Skip to main content

Advertisement

SpringerLink
Log in

A virtual collaborative maintenance architecture for manufacturing enterprises

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

This paper presents a virtual collaborative maintenance architecture aimed at improving the performance of manufacturing systems. The proposed architecture incorporates maintenance elements such as operational reliability, maintenance economics, human factors in maintenance, maintenance program, and maintenance optimization in a virtual collaborative architecture. An analytical model is proposed to measure the relative performance of the proposed virtual collaborative architecture as well as that of the manufacturing enterprise. A numerical example is also presented to demonstrate the application of the proposed approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

OR:

Operational reliability

ME:

Maintenance economics

MO:

Maintenance optimization

HF:

Human factors

MP:

Maintenance program

PM:

Preventive maintenance

TMFGC:

Total manufacturing cost ($)

TMFGH:

Total manufacturing man-hour worked

TS:

Total sales ($)

TO:

Total output ($)

TLOI:

Total loss due to operational interruptions ($)

TOIM:

Total man-hour cost for operational interruption analysis ($)

MFGOR:

Manufacturing operational reliability which is measured in terms of the percentage of availability of manufacturing facility in unit time (%)

TRMJ:

Total cost of required maintenance jobs ($)

TMEC:

Total investment for estimating direct maintenance cost ($)

TMEM:

Total man-hour cost for estimating direct maintenance cost ($)

TMC:

Total maintenance cost ($)

TCE:

Total cost of maintenance cost estimation ($)

TMOC:

Total investment for maintenance optimization ($)

TMOM:

Total man-hour cost for maintenance optimization ($)

TE:

Achievement factor indicating the efficiency of the maintenance optimization element (%)

TBD:

Total cost of breakdowns ($)

THEC:

Total investment for improving equipment design, work environment, work layout, work tools, training requirement, and written equipment maintenance and operating procedures ($)

THEM:

Total man-hour cost for improving equipment design, work environment, work layout, work tools, training requirement, and written equipment maintenance and operating procedures ($)

TDTCH:

Total downtime cost caused by human errors in maintenance ($)

TBDH:

Total cost of maintenance jobs resulting from human errors ($)

TCMP:

Total cost for implementation of an appropriate maintenance strategy ($)

TMMP:

Total cost of man-hour for planning ($)

TLPUB:

Total loss of production due to unscheduled maintenance jobs ($)

TJ:

Total cost of direct labour and parts of maintenance jobs ($)

DC:

Unit time delay cost due to unavailability of the manufacturing facility ($)

IMC:

Initial maintenance cost which is the cost before implementing maintenance optimization ($)

Z ep :

The objective value when the element e in period p is used as the reference

θ :

Enterprise performance known as proportion input index

E:

Archimedes factor (10−6)

t, p :

Period index t, p =  1, 2, . . . . . . . , T

i :

Input index, i = 1, 2, . . . , n

j, e :

Element index j, e = 0, 1, 2, 3, 4, 5—0 for enterprise, 1–5 for maintenance elements

k :

Output index, k = 1, 2, . . . , m

x jt :

The decision variable of the jth element in period t

SP k :

The surplus variable of kth output

SN i :

The slack variable of ith input

in ijt :

Input i for maintenance element j in period t

out kjt :

Output k for maintenance element j in period t

IN i :

Reference input i, which is equal to out kep where the element e in period p is the reference

OUT k :

Reference output k, which is equal to out kep where the element e in period p is the reference

References

  • AMCP 706-134. (1972). Maintainability guide for design. Washington, D.C.: U.S. army material command, Department of the Army.

  • Barlow R.E. and Hunter L.C. (1960). Optimum preventive maintenance policies. Operations Research 8: 90–100

    Google Scholar 

  • Barlow R.E. and Proshan F. (1975). Statistical theory of reliability and life testing. Holt, Rinehart & Winston, New York

    Google Scholar 

  • Block H.W., Langberg N.A. and Savits T.H. (1993). Repair replacement policies. Journal of Applied Probability 30(1): 194–206

    Article  Google Scholar 

  • Charnes A., Cooper W.W. and Rhodes E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research 2(6): 429–444

    Article  Google Scholar 

  • De Groote P. (1995). Maintenance performance analysis: A practical approach. Journal of Quality in Maintenance Engineering 1(2): 4–24

    Article  Google Scholar 

  • Dohi T., Matsushima N., Kaio N. and Osaki S. (1996). Nonparametric repair-limit replacement policies with imperfect repair. European Journal of Operational Research 96(2): 260–273

    Article  Google Scholar 

  • Jardine A.K.S., Joseph T. and Banjevic D. (1999). Optimizing condition-based maintenance decision for equipment subject to vibration monitoring. Journal of Quality in Maintenance Engineering 5(3): 192–202

    Article  Google Scholar 

  • Jayabalan V. and Chaudhuri D. (1992a). Optimal maintenance-replacement policy under imperfect maintenance. Reliability Engineering and System Safety 36(2): 165–169

    Article  Google Scholar 

  • Jayabalan V. and Chaudhuri D. (1992b). Optimal maintenance and replacement policy for deteriorating system with increased mean downtime. Naval Research Logistics 39: 67–78

    Article  Google Scholar 

  • Kapur P.K., Garg R.B. and Butani N.L. (1989). Some replacement policies with minimal repairs and repair cost limit. International Journal of Systems Science 20(2): 267–279

    Article  Google Scholar 

  • Kijima M. and Nakagawa T. (1992). Replacement policies of a shock model with imperfect preventive maintenance. European Journal of Operations Research 57: 100–110

    Article  Google Scholar 

  • Latino, C. J. (1999). Hidden treasure: eliminating chronic failure can cut maintenance cost up to 60%. Report, Reliability Center, Hopewell, Virginia.

  • Lam Y. (2007). A geometric process maintenance model with preventive repair. European Journal of Operational Research 182(2): 806–819

    Article  Google Scholar 

  • Lin J. and Lin T. (2004). Object-oriented conceptual modeling for commitment-based collaboration management in virtual enterprises. Information and Software Technology 46: 209–217

    Article  Google Scholar 

  • Liu J and Yu D. (2004). Evaluation of plant maintenance data based on data envelopment analysis. Journal of Quality in Maintenance Engineering 10(3): 203–209

    Article  Google Scholar 

  • Liu X., Makis V. and Jardine A.K.S. (1995). A replacement model with overhauls and repairs. Naval Research Logistics 42: 1063–1079

    Article  Google Scholar 

  • Love C.E. and Guo R. (1996). Utilizing Weibull failure rates in repair limit analysis for equipment replacement/preventive maintenance decisions. Journal of the Operational Research Society 47(11): 1366–1376

    Article  Google Scholar 

  • Makis V. and Jardine A.K.S. (1993). A note on optimal replacement policy under general repair. European Journal of Operational Research 69: 75–82

    Article  Google Scholar 

  • Morimura H. and Makabe H. (1963). A new policy for preventive maintenance. Journal of the Operations Research Society of Japan 5: 110–124

    Google Scholar 

  • Muth E.J. (1977). An optimal decision rule for repair vs. replacement. IEEE Transactions on Reliability 26(3): 179–181

    Article  Google Scholar 

  • Nakagawa T. (1984). Optimal policy of continuous and discrete replacement with minimal repair at failure. Naval Research Logistics Quarterly 31(4): 543–550

    Article  Google Scholar 

  • Niebel B.W. (1994). Engineering maintenance management. Marcell Dekker, New York

    Google Scholar 

  • Pham H. and Wang H. (1996). Imperfect maintenance. European Journal of Operational Research 94: 425–438

    Google Scholar 

  • Pham H. and Wang H. (2000). Optimal (s; T) opportunistic maintenance of a k-out-of-n: G system with imperfect PM and partial failure. Naval Research Logistics 47: 223–239

    Article  Google Scholar 

  • Sheu S., Kuo C. and Nakagawa T. (1993). Extended optimal age replacement policy with minimal repair. RAIRO: Recherche Operationnelle 27(3): 337–351

    Google Scholar 

  • Tahara A. and Nishida T. (1975). Optimal replacement policy for minimal repair model. Journal of Operations Research Society of Japan 18(3-4): 113–124

    Google Scholar 

  • Wang, H., Pham, H., & Izundu, A. E. (2001). Optimal preparedness maintenance of multi-unit systems with imperfect maintenance and economic dependence. In Recent advances in reliability and quality engineering (pp. 75-92). New Jersey: World Scientific.

  • Zhou X., Xi L. and Lee J. (2006). A dynamic opportunistic maintenance policy for continuously monitored systems. Journal of Quality in Maintenance Engineering 12(3): 294–305

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, ON, Canada

    K. Jenab & S. Zolfaghari

Authors
  1. K. Jenab
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Zolfaghari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Zolfaghari.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jenab, K., Zolfaghari, S. A virtual collaborative maintenance architecture for manufacturing enterprises. J Intell Manuf 19, 763–771 (2008). https://doi.org/10.1007/s10845-008-0126-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-008-0126-0

Keywords

Search

Navigation