scholarly journals Production, preventive and corrective maintenance planning in manufacturing systems under imperfect repairs

2011 ◽  
Author(s):  
Annie Francie Kouedeu ◽  
Jean-Pierre Kenne ◽  
Victor Songmene
Keyword(s):  
Manufacturing Systems ◽  
Maintenance Planning ◽  
Corrective Maintenance ◽  
Imperfect Repairs

Machine Fault Diagnosis and Prognosis using Self-Organizing Map

2014 ◽  
pp. 129-148
Author(s):  
Kesheng Wang ◽  
Zhenyou Zhang ◽  
Yi Wang
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Manufacturing Systems ◽  
Maintenance Scheduling ◽  
Self Organizing Map ◽  
Corrective Maintenance ◽  
Diagnosis And Prognosis ◽  
Machine Fault ◽  
Fault Diagnosis And Prognosis ◽  
Self Organizing

This chapter proposes a Self-Organizing Map (SOM) method for fault diagnosis and prognosis of manufacturing systems, machines, components, and processes. The aim of this work is to optimize the condition monitoring of the health of the system. With this method, manufacturing faults can be classified, and the degradations can be predicted very effectively and clearly. A good maintenance scheduling can then be created, and the number of corrective maintenance actions can be reduced. The results of the experiment show that the SOM method can be used to classify the fault and predict the degradation of machines, components, and processes effectively, clearly, and easily.

Improved Markov stable state simulation for maintenance planning

2019 ◽  
Vol 25 (2) ◽  
pp. 199-212
Author(s):  
Chibundo Princewill Nwadinobi ◽  
Bethrand Nduka Nwankwojike ◽  
Fidelis Ibiang Abam
Keyword(s):  
Manufacturing Systems ◽  
Stable State ◽  
Mechanistic Modeling ◽  
Maintenance Planning ◽  
Probability Models ◽  
Actual Performance ◽  
Content Type ◽  
Mean Time Between Failures ◽  
Relevant Variables ◽  
Mean Time

Purpose The purpose of this paper is to propose a software (Equipment State Simulator) used for predicting equipment performance parameters required for maintenance planning. Design/methodology/approach This maintenance software was developed from the derived stable state probability models using algebraic substitution and computation of total operational period, number of breakdowns, total downtime, mean time between failures and mean time to repair of equipment/component(s) at preventive maintenance and corrective maintenance states. The models were derived using mechanistic modeling technique such that all the relevant variables were accounted for. Findings Analysis of this software revealed that its predictions reckon with the actual performance of the test specimens by about 99 percent. Originality/value The research proposes a maintenance model and software for predicting state probabilities of manufacturing systems degradation. This program also predicts maintenance action(s) required by the equipment based on the predetermined alert levels.

scholarly journals Age-dependent production and replacement strategies in failure-prone manufacturing systems

2016 ◽  
Vol 231 (3) ◽  
pp. 540-554 ◽  
Author(s):  
Samir Ouaret ◽  
Jean-Pierre Kenné ◽  
Ali Gharbi ◽  
Vladimir Polotski
Keyword(s):  
Numerical Methods ◽  
Production Rate ◽  
Manufacturing Systems ◽  
Planning Horizon ◽  
Replacement Policy ◽  
Control Policies ◽  
Bellman Equations ◽  
Machine Failure ◽  
The Impact ◽  
Imperfect Repairs

A failure-prone manufacturing system that consists of one machine producing one type of product is studied. The random phenomena examined are machine breakdowns and repairs. We assume that the machine undergoes a progressive deterioration while in operation and that the machine failure rate is a function of its age. The aging of the machine (the dynamics of the machine age) is assumed to be an increasing function of its production rate. Corrective maintenance activities are imperfect and restore the age of the machine to as-bad-as-old conditions. When a failure occurs, the machine can be repaired, and during production, the machine can be replaced, depending on its age. When the replacement action is selected, the machine is replaced by a new and identical one. The decision variables are the production rate and the replacement policy. The objective of this article is to address the simultaneous production and replacement policy optimization problem in the context of manufacturing with deterioration and imperfect repairs satisfying the customer demand and minimizing the total cost, which includes costs associated with inventory, backlog, production, repair and replacement, over an infinite planning horizon. We thoroughly explore the impact of the machine aging on the production and replacement policies. Particular attention is paid to the verification of underlying mathematical results that guarantee the existence of optimal solutions and the convergence of numerical methods. Due to imperfect repairs, the dynamics of the system is affected by the system history, and semi-Markov processes have to be used for modeling. Optimality conditions in the form of the Hamilton–Jacobi–Bellman equations are developed, and numerical methods are used to obtain the optimal control policies (production (rate) and replacement policies). A numerical example is given to illustrate the proposed approach, and an extensive sensitivity analysis is presented to confirm the structure of the obtained control policies.

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