We consider a supply chain of a production unit permanently supplied and a warehouse where customers receive their products. The production unit is prone to random breakdowns. Corrective maintenance actions are carried out at each failure for random durations. In order to minimize the number of breakdowns, the production unit is subject to an age-type preventive maintenance policy. Corrective and preventive maintenance actions generate costs related to the maintenance of the production unit. The cost of a corrective maintenance action is Cmc and that of a preventive maintenance action is Cmp. Data : Tsim Cmp Cmc simulation time: 15000 ut cost of a preventive maintenance action: 300 um cost of a corrective maintenance action: 2500 um f1 equipment failure probability density: Weibull (2,100) gc probability density of equipment corrective maintenance actions: EXP (30) gp probability density of equipment preventive maintenance actions: EXP (10) Questions : 1) Establish the state machine of this supply chain. 2) Establish the temporal correlation table. 3) Establish a simulation algorithm to determine the optimal age m* of the preventive maintenance of the supply chain production unit. 4) Deduce this optimal age m* of maintenance via a simulation program in MATLAB.
We consider a supply chain of a production unit permanently supplied and a warehouse where customers receive their products. The production unit is prone to random breakdowns. Corrective maintenance actions are carried out at each failure for random durations. In order to minimize the number of breakdowns, the production unit is subject to an age-type preventive maintenance policy. Corrective and preventive maintenance actions generate costs related to the maintenance of the production unit. The cost of a corrective maintenance action is Cmc and that of a preventive maintenance action is Cmp. Data : Tsim Cmp Cmc simulation time: 15000 ut cost of a preventive maintenance action: 300 um cost of a corrective maintenance action: 2500 um f1 equipment failure probability density: Weibull (2,100) gc probability density of equipment corrective maintenance actions: EXP (30) gp probability density of equipment preventive maintenance actions: EXP (10) Questions : 1) Establish the state machine of this supply chain. 2) Establish the temporal correlation table. 3) Establish a simulation algorithm to determine the optimal age m* of the preventive maintenance of the supply chain production unit. 4) Deduce this optimal age m* of maintenance via a simulation program in MATLAB.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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Transcribed Image Text:We consider a supply chain of a production unit permanently supplied and a warehouse where customers receive their products.
The production unit is prone to random breakdowns.
Corrective maintenance actions are carried out at each failure for random durations.
In order to minimize the number of breakdowns, the production unit is subject to an age-type preventive maintenance policy.
Corrective and preventive maintenance actions generate costs related to the maintenance of the production unit.
The cost of a corrective maintenance action is Cmc and that of a preventive maintenance action is Cmp.
Data :
Tsim
simulation time: 15000 ut
Cmp cost of a preventive maintenance action: 300 um
Cmc cost of a corrective maintenance action: 2500 um
f1 : equipment failure probability density: Weibull(2,100)
gc probability density of equipment corrective maintenance actions: EXP (30)
gp probability density of equipment preventive maintenance actions: EXP (10)
Questions :
1) Establish the state machine of this supply chain.
2) Establish the temporal correlation table.
3) Establish a simulation algorithm to determine the optimal age m* of the preventive maintenance of the supply chain production unit.
4)Deduce this optimal age m* of maintenance via a simulation program in MATLAB.
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