Optimizing production and maintenance for the service-oriented manufacturing supply chain
Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to max...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jiang, Zhong-Zhong [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
|---|
| Schlagwörter: |
Service-oriented manufacturing |
|---|
| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2020 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Annals of operations research - Springer US, 1984, 316(2020), 1 vom: 19. Aug., Seite 33-58 |
|---|---|
| Übergeordnetes Werk: |
volume:316 ; year:2020 ; number:1 ; day:19 ; month:08 ; pages:33-58 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10479-020-03758-7 |
|---|
| Katalog-ID: |
OLC2079366874 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | OLC2079366874 | ||
| 003 | DE-627 | ||
| 005 | 20230506055047.0 | ||
| 007 | tu | ||
| 008 | 221220s2020 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s10479-020-03758-7 |2 doi | |
| 035 | |a (DE-627)OLC2079366874 | ||
| 035 | |a (DE-He213)s10479-020-03758-7-p | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 004 |q VZ |
| 084 | |a 3,2 |2 ssgn | ||
| 100 | 1 | |a Jiang, Zhong-Zhong |e verfasserin |0 (orcid)0000-0003-0616-9416 |4 aut | |
| 245 | 1 | 0 | |a Optimizing production and maintenance for the service-oriented manufacturing supply chain |
| 264 | 1 | |c 2020 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 500 | |a © Springer Science+Business Media, LLC, part of Springer Nature 2020 | ||
| 520 | |a Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. | ||
| 650 | 4 | |a Service-oriented manufacturing | |
| 650 | 4 | |a Equipment quality | |
| 650 | 4 | |a Preventive and corrective maintenance | |
| 650 | 4 | |a Learning behavior | |
| 650 | 4 | |a Supply chain optimization and coordination | |
| 700 | 1 | |a He, Na |4 aut | |
| 700 | 1 | |a Qin, Xuwei |4 aut | |
| 700 | 1 | |a Sun, Minghe |4 aut | |
| 700 | 1 | |a Wang, Pengfei |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Annals of operations research |d Springer US, 1984 |g 316(2020), 1 vom: 19. Aug., Seite 33-58 |w (DE-627)12964370X |w (DE-600)252629-3 |w (DE-576)018141862 |x 0254-5330 |
| 773 | 1 | 8 | |g volume:316 |g year:2020 |g number:1 |g day:19 |g month:08 |g pages:33-58 |
| 856 | 4 | 1 | |u https://doi.org/10.1007/s10479-020-03758-7 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-WIW | ||
| 912 | |a SSG-OLC-MAT | ||
| 951 | |a AR | ||
| 952 | |d 316 |j 2020 |e 1 |b 19 |c 08 |h 33-58 | ||
| author_variant |
z z j zzj n h nh x q xq m s ms p w pw |
|---|---|
| matchkey_str |
article:02545330:2020----::piiigrdcinnmitnneoteevcoinem |
| hierarchy_sort_str |
2020 |
| publishDate |
2020 |
| allfields |
10.1007/s10479-020-03758-7 doi (DE-627)OLC2079366874 (DE-He213)s10479-020-03758-7-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Jiang, Zhong-Zhong verfasserin (orcid)0000-0003-0616-9416 aut Optimizing production and maintenance for the service-oriented manufacturing supply chain 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. Service-oriented manufacturing Equipment quality Preventive and corrective maintenance Learning behavior Supply chain optimization and coordination He, Na aut Qin, Xuwei aut Sun, Minghe aut Wang, Pengfei aut Enthalten in Annals of operations research Springer US, 1984 316(2020), 1 vom: 19. Aug., Seite 33-58 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:316 year:2020 number:1 day:19 month:08 pages:33-58 https://doi.org/10.1007/s10479-020-03758-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 316 2020 1 19 08 33-58 |
| spelling |
10.1007/s10479-020-03758-7 doi (DE-627)OLC2079366874 (DE-He213)s10479-020-03758-7-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Jiang, Zhong-Zhong verfasserin (orcid)0000-0003-0616-9416 aut Optimizing production and maintenance for the service-oriented manufacturing supply chain 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. Service-oriented manufacturing Equipment quality Preventive and corrective maintenance Learning behavior Supply chain optimization and coordination He, Na aut Qin, Xuwei aut Sun, Minghe aut Wang, Pengfei aut Enthalten in Annals of operations research Springer US, 1984 316(2020), 1 vom: 19. Aug., Seite 33-58 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:316 year:2020 number:1 day:19 month:08 pages:33-58 https://doi.org/10.1007/s10479-020-03758-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 316 2020 1 19 08 33-58 |
| allfields_unstemmed |
10.1007/s10479-020-03758-7 doi (DE-627)OLC2079366874 (DE-He213)s10479-020-03758-7-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Jiang, Zhong-Zhong verfasserin (orcid)0000-0003-0616-9416 aut Optimizing production and maintenance for the service-oriented manufacturing supply chain 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. Service-oriented manufacturing Equipment quality Preventive and corrective maintenance Learning behavior Supply chain optimization and coordination He, Na aut Qin, Xuwei aut Sun, Minghe aut Wang, Pengfei aut Enthalten in Annals of operations research Springer US, 1984 316(2020), 1 vom: 19. Aug., Seite 33-58 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:316 year:2020 number:1 day:19 month:08 pages:33-58 https://doi.org/10.1007/s10479-020-03758-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 316 2020 1 19 08 33-58 |
| allfieldsGer |
10.1007/s10479-020-03758-7 doi (DE-627)OLC2079366874 (DE-He213)s10479-020-03758-7-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Jiang, Zhong-Zhong verfasserin (orcid)0000-0003-0616-9416 aut Optimizing production and maintenance for the service-oriented manufacturing supply chain 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. Service-oriented manufacturing Equipment quality Preventive and corrective maintenance Learning behavior Supply chain optimization and coordination He, Na aut Qin, Xuwei aut Sun, Minghe aut Wang, Pengfei aut Enthalten in Annals of operations research Springer US, 1984 316(2020), 1 vom: 19. Aug., Seite 33-58 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:316 year:2020 number:1 day:19 month:08 pages:33-58 https://doi.org/10.1007/s10479-020-03758-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 316 2020 1 19 08 33-58 |
| allfieldsSound |
10.1007/s10479-020-03758-7 doi (DE-627)OLC2079366874 (DE-He213)s10479-020-03758-7-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Jiang, Zhong-Zhong verfasserin (orcid)0000-0003-0616-9416 aut Optimizing production and maintenance for the service-oriented manufacturing supply chain 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. Service-oriented manufacturing Equipment quality Preventive and corrective maintenance Learning behavior Supply chain optimization and coordination He, Na aut Qin, Xuwei aut Sun, Minghe aut Wang, Pengfei aut Enthalten in Annals of operations research Springer US, 1984 316(2020), 1 vom: 19. Aug., Seite 33-58 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:316 year:2020 number:1 day:19 month:08 pages:33-58 https://doi.org/10.1007/s10479-020-03758-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 316 2020 1 19 08 33-58 |
| language |
English |
| source |
Enthalten in Annals of operations research 316(2020), 1 vom: 19. Aug., Seite 33-58 volume:316 year:2020 number:1 day:19 month:08 pages:33-58 |
| sourceStr |
Enthalten in Annals of operations research 316(2020), 1 vom: 19. Aug., Seite 33-58 volume:316 year:2020 number:1 day:19 month:08 pages:33-58 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Service-oriented manufacturing Equipment quality Preventive and corrective maintenance Learning behavior Supply chain optimization and coordination |
| dewey-raw |
004 |
| isfreeaccess_bool |
false |
| container_title |
Annals of operations research |
| authorswithroles_txt_mv |
Jiang, Zhong-Zhong @@aut@@ He, Na @@aut@@ Qin, Xuwei @@aut@@ Sun, Minghe @@aut@@ Wang, Pengfei @@aut@@ |
| publishDateDaySort_date |
2020-08-19T00:00:00Z |
| hierarchy_top_id |
12964370X |
| dewey-sort |
14 |
| id |
OLC2079366874 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2079366874</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230506055047.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">221220s2020 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10479-020-03758-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2079366874</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10479-020-03758-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">3,2</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jiang, Zhong-Zhong</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-0616-9416</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Optimizing production and maintenance for the service-oriented manufacturing supply chain</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2020</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Service-oriented manufacturing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Equipment quality</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Preventive and corrective maintenance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Learning behavior</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Supply chain optimization and coordination</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Na</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qin, Xuwei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sun, Minghe</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Pengfei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Annals of operations research</subfield><subfield code="d">Springer US, 1984</subfield><subfield code="g">316(2020), 1 vom: 19. Aug., Seite 33-58</subfield><subfield code="w">(DE-627)12964370X</subfield><subfield code="w">(DE-600)252629-3</subfield><subfield code="w">(DE-576)018141862</subfield><subfield code="x">0254-5330</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:316</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:1</subfield><subfield code="g">day:19</subfield><subfield code="g">month:08</subfield><subfield code="g">pages:33-58</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10479-020-03758-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">316</subfield><subfield code="j">2020</subfield><subfield code="e">1</subfield><subfield code="b">19</subfield><subfield code="c">08</subfield><subfield code="h">33-58</subfield></datafield></record></collection>
|
| author |
Jiang, Zhong-Zhong |
| spellingShingle |
Jiang, Zhong-Zhong ddc 004 ssgn 3,2 misc Service-oriented manufacturing misc Equipment quality misc Preventive and corrective maintenance misc Learning behavior misc Supply chain optimization and coordination Optimizing production and maintenance for the service-oriented manufacturing supply chain |
| authorStr |
Jiang, Zhong-Zhong |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)12964370X |
| format |
Article |
| dewey-ones |
004 - Data processing & computer science |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0254-5330 |
| topic_title |
004 VZ 3,2 ssgn Optimizing production and maintenance for the service-oriented manufacturing supply chain Service-oriented manufacturing Equipment quality Preventive and corrective maintenance Learning behavior Supply chain optimization and coordination |
| topic |
ddc 004 ssgn 3,2 misc Service-oriented manufacturing misc Equipment quality misc Preventive and corrective maintenance misc Learning behavior misc Supply chain optimization and coordination |
| topic_unstemmed |
ddc 004 ssgn 3,2 misc Service-oriented manufacturing misc Equipment quality misc Preventive and corrective maintenance misc Learning behavior misc Supply chain optimization and coordination |
| topic_browse |
ddc 004 ssgn 3,2 misc Service-oriented manufacturing misc Equipment quality misc Preventive and corrective maintenance misc Learning behavior misc Supply chain optimization and coordination |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
Annals of operations research |
| hierarchy_parent_id |
12964370X |
| dewey-tens |
000 - Computer science, knowledge & systems |
| hierarchy_top_title |
Annals of operations research |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 |
| title |
Optimizing production and maintenance for the service-oriented manufacturing supply chain |
| ctrlnum |
(DE-627)OLC2079366874 (DE-He213)s10479-020-03758-7-p |
| title_full |
Optimizing production and maintenance for the service-oriented manufacturing supply chain |
| author_sort |
Jiang, Zhong-Zhong |
| journal |
Annals of operations research |
| journalStr |
Annals of operations research |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
000 - Computer science, information & general works |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
txt |
| container_start_page |
33 |
| author_browse |
Jiang, Zhong-Zhong He, Na Qin, Xuwei Sun, Minghe Wang, Pengfei |
| container_volume |
316 |
| class |
004 VZ 3,2 ssgn |
| format_se |
Aufsätze |
| author-letter |
Jiang, Zhong-Zhong |
| doi_str_mv |
10.1007/s10479-020-03758-7 |
| normlink |
(ORCID)0000-0003-0616-9416 |
| normlink_prefix_str_mv |
(orcid)0000-0003-0616-9416 |
| dewey-full |
004 |
| title_sort |
optimizing production and maintenance for the service-oriented manufacturing supply chain |
| title_auth |
Optimizing production and maintenance for the service-oriented manufacturing supply chain |
| abstract |
Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
| abstractGer |
Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
| abstract_unstemmed |
Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT |
| container_issue |
1 |
| title_short |
Optimizing production and maintenance for the service-oriented manufacturing supply chain |
| url |
https://doi.org/10.1007/s10479-020-03758-7 |
| remote_bool |
false |
| author2 |
He, Na Qin, Xuwei Sun, Minghe Wang, Pengfei |
| author2Str |
He, Na Qin, Xuwei Sun, Minghe Wang, Pengfei |
| ppnlink |
12964370X |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s10479-020-03758-7 |
| up_date |
2024-07-04T00:39:05.064Z |
| _version_ |
1803606866071126016 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2079366874</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230506055047.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">221220s2020 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10479-020-03758-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2079366874</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10479-020-03758-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">3,2</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jiang, Zhong-Zhong</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-0616-9416</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Optimizing production and maintenance for the service-oriented manufacturing supply chain</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2020</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This work investigates a service-oriented manufacturing supply chain in which a manufacturer and an operator make decisions about equipment quality and maintenance service. Both the manufacturer and the operator have to make tradeoffs between equipment quality and maintenance service to maximize their own profit, which can lead to supply chain conflict. Decision models under decentralized decisions are formulated first for the manufacturer and the operator to make their respective independent optimal decisions, and a decision model under centralized decisions is formulated to obtain optimal decisions for the supply chain. The results show that channel coordination is not achievable and an agreement cannot be reached with decentralized decisions. To address this issue, two, i.e., a cost-sharing and a performance-based, strategies are introduced to coordinate the supply chain. The results reveal that the manufacturer and the operator are motivated to find the optimal decisions to maximize the profit of the supply chain when the subsidy rate or the penalty rate is equal to the profit margin of the operator. The models and the coordination strategies are extended to the situation considering the learning behavior of the manufacturer. The results show that the learning behavior impacts the profit of the supply chain with coordination and the preferences of the coordination strategy in the supply chain.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Service-oriented manufacturing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Equipment quality</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Preventive and corrective maintenance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Learning behavior</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Supply chain optimization and coordination</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Na</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qin, Xuwei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sun, Minghe</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Pengfei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Annals of operations research</subfield><subfield code="d">Springer US, 1984</subfield><subfield code="g">316(2020), 1 vom: 19. Aug., Seite 33-58</subfield><subfield code="w">(DE-627)12964370X</subfield><subfield code="w">(DE-600)252629-3</subfield><subfield code="w">(DE-576)018141862</subfield><subfield code="x">0254-5330</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:316</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:1</subfield><subfield code="g">day:19</subfield><subfield code="g">month:08</subfield><subfield code="g">pages:33-58</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10479-020-03758-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">316</subfield><subfield code="j">2020</subfield><subfield code="e">1</subfield><subfield code="b">19</subfield><subfield code="c">08</subfield><subfield code="h">33-58</subfield></datafield></record></collection>
|
| score |
7.4004498 |