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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Morvarid Derakhshan Andisheh</PublisherName>
				<JournalTitle>Journal of Quality Engineering and Management</JournalTitle>
				<Issn>2322-1305</Issn>
				<Volume>6</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>01</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Development of a piecemeal regression-based approach for monitoring multiple linear profiles with phase interactions</ArticleTitle>
<VernacularTitle>Development of a piecemeal regression-based approach for monitoring multiple linear profiles with phase interactions</VernacularTitle>
			<FirstPage>237</FirstPage>
			<LastPage>249</LastPage>
			<ELocationID EIdType="pii">66179</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Majid</FirstName>
					<LastName>Jalili</LastName>
<Affiliation>PhD Student, Department of Industrial Engineering, Materials and Energy Research Institute, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mahdi</FirstName>
					<LastName>Bashiri</LastName>
<Affiliation>Associate Professor, Shahed University, Faculty of Engineering, Department of Industrial Engineering</Affiliation>

</Author>
<Author>
					<FirstName>Manouchehr</FirstName>
					<LastName>Manteghi</LastName>
<Affiliation>Associate Professor, Malek Ashtar University, Faculty of Industrial Engineering</Affiliation>

</Author>
<Author>
					<FirstName>Ali Asghar</FirstName>
					<LastName>Tofigh</LastName>
<Affiliation>Associate Professor, Amirkabir University of Technology, Faculty of Industrial Engineering</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2018</Year>
					<Month>07</Month>
					<Day>21</Day>
				</PubDate>
			</History>
		<Abstract>In many statistical process control applications, the relationship between a response variable and one or more control variables is evaluated by a function called a profile. Profiles are divided into different types according to the nature of the response variable, such as linear and nonlinear profiles. In this research, a new control diagram based on the generalized linear test approach and fractional regression is presented to monitor multiple linear profiles with interactions in phase 2. The simulation results of the proposed control diagram show its much better performance than the control diagram based on the least squares error method.</Abstract>
			<OtherAbstract Language="FA">In many statistical process control applications, the relationship between a response variable and one or more control variables is evaluated by a function called a profile. Profiles are divided into different types according to the nature of the response variable, such as linear and nonlinear profiles. In this research, a new control diagram based on the generalized linear test approach and fractional regression is presented to monitor multiple linear profiles with interactions in phase 2. The simulation results of the proposed control diagram show its much better performance than the control diagram based on the least squares error method.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Multiple linear profiles</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fragmentary regression model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Average trail length</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">phase 2</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.pqprc.ir/article_66179_4b5355f08f0d25f1d2749af98089dae4.pdf</ArchiveCopySource>
</Article>
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