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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Amirkabir University of Technology</PublisherName>
				<JournalTitle>Amirkabir Journal of Civil Engineering</JournalTitle>
				<Issn>2588-297X</Issn>
				<Volume>51</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2019</Year>
					<Month>10</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Statistical Quality Control Based on the Process Capability Index and Control Charts  with Fuzzy Approach (Case Study: Water and Wastewater Company of West Azerbaijan Province)</ArticleTitle>
<VernacularTitle>Statistical Quality Control Based on the Process Capability Index and Control Charts  with Fuzzy Approach (Case Study: Water and Wastewater Company of West Azerbaijan Province)</VernacularTitle>
			<FirstPage>699</FirstPage>
			<LastPage>712</LastPage>
			<ELocationID EIdType="pii">2915</ELocationID>
			
<ELocationID EIdType="doi">10.22060/ceej.2018.13897.5504</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Khosro</FirstName>
					<LastName>Alinejad</LastName>
<Affiliation>MSc student, Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Rahim</FirstName>
					<LastName>Dabbagh</LastName>
<Affiliation>Urmia University of technology faculty member</Affiliation>
<Identifier Source="ORCID">0000-0003-2888-3928</Identifier>

</Author>
<Author>
					<FirstName>Akbar</FirstName>
					<LastName>Shirzad</LastName>
<Affiliation>Assistant Professor, Faculty of Civil Engineering, Urmia University of Technology</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2018</Year>
					<Month>01</Month>
					<Day>01</Day>
				</PubDate>
			</History>
		<Abstract>Statistical quality control is a method for monitoring the process to identify the underlying causes of changes and carrying out corrective actions. Process and capability control charts are two important applied tools for statistical quality control. In many actual systems in which accurate and certain information is not always available and the information is vague and fuzzy, fuzzy based methods can survey production process more precisely using appropriate linguistic terms and fuzzy numbers. In this study, fuzzy control charts were developed using fuzzy rules, and then the fuzzy actual capability index of process (Cpm) was investigated in order to evaluate the precision, accuracy and performance of production process in the fuzzy state. The results of the studies performed on the quality of water flowmeters in the urban water and wastewater company of West Azerbaijan province showed that using fuzzy rules provides more decision-making options to decision- makers compared to the crisp data and provided more precise division about the product quality. Also, the fuzzy actual capability index of process could propose a more precise analysis of the process taking into account the average, target value and process variance, simultaneously. The values of the fuzzy actual capability index of process in the studied case were less than one, showing that the conditions of the production process are unfavorable.</Abstract>
			<OtherAbstract Language="FA">Statistical quality control is a method for monitoring the process to identify the underlying causes of changes and carrying out corrective actions. Process and capability control charts are two important applied tools for statistical quality control. In many actual systems in which accurate and certain information is not always available and the information is vague and fuzzy, fuzzy based methods can survey production process more precisely using appropriate linguistic terms and fuzzy numbers. In this study, fuzzy control charts were developed using fuzzy rules, and then the fuzzy actual capability index of process (Cpm) was investigated in order to evaluate the precision, accuracy and performance of production process in the fuzzy state. The results of the studies performed on the quality of water flowmeters in the urban water and wastewater company of West Azerbaijan province showed that using fuzzy rules provides more decision-making options to decision- makers compared to the crisp data and provided more precise division about the product quality. Also, the fuzzy actual capability index of process could propose a more precise analysis of the process taking into account the average, target value and process variance, simultaneously. The values of the fuzzy actual capability index of process in the studied case were less than one, showing that the conditions of the production process are unfavorable.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">quality control</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">control charts</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Process Actual Capability</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fuzzy Logic</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Water Flowmeters</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ceej.aut.ac.ir/article_2915_e924517087669cf201ea91bd737a4ff4.pdf</ArchiveCopySource>
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