Multi-objective maintenance planning under preventive maintenance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abbas Al-Refaie ◽  
Hiba Almowas

PurposeThis research developed and examined a mathematical model for concurrent corrective and preventive maintenance policy of a system of series configuration.Design/methodology/approachA mathematical model was developed to maximize availability, and maximal net revenues, and minimal cost. Different probability distributions for time to failure and time to repair were considered. The model was then implemented on a real case study, which was studied under corrective maintenance policy and concurrent corrective and preventive policy.FindingsA comparison between results at current policy (90 days) and optimal period of corrective and preventive policy was conducted. It was found that availability, profit was increased from 94.4% and $20.091 – 96.5% and $24.803, respectively. Further, the cost was reduced from $1104.8 to $797.22.Research limitations/implicationsThe proposed optimization model can be adopted in planning maintenance activities for a single machine as well as for a system of series configuration machines under various probability distributions.Practical implicationsThe proposed model can significantly enhance performance of the production as well as maintenance systems. In addition, the developed model may support maintenance engineering in effective management of maintenance resources and the performance of its activities.Originality/valueThis research considers a mathematical model with multi-objective functions and distinct probability distributions for time-to-failure for a system of series machines. Moreover, appropriate approximation solution was deployed to find integral of some functions. Finally, it provides maintenance planning for a single machine or a series of machines.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Giuseppe Aiello ◽  
Julio Benítez ◽  
Silvia Carpitella ◽  
Antonella Certa ◽  
Mario Enea ◽  
...  

PurposeThis study aims to propose a decision support system (DSS) for maintenance management of a service system, namely, a street cleaning service vehicle. Referring to the information flow management, the blockchain technology is integrated in the proposed DSS to assure data transparency and security.Design/methodology/approachThe DSS is designed to efficiently handle the data acquired by the network of sensors installed on selected system components and to support the maintenance management. The DSS supports the decision makers to select a subset of indicators (KPIs) by means of the DEcision-MAaking Trial and Evaluation Laboratory method and to monitor the efficiency of performed preventive maintenance actions by using the mathematical model.FindingsThe proposed maintenance model allows real-time decisions on interventions on each component based on the number of alerts given by sensors and taking into account the annual cost budget constraint.Research limitations/implicationsThe present paper aims to highlight the implications of the blockchain technology in the maintenance field, in particular to manage maintenance actions’ data related to service systems.Practical implicationsThe proposed approach represents a support in planning, executing and monitoring interventions by assuring the security of the managed data through a blockchain database. The implications regard the monitoring of the efficiency of preventive maintenance actions on the analysed components.Originality/valueA combined approach based on a multi-criteria decision method and a novel mathematical programming model is herein proposed to provide a DSS supporting the management of predictive maintenance policy.


Author(s):  
Takao Ota ◽  
Hiroyuki Kawamura ◽  
Yoshiharu Matsumi ◽  
Junji Koyanagi ◽  
Takashi Satow

The infrastructures are required to keep a certain level of performance during the duration of service. Because the performance of the infrastructures including harbor and coastal structures deteriorates due to aging and damage that is caused by the action of external forces, it is necessary to perform appropriate maintenance. Satow et al. (2009) proposed a mathematical model for the preventive maintenance of wave dissipating blocks based on the method of the reliability engineering. They also derived the expected maintenance cost over the in service period and the optimal preventive maintenance policy. In this study, the optimal threshold for preventive maintenance to minimize the expected maintenance cost is determined for the wave dissipating blocks covering caisson breakwater by using the above model.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imad Alsyouf ◽  
Sadeque Hamdan ◽  
Mohammad Shamsuzzaman ◽  
Salah Haridy ◽  
Iyad Alawaysheh

PurposeThis paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.Design/methodology/approachThe critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.FindingsFor a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.Research limitations/implicationsOnly three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.Practical implicationsThe proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.Originality/valueThis research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amit Kumar ◽  
Pardeep Kumar

PurposeThis paper presents the performance analysis of the automatic ticket vending machine (ATVM) through the functioning of its different hardware and software failures.Design/methodology/approachFrequent failures in the working of ATVM have been observed; therefore, the authors of the paper intend to analyze the performance measures of the same. Authors have developed a mathematical model based on different hardware and software failures/repairs, which may occur during the operation, with the help of the Markov process. The developed model has been solved for two kinds of failure/repair rates namely variable failures (very much similar to real-time failure) and constant failures. Lagrange's method and Laplace transformation are used for the solution of the developed model.FindingsReliability and mean time to failure of the ATVM are determined. Sensitivity analysis for ATVM is also carried out in the paper. Critical components of the ATVM, which affect the performance of the same, in terms of reliability and MTTF are also identified.Originality/valueA mathematical model based on different hardware and software failures/repairs of ATVM has been developed to analyze its performance, which has not been done in the past.


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