Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy

The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However...
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Gespeichert in:

Autor*in:	Yaping Li [verfasserIn] Zhen Chen [verfasserIn] Ershun Pan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Übergeordnetes Werk:	In: Mathematical Problems in Engineering - Hindawi Limited, 2002, (2018)
Übergeordnetes Werk:	year:2018

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1155/2018/9246372

Katalog-ID:	DOAJ051363607

Internformat


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allfields	10.1155/2018/9246372 doi (DE-627)DOAJ051363607 (DE-599)DOAJ8979f79587df439786d80a29685fdd79 DE-627 ger DE-627 rakwb eng TA1-2040 QA1-939 Yaping Li verfasserin aut Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters. Engineering (General). Civil engineering (General) Mathematics Zhen Chen verfasserin aut Ershun Pan verfasserin aut In Mathematical Problems in Engineering Hindawi Limited, 2002 (2018) (DE-627)320519937 (DE-600)2014442-8 1024123X nnns year:2018 https://doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/article/8979f79587df439786d80a29685fdd79 kostenfrei http://dx.doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/toc/1024-123X Journal toc kostenfrei https://doaj.org/toc/1563-5147 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018
spelling	10.1155/2018/9246372 doi (DE-627)DOAJ051363607 (DE-599)DOAJ8979f79587df439786d80a29685fdd79 DE-627 ger DE-627 rakwb eng TA1-2040 QA1-939 Yaping Li verfasserin aut Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters. Engineering (General). Civil engineering (General) Mathematics Zhen Chen verfasserin aut Ershun Pan verfasserin aut In Mathematical Problems in Engineering Hindawi Limited, 2002 (2018) (DE-627)320519937 (DE-600)2014442-8 1024123X nnns year:2018 https://doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/article/8979f79587df439786d80a29685fdd79 kostenfrei http://dx.doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/toc/1024-123X Journal toc kostenfrei https://doaj.org/toc/1563-5147 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018
allfields_unstemmed	10.1155/2018/9246372 doi (DE-627)DOAJ051363607 (DE-599)DOAJ8979f79587df439786d80a29685fdd79 DE-627 ger DE-627 rakwb eng TA1-2040 QA1-939 Yaping Li verfasserin aut Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters. Engineering (General). Civil engineering (General) Mathematics Zhen Chen verfasserin aut Ershun Pan verfasserin aut In Mathematical Problems in Engineering Hindawi Limited, 2002 (2018) (DE-627)320519937 (DE-600)2014442-8 1024123X nnns year:2018 https://doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/article/8979f79587df439786d80a29685fdd79 kostenfrei http://dx.doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/toc/1024-123X Journal toc kostenfrei https://doaj.org/toc/1563-5147 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018
allfieldsGer	10.1155/2018/9246372 doi (DE-627)DOAJ051363607 (DE-599)DOAJ8979f79587df439786d80a29685fdd79 DE-627 ger DE-627 rakwb eng TA1-2040 QA1-939 Yaping Li verfasserin aut Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters. Engineering (General). Civil engineering (General) Mathematics Zhen Chen verfasserin aut Ershun Pan verfasserin aut In Mathematical Problems in Engineering Hindawi Limited, 2002 (2018) (DE-627)320519937 (DE-600)2014442-8 1024123X nnns year:2018 https://doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/article/8979f79587df439786d80a29685fdd79 kostenfrei http://dx.doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/toc/1024-123X Journal toc kostenfrei https://doaj.org/toc/1563-5147 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018
allfieldsSound	10.1155/2018/9246372 doi (DE-627)DOAJ051363607 (DE-599)DOAJ8979f79587df439786d80a29685fdd79 DE-627 ger DE-627 rakwb eng TA1-2040 QA1-939 Yaping Li verfasserin aut Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters. Engineering (General). Civil engineering (General) Mathematics Zhen Chen verfasserin aut Ershun Pan verfasserin aut In Mathematical Problems in Engineering Hindawi Limited, 2002 (2018) (DE-627)320519937 (DE-600)2014442-8 1024123X nnns year:2018 https://doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/article/8979f79587df439786d80a29685fdd79 kostenfrei http://dx.doi.org/10.1155/2018/9246372 kostenfrei https://doaj.org/toc/1024-123X Journal toc kostenfrei https://doaj.org/toc/1563-5147 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2018
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authorswithroles_txt_mv	Yaping Li @@aut@@ Zhen Chen @@aut@@ Ershun Pan @@aut@@
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author	Yaping Li
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title	Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy
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title_full	Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy
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title_sort	joint economic design of cusum control chart and age-based imperfect preventive maintenance policy
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title_auth	Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy
abstract	The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters.
abstractGer	The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters.
abstract_unstemmed	The close relationship between statistical process control and maintenance has attracted lots of researchers to focus on the jointly economic design of control chart (a main tool of statistical process control) and preventive maintenance policy, and much progress has been made in this field. However, in the existing literatures, the X- chart is used most, and other charts are rarely considered. In this paper, the economic design of CUSUM chart and age-based imperfect preventive maintenance policy is presented. The process is considered as a multiphase system, and a recursive algorithm is used to model each phase. Besides, a sampling policy under the non-Markovian deterioration assumption is employed, and an age-based imperfect preventive maintenance policy is used. An optimization model with the objective of minimizing the expected cost per unit time is constructed to obtain the near-optimal solution of decision variables: the age of the machine for maintenance, the number of age-based maintenances, sample size, sampling intervals, and the decision interval coefficient and reference value coefficient of CUSUM chart. The solution procedure of the model is provided. Also, sensitivity analysis is performed on the decision variables for each of the various parameters.
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title_short	Joint Economic Design of CUSUM Control Chart and Age-Based Imperfect Preventive Maintenance Policy
url	https://doi.org/10.1155/2018/9246372 https://doaj.org/article/8979f79587df439786d80a29685fdd79 http://dx.doi.org/10.1155/2018/9246372 https://doaj.org/toc/1024-123X https://doaj.org/toc/1563-5147
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