A predictive maintenance cost model for CNC SMEs in the era of industry 4.0
Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value anal...
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| Autor*in: |
Adu-Amankwa, Kwaku [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Ltd., part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - Springer London, 1985, 104(2019), 9-12 vom: 13. Juli, Seite 3567-3587 |
|---|---|
| Übergeordnetes Werk: |
volume:104 ; year:2019 ; number:9-12 ; day:13 ; month:07 ; pages:3567-3587 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00170-019-04094-2 |
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OLC2026144524 |
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| 520 | |a Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value analysis or cost model specifically for small-medium enterprises (SMEs) operating computer numerically controlled (CNC) MTs. This paper’s novelty is addressing SMEs’ minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost-effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804 to £48,585 over a range of 1–50 CNC MTs maintained on a distributed numerically controlled (DNC) network. It affirms PdM’s tangible value creation for SME CNC machine shops with predicted positive impacts on their MT cost and performance drivers. These exploratory research findings corroborate SMEs pooling together to optimise their CNC MT maintenance cost through the recommended system architecture. Finally, it introduces opportunities for further PdM research taking into account SMEs’ perspective. The paper’s industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT’s overall life cycle costs. | ||
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10.1007/s00170-019-04094-2 doi (DE-627)OLC2026144524 (DE-He213)s00170-019-04094-2-p DE-627 ger DE-627 rakwb eng 670 VZ Adu-Amankwa, Kwaku verfasserin aut A predictive maintenance cost model for CNC SMEs in the era of industry 4.0 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value analysis or cost model specifically for small-medium enterprises (SMEs) operating computer numerically controlled (CNC) MTs. This paper’s novelty is addressing SMEs’ minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost-effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804 to £48,585 over a range of 1–50 CNC MTs maintained on a distributed numerically controlled (DNC) network. It affirms PdM’s tangible value creation for SME CNC machine shops with predicted positive impacts on their MT cost and performance drivers. These exploratory research findings corroborate SMEs pooling together to optimise their CNC MT maintenance cost through the recommended system architecture. Finally, it introduces opportunities for further PdM research taking into account SMEs’ perspective. The paper’s industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT’s overall life cycle costs. Industry 4.0 Predictive maintenance Machine maintenance cost Machine tool Attia, Ashraf K.A. aut Janardhanan, Mukund Nilakantan aut Patel, Imran aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 104(2019), 9-12 vom: 13. Juli, Seite 3567-3587 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:104 year:2019 number:9-12 day:13 month:07 pages:3567-3587 https://doi.org/10.1007/s00170-019-04094-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 104 2019 9-12 13 07 3567-3587 |
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10.1007/s00170-019-04094-2 doi (DE-627)OLC2026144524 (DE-He213)s00170-019-04094-2-p DE-627 ger DE-627 rakwb eng 670 VZ Adu-Amankwa, Kwaku verfasserin aut A predictive maintenance cost model for CNC SMEs in the era of industry 4.0 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value analysis or cost model specifically for small-medium enterprises (SMEs) operating computer numerically controlled (CNC) MTs. This paper’s novelty is addressing SMEs’ minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost-effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804 to £48,585 over a range of 1–50 CNC MTs maintained on a distributed numerically controlled (DNC) network. It affirms PdM’s tangible value creation for SME CNC machine shops with predicted positive impacts on their MT cost and performance drivers. These exploratory research findings corroborate SMEs pooling together to optimise their CNC MT maintenance cost through the recommended system architecture. Finally, it introduces opportunities for further PdM research taking into account SMEs’ perspective. The paper’s industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT’s overall life cycle costs. Industry 4.0 Predictive maintenance Machine maintenance cost Machine tool Attia, Ashraf K.A. aut Janardhanan, Mukund Nilakantan aut Patel, Imran aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 104(2019), 9-12 vom: 13. Juli, Seite 3567-3587 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:104 year:2019 number:9-12 day:13 month:07 pages:3567-3587 https://doi.org/10.1007/s00170-019-04094-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 104 2019 9-12 13 07 3567-3587 |
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10.1007/s00170-019-04094-2 doi (DE-627)OLC2026144524 (DE-He213)s00170-019-04094-2-p DE-627 ger DE-627 rakwb eng 670 VZ Adu-Amankwa, Kwaku verfasserin aut A predictive maintenance cost model for CNC SMEs in the era of industry 4.0 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value analysis or cost model specifically for small-medium enterprises (SMEs) operating computer numerically controlled (CNC) MTs. This paper’s novelty is addressing SMEs’ minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost-effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804 to £48,585 over a range of 1–50 CNC MTs maintained on a distributed numerically controlled (DNC) network. It affirms PdM’s tangible value creation for SME CNC machine shops with predicted positive impacts on their MT cost and performance drivers. These exploratory research findings corroborate SMEs pooling together to optimise their CNC MT maintenance cost through the recommended system architecture. Finally, it introduces opportunities for further PdM research taking into account SMEs’ perspective. The paper’s industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT’s overall life cycle costs. Industry 4.0 Predictive maintenance Machine maintenance cost Machine tool Attia, Ashraf K.A. aut Janardhanan, Mukund Nilakantan aut Patel, Imran aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 104(2019), 9-12 vom: 13. Juli, Seite 3567-3587 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:104 year:2019 number:9-12 day:13 month:07 pages:3567-3587 https://doi.org/10.1007/s00170-019-04094-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 104 2019 9-12 13 07 3567-3587 |
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A predictive maintenance cost model for CNC SMEs in the era of industry 4.0 |
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A predictive maintenance cost model for CNC SMEs in the era of industry 4.0 |
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Adu-Amankwa, Kwaku |
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Adu-Amankwa, Kwaku Attia, Ashraf K.A. Janardhanan, Mukund Nilakantan Patel, Imran |
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a predictive maintenance cost model for cnc smes in the era of industry 4.0 |
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A predictive maintenance cost model for CNC SMEs in the era of industry 4.0 |
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Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value analysis or cost model specifically for small-medium enterprises (SMEs) operating computer numerically controlled (CNC) MTs. This paper’s novelty is addressing SMEs’ minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost-effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804 to £48,585 over a range of 1–50 CNC MTs maintained on a distributed numerically controlled (DNC) network. It affirms PdM’s tangible value creation for SME CNC machine shops with predicted positive impacts on their MT cost and performance drivers. These exploratory research findings corroborate SMEs pooling together to optimise their CNC MT maintenance cost through the recommended system architecture. Finally, it introduces opportunities for further PdM research taking into account SMEs’ perspective. The paper’s industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT’s overall life cycle costs. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value analysis or cost model specifically for small-medium enterprises (SMEs) operating computer numerically controlled (CNC) MTs. This paper’s novelty is addressing SMEs’ minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost-effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804 to £48,585 over a range of 1–50 CNC MTs maintained on a distributed numerically controlled (DNC) network. It affirms PdM’s tangible value creation for SME CNC machine shops with predicted positive impacts on their MT cost and performance drivers. These exploratory research findings corroborate SMEs pooling together to optimise their CNC MT maintenance cost through the recommended system architecture. Finally, it introduces opportunities for further PdM research taking into account SMEs’ perspective. The paper’s industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT’s overall life cycle costs. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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Abstract Within the subject area of maintenance and maintenance management, authors identified a deficiency in studies focussing on the expected value from adopting predictive maintenance (PdM) techniques for machine tools (MTs). Authors identified no studies focussing on presenting a PdM value analysis or cost model specifically for small-medium enterprises (SMEs) operating computer numerically controlled (CNC) MTs. This paper’s novelty is addressing SMEs’ minimal representation in literature by explanatorily collecting data from SMEs within the focal area via surveys, modelling and analysing datasets, then proposes a cost-effective PdM system architecture for SME CNC machine shops that predicts cost savings ranging from £22,804 to £48,585 over a range of 1–50 CNC MTs maintained on a distributed numerically controlled (DNC) network. It affirms PdM’s tangible value creation for SME CNC machine shops with predicted positive impacts on their MT cost and performance drivers. These exploratory research findings corroborate SMEs pooling together to optimise their CNC MT maintenance cost through the recommended system architecture. Finally, it introduces opportunities for further PdM research taking into account SMEs’ perspective. The paper’s industrial application is confirmed from the surveyed SMEs that demonstrated their current utility of PdM; then anonymous positive feedback on the online dashboard, shared with participant companies, confirmed the research results supported SMEs in considering exploring the path to adapting PdM. It is anticipated that beneficiaries of this research will be maintenance managers, business executives and researchers who seek to understand the expected financial and performance impact of adopting PdM for a MT’s overall life cycle costs. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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