Integrated graphical model to evaluate multi-criteria maintenance policies for degradable systems
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Abstract
This paper deals with a system developed that will investigate on the (failure) data input of a given system to decide on its maintenance policies, specifically between breakdown maintenance and preventive maintenance (PM), which can restore the system either by repair or replacement as may be applicable. The system developed has the genesis of Kay’s work. Working on the basic limitations of Kay’s work, a complete system is developed as an integrated graphical tool to be suitable for degradable systems wherein repairing or replacement as applicable, considering three important criteria as suggested by Kay. After evaluating what type of maintenance is possible, the system developed optimizes for optimal period in case of PM is preferred. The algorithm involved in the development of the graphical tool is coded in Matlab 7.0 for in between Weibull shape parameters and numerical integration. The details of the research methodology and analytical issues involved are all presented appropriately in the paper. The system has been applied to four test cases and the utility of the tool has been explained through stepwise procedure and flow chart in the paper with appropriate results and discussions.
Keywords
Optimal maintenance schedule Availability Maintenance cost rate Revenue earning rate Multi-criteria decision makingList of symbols
- f(t)
Time to failure density
- R(t)
Reliability function
- M
MTBF, E(t)
- M
Mean maintenance time for BDM
- ms
Mean maintenance time for PM
- T
Scheduled period
- T*
Optimal schedule
- \( \overline{\text{T}} \)
Mean time between replacements or MTTF in period T
- h(t)
Hazard function
- p
Net earning rate = total revenue/unit time − cost/unit time
- A
Availability in case of BDM
- As
Availability in case of PM
- C
Maintenance cost rate in case of BDM
- cs
Maintenance cost rate in case of PM
- C
Average maintenance cost per unit time in case of BDM
- Cs
Average maintenance cost per unit time in case of PM
- P
Average earning per unit time in case of BDM
- Ps
Average earning per unit time in case of PM
- α
\( \overline{\text{T}} /{\text{M}} \le 1 \)
- γ
mp/mb ≤ 1
- δ
cp/cb ≤ 1
- μ
mb/M ≤ 1
- ω
cb/pb
- θ
Scale parameter of two parameter Weibull distribution
- β
Shape parameter of two parameter Weibull distribution
- Tint*
Value of T where α and 1-kR(T) intersect
- TΔ*
Value of T maximum gap between α and 1-KR(T)
- Tcri*
Optimal value of T obtained from criterion function
- Titr*
Optimal value of T obtained from the iterative mechanism
- F(t)
Distribution function
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