxqwkowWugLKwFCOldJSQCMrSUIZEKizVCpsrVyxu6OtI6LNbnS9HQ-b08PkL5ySWII</recordid><startdate>200906</startdate><enddate>200906</enddate><creator>Zhang Dongling</creator><creator>Li Zhao ling</creator><creator>Gao Qisheng</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200906</creationdate><title>The product quality improvement evaluation based on linguistic information processing</title><author>Zhang Dongling ; Li Zhao ling ; Gao Qisheng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-1ab000d7a3c4840d0978d0a3e9828b0e609e71b48320d3b3e249021865341fa3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Aggregates</topic><topic>aggregation operators</topic><topic>AHP</topic><topic>Character recognition</topic><topic>Entropy</topic><topic>Environmental economics</topic><topic>group decision</topic><topic>Information processing</topic><topic>Information representation</topic><topic>linguistic information</topic><topic>linguistic information processing</topic><topic>Process control</topic><topic>Q factor</topic><topic>quality improvement</topic><topic>Quality management</topic><topic>systematic evaluation</topic><topic>Two-tuple</topic><topic>Uncertainty</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhang Dongling</creatorcontrib><creatorcontrib>Li Zhao ling</creatorcontrib><creatorcontrib>Gao Qisheng</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhang Dongling</au><au>Li Zhao ling</au><au>Gao Qisheng</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>The product quality improvement evaluation based on linguistic information processing</atitle><btitle>2009 Chinese Control and Decision Conference</btitle><stitle>CCDC</stitle><date>2009-06</date><risdate>2009</risdate><spage>2452</spage><epage>2456</epage><pages>2452-2456</pages><issn>1948-9439</issn><eissn>1948-9447</eissn><isbn>9781424427222</isbn><isbn>1424427223</isbn><eisbn>9781424427239</eisbn><eisbn>1424427231</eisbn><abstract>The product continual quality improvement is the effective approach for the enterprise to enhance its product competitiveness. This paper introduces a systematic method based on linguistic information processing to evaluate product quality improvement. Firstly, a quality improvement structure model is built, and its evaluation index system is proposed, which is composed of five aspects such as quality stratagem, quality resources, quality capability, and customers' value and quality economics. The weights of evaluation indexes are decided by using the analytic hierarchy process approach. Secondly, the linguistic information from evaluation is transformed into two-tuple linguistic information representation, and the linguistic information of multi-attribute is aggregated to obtain evaluation outcome of the quality improvement at various periods. Thirdly, according recognition degree to the present data from decision-makers, the weights of time are determined with entropy method, and T-TOWA, aggregation operators based on sequential characteristic linguistic information are proposed, and the systematic evaluation result is reached. Finally, an example is shown to illustrate above method.</abstract><pub>IEEE</pub><doi>10.1109/CCDC.2009.5192519</doi><tpages>5</tpages></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Aggregates aggregation operators AHP Character recognition Entropy Environmental economics group decision Information processing Information representation linguistic information linguistic information processing Process control Q factor quality improvement Quality management systematic evaluation Two-tuple Uncertainty |
title | The product quality improvement evaluation based on linguistic information processing |
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