A predictive maintenance cost model for CNC SMEs in the era of industry 4.0

Kwaku Adu-Amankwa, Ashraf K.A. Attia, Mukund Nilakantan Janardhanan, Imran Patel

Research output: Contribution to journalArticle

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.

LanguageEnglish
Pages3567-3587
Number of pages21
JournalInternational Journal of Advanced Manufacturing Technology
Volume104
Issue number9-12
Early online date13 Jul 2019
DOIs
Publication statusPublished - 31 Oct 2019

Fingerprint

Machine tools
Costs
Industry
Machine shops
Value engineering
Industrial applications
Life cycle
Managers
Feedback

Keywords

  • industry 4.0
  • machine maintenance cost
  • machine tool
  • predictive maintenance

Cite this

Adu-Amankwa, Kwaku ; Attia, Ashraf K.A. ; Janardhanan, Mukund Nilakantan ; Patel, Imran. / A predictive maintenance cost model for CNC SMEs in the era of industry 4.0. In: International Journal of Advanced Manufacturing Technology. 2019 ; Vol. 104, No. 9-12. pp. 3567-3587.
@article{0752269fd8cb4669a6777cdefeda2b48,
title = "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 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.",
keywords = "industry 4.0, machine maintenance cost, machine tool, predictive maintenance",
author = "Kwaku Adu-Amankwa and Attia, {Ashraf K.A.} and Janardhanan, {Mukund Nilakantan} and Imran Patel",
year = "2019",
month = "10",
day = "31",
doi = "10.1007/s00170-019-04094-2",
language = "English",
volume = "104",
pages = "3567--3587",
journal = "International Journal of Advanced Manufacturing Technology",
issn = "0268-3768",
number = "9-12",

}

A predictive maintenance cost model for CNC SMEs in the era of industry 4.0. / Adu-Amankwa, Kwaku; Attia, Ashraf K.A.; Janardhanan, Mukund Nilakantan; Patel, Imran.

In: International Journal of Advanced Manufacturing Technology, Vol. 104, No. 9-12, 31.10.2019, p. 3567-3587.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A predictive maintenance cost model for CNC SMEs in the era of industry 4.0

AU - Adu-Amankwa, Kwaku

AU - Attia, Ashraf K.A.

AU - Janardhanan, Mukund Nilakantan

AU - Patel, Imran

PY - 2019/10/31

Y1 - 2019/10/31

N2 - 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.

AB - 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.

KW - industry 4.0

KW - machine maintenance cost

KW - machine tool

KW - predictive maintenance

UR - http://www.scopus.com/inward/record.url?scp=85068960453&partnerID=8YFLogxK

U2 - 10.1007/s00170-019-04094-2

DO - 10.1007/s00170-019-04094-2

M3 - Article

VL - 104

SP - 3567

EP - 3587

JO - International Journal of Advanced Manufacturing Technology

T2 - International Journal of Advanced Manufacturing Technology

JF - International Journal of Advanced Manufacturing Technology

SN - 0268-3768

IS - 9-12

ER -