What are the key determinants of maintenance performance?

Darestani, Soroush Avakh; Ganji, Mandana; Imannezhad, Rana

doi:10.1590/0103-6513.20190155

Soroush Avakh Darestani ^* * ad5710@coventry.ac.uk

School of Strategy and Leadership, Faculty of Business and Law, Coventry University, Coventry, UK

http://orcid.org/0000-0003-0388-9004

Mandana Ganji

Department of Industrial Engineering, Bandar e Anzali International Branch, Islamic Azad University, Bandar e Anzali, Iran

http://orcid.org/0000-0002-4479-1030

Rana Imannezhad

Department of Industrial Engineering, Bandar e Anzali International Branch, Islamic Azad University, Bandar e Anzali, Iran

http://orcid.org/0000-0002-0638-002X

* ad5710@coventry.ac.uk

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Figure 1
Cause-and-effect relationships Diagram.

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Figure 2
Relative weight of criteria and sub-criteria.

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Figure 3
Important factors in measurement of maintenance performance.

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Table 1
Sub-criteria relationships

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Table 2
Criteria and sub-criteria of maintenance performance measurement

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Table 3
W₂₁ vector and W₃₂ matrix

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Table 4
Internal relations matrix of criteria

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Table 5
Internal relations matrix of sub-criteria

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Table 6
Limited Super Matrix

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Table 7
the relative importance and weight of the criteria and sub-criteria

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C1 C2 C3 C4 C1 (0.12,0.55,5.33) (0.07,0.38,3.67) (0.27,0.75,5.57) (0.26,0.69,5.06) C2 (0.31,0.81,5.36) (0.02,0.26,3.32) (0.32,0.82,5.34) (0.12,0.58,4.74) C3 (0.28,0.75,5.30) (0.02,0.33,3.44) (0.10,0.50,5.01) (0.25,0.66,4.79) C4 (0.26,0.73,5.33) (0.02,0.32,3.46) (0.25,0.72,5.30) (0.10,0.44,4.55)

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C1 C2 C3 C4 C1 (1.99) (1.37) (2.20) (2.01) C2 (2.16) (1.20) (2.16) (1.82) C3 (2.11) (1.26) (1.87) (1.90) C4 (2.11) (1.27) (2.09) (1.70)

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L M U R1 3.148 3.539 4.298 R2 3.22 3.841 4.473 R3 3.989 4.765 5.413 R4 3.429 4.065 4.489 SR 13.79 16.21 19.14

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SI L M U S1 0.164 0.218 0.312 S2 0.168 0.237 0.344 S3 0.208 0.294 0.393 S4 0.179 0.251 0.34

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SI S1 S2 S3 S4 S1 1 1 1 1 S2 0.885 1 1 1 S3 0.577 0.704 1 0.753 S4 0.803 0.923 1 1

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weigh W1 0.577 W2 0.704 W3 1 W4 0.753

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weigh W1 0.19 W2 0.232 W3 0.33 W4 0.248

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S₁	S₂	S₃	S₄	S₅	S₆	S₇	S₈	S₉	S₁₀	S₁₁	S₁₂	S₁₃	S₁₄
S₁	0	1	0	0	0	0	0	0	1	0	0	0	0
S₂	0	1	0	0	0	0	0	0	1	0	0	0	0
S₃	0	0	0	0	0	0	0	0	0	0	0	1	0
S₄	1	0	0	1	0	1	1	0	1	0	0	0	0
S₅	1	1	1	0	0	1	1	0	1	0	0	0	0
S₆	1	1	0	0	0	1	1	1	1	1	0	0	1
S₇	1	1	0	0	0	0	1	0	1	0	0	1	1
S₈	1	0	0	1	0	1	0	0	0	1	1	0	0
S₉	0	0	1	0	0	0	1	0	0	1	0	1	0
S₁₀	0	0	0	0	0	1	0	0	0	0	0	0	0
S₁₁	0	0	0	0	0	0	0	0	0	0	1	0	0
S₁₂	0	0	0	0	1	1	1	0	0	0	0	0	1
S₁₃	0	0	0	0	0	1	0	0	0	0	0	0	0
S₁₄	0	1	0	0	1	1	1	1	1	0	1	0	0

Authors	Criterion	Abbreviation	Sub-criteria	Abbreviation
Amrina et al. (2019)Amrina, E., Yulianto, A., & Kamil, I. (2019). Fuzzy multi criteria approach for sustainable maintenance evaluation in rubber industry, 16th Global Conference on Sustainable Manufacturing – Sustainable Manufacturing for Global Circular Economy, Procedia Manufacturing, 33, 538-545. http://dx.doi.org/10.1016/j.promfg.2019.04.067. http://dx.doi.org/10.1016/j.promfg.2019....	Economic	C₁	Maintenance cost	S₁
Sari et al. (2015)Sari, E., Shaharoun, A. M., Ma’aram, A., & Yazid, A. M. (2015). Sustainable Maintenance Performance Measures: A pilot survey in Malaysian Automotive Companies. Procedia CIRP, 26, 443-448. http://dx.doi.org/10.1016/j.procir.2014.07.163. http://dx.doi.org/10.1016/j.procir.2014....			Breakdown Cost	S₂
			Maintenance Value	S₃
Cruz & Haugan (2019)Cruz, A. M., & Haugan, G. L. (2019). Determinants of maintenance performance: A resource-based view and agency theory approach. Journal of Engineering and Technology Management, 51, 33-47. http://dx.doi.org/10.1016/j.jengtecman.2019.03.001. http://dx.doi.org/10.1016/j.jengtecman.2...	Support	C₂	Spare Parts Inventory	S₄
			Logistic	S₅
			Skilled and Trained Workforce	S₆
Oliveira et al. (2016)Oliveira, M., Lopes, I., & Rodrigues, C. (2016). Use of maintenance performance indicators by companies of the industrial hub of Manaus. Procedia CIRP, 52, 157-160. http://dx.doi.org/10.1016/j.procir.2016.07.071. http://dx.doi.org/10.1016/j.procir.2016....	Functional	C₃	Quality for Maintenance	S₇
			Availability	S₈
			Reliability	S₉
			Productivity	S₁₀
Amrina et al. (2019)Amrina, E., Yulianto, A., & Kamil, I. (2019). Fuzzy multi criteria approach for sustainable maintenance evaluation in rubber industry, 16th Global Conference on Sustainable Manufacturing – Sustainable Manufacturing for Global Circular Economy, Procedia Manufacturing, 33, 538-545. http://dx.doi.org/10.1016/j.promfg.2019.04.067. http://dx.doi.org/10.1016/j.promfg.2019....	Social & People	C₄	Safety / Risk/ Health	S₁₁
Sari et al. (2015)Sari, E., Shaharoun, A. M., Ma’aram, A., & Yazid, A. M. (2015). Sustainable Maintenance Performance Measures: A pilot survey in Malaysian Automotive Companies. Procedia CIRP, 26, 443-448. http://dx.doi.org/10.1016/j.procir.2014.07.163. http://dx.doi.org/10.1016/j.procir.2014....			Employee Satisfaction	S₁₂
			Stakeholders Satisfaction	S₁₃
			Learning and Growth	S₁₄

Weight of criteria relative to objective function (W₂₁)			Sub-Criteria Weight to Criteria (W₃₃)
			C₁	C₂	C₃	C₄
C₁	0.19	S₁	0.285	0	0	0
		S₂	0.374	0	0	0
		S₃	0.341	0	0	0
C₂	0.232	S₄	0	0.344	0	0
		S₅	0	0.313	0	0
		S₆	0	0.344	0	0
C₃	0.33	S₇	0	0	0.274	0
		S₈	0	0	0.313	0
		S₉	0	0	0.206	0
		S₁₀	0	0	0.206	0
C₄	0.248	S₁₁	0	0	0	0.268
		S₁₂	0	0	0	0.298
		S₁₃	0	0	0	0.217
		S₁₄	0	0	0	0.217

	C₁	C₃	C₄
C₁	0	0.5	0.5
C₂	0.43	0.57	0
C₃	0	1	0
C₄	0.451	0.549	0

	S₁	S₂	S₃	S₄	S₅	S₆	S₇	S₈	S₉	S₁₀	S₁₁	S₁₂	S₁₃	S₁₄
S₁	0	0	0.5	0	0	0	0	0	0	0.5	0	0	0	0
S₂	0	0	0.5	0	0	0	0	0	0	0.5	0	0	0	0
S₃	0	0	0	0	0	0	0	0	0	0	0	0	1	0
S₄	0.167	0.167	0	0	0.167	0	0.167	0.167	0	0.167	0	0	0	0
S₅	0.114	0.114	0.114	0.167	0	0	0.134	0.135	0	0.144	0	0	0	0
S₆	0	0.122	0.122	0	0	0	0.122	0.148	0.118	0.118	0.125	0	0	0.125
S₇	0	0.167	0.163	0	0	0	0	0.156	0	0.203	0	0	0.154	0.156
S₈	0	0.25	0	0	0.242	0	0.254	0	0	0	0	0.254	0	0
S₉	0	0	0	0.212	0	0	0	0.318	0	0	0.235	0	0.235	0
S₁₀	0	0	0	0	0	0	1	0	0	0	0	0	0	0
S₁₁	0	0	0	0	0	0	0	0	0	0	0	0	1	0
S₁₂	0	0	0	0	0	0.243	0.243	0.243	0	0	0	0	0	0.271
S₁₃	0	0	0	0	0	0	1	0	0	0	0	0	0	0
S₁₄	0	0	0.126	0	0	0.126	0.126	0.231	0.13	0.112	0	0.147	0	0

	G	C₁	C₂	C₃	C₄	S₁	S₂	S₃	S₄	S₅	S₆	S₇	S₈	S₉	S₁₀	S₁₁	S₁₂	S₁₃	S₁₄
G	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
C₁	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
C₂	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
C₃	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
C₄	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
S₁	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01
S₂	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01
S₃	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01
S₄	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06	0.06
S₅	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05	0.05
S₆	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.11	0.08
S₇	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08
S₈	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16	0.16
S₉	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08	0.08
S₁₀	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03
S₁₁	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01
S₁₂	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19	0.19
S₁₃	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03	0.03
S₁₄	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18	0.18

weight of the criteria and sub-criteria
C₁	0.03	C₂	0.22	C₃	0.34	C₄	0.41
S₁	0.01	S₄	0.05	S₇	0.08	S₁₁	0.01
S₂	0.01	S₅	0.06	S₈	0.16	S₁₂	0.19
S₃	0.01	S₆	0.11	S₉	0.08	S₁₃	0.03
				S₁₀	0.03	S₁₄	0.18

\tilde{X} = [\begin{matrix} {\tilde{X}}_{11} {\tilde{X}}_{12} \dots {\tilde{X}}_{1 n} \\ {\tilde{X}}_{21} {\tilde{X}}_{22} \dots {\tilde{X}}_{2 n} \\ ⋮ ⋮ ⋱ ⋮ \\ {\tilde{X}}_{n 1} {\tilde{X}}_{n 2} \dots {\tilde{X}}_{n m} \end{matrix}]

\tilde{T} = [\begin{matrix} {\tilde{t}}_{11} {\tilde{t}}_{12} \dots {\tilde{t}}_{1 n} \\ {\tilde{t}}_{21} {\tilde{t}}_{22} \dots {\tilde{t}}_{2 n} \\ ⋮ ⋮ ⋱ ⋮ \\ {\tilde{t}}_{n 1} {\tilde{t}}_{n 2} \dots {\tilde{t}}_{n m} \end{matrix}]

\{\begin{matrix} V (M_{1} \geq M_{2}) = 1 i f (m_{1} \geq m_{2} \\ V (M_{1} < M_{2}) = h g t (M_{1} \cap M_{2}) o t h e r w i s e \end{matrix}

[1] * ad5710@coventry.ac.uk

Brasil

Brasil

What are the key determinants of maintenance performance?

Abstract

Paper aims

Originality

Research method

Main findings

Implications for theory and practice