scholarly journals Non-periodic inspection of optimization of repairable systems

2021 ◽  
Author(s):  
Yassin Hajipour
Keyword(s):  
Simulation Model ◽  
Failure Time ◽  
Planning Horizon ◽  
Repairable Systems ◽  
Expected Cost ◽  
Total Cost ◽  
Penalty Cost ◽  
Periodic Inspection ◽  
Finite Planning Horizon ◽  
Hard Type

This study proposes models to find the optimal non-periodic inspection interval over a finite planning horizon for two types of multi-component repairable systems. The first system consists of hard-type and soft-type components, and the second system is a k-out-of-m system with m identical components. The failures of components in both systems follow a non-homogeneous Poisson process. The failure of soft-type components and the failure of components in a k-out-of-m system when the number of failed components is still less than m-k+1, are soft failures. Soft failures are revealed only at scheduled inspections or when an event of opportunistic inspection or a system failure occurs. The failures of hard-type components or the failure of (m-k+1)th failed component in a k-out-of-m system are hard failures, and cause the system to stop functioning. Hard failures are revealed immediately and the failed components are fixed. In this study, a failed component is either replaced or minimally repaired according to its age at failure time. To find the optimal inspection schedules for the systems, we minimize the total expected cost of the systems over a finite planning horizon. The total cost for the first type of system includes the costs of components’ minimal repairs, replacements, downtimes, and the scheduled inspections. The total cost of a k-out-of-m system has an additional penalty cost for system failures. We consider a binary variable for a possible scheduled inspection’s time, in which 1 indicates performing a planned inspection at that time, and 0 shows no inspection to be performed. Thus, our goal is to find the optimal vector of binary decision variables which results in the minimum total cost of the system. A recursive formula is developed to calculate the expected number of minimal repairs, replacements and downtime of soft-type components. However since obtaining the expected values from the mathematical formula is cumbersome, we develop a simulation model to obtain the total expected cost for a given non-periodic inspection scheme. We then integrate the simulation model with a genetic algorithm to obtain the optimal inspection scheme.

scholarly journals Non-periodic inspection of optimization of repairable systems

2021 ◽  
Author(s):  
Yassin Hajipour
Keyword(s):  
Simulation Model ◽  
Failure Time ◽  
Planning Horizon ◽  
Repairable Systems ◽  
Expected Cost ◽  
Total Cost ◽  
Penalty Cost ◽  
Periodic Inspection ◽  
Finite Planning Horizon ◽  
Hard Type

This study proposes models to find the optimal non-periodic inspection interval over a finite planning horizon for two types of multi-component repairable systems. The first system consists of hard-type and soft-type components, and the second system is a k-out-of-m system with m identical components. The failures of components in both systems follow a non-homogeneous Poisson process. The failure of soft-type components and the failure of components in a k-out-of-m system when the number of failed components is still less than m-k+1, are soft failures. Soft failures are revealed only at scheduled inspections or when an event of opportunistic inspection or a system failure occurs. The failures of hard-type components or the failure of (m-k+1)th failed component in a k-out-of-m system are hard failures, and cause the system to stop functioning. Hard failures are revealed immediately and the failed components are fixed. In this study, a failed component is either replaced or minimally repaired according to its age at failure time. To find the optimal inspection schedules for the systems, we minimize the total expected cost of the systems over a finite planning horizon. The total cost for the first type of system includes the costs of components’ minimal repairs, replacements, downtimes, and the scheduled inspections. The total cost of a k-out-of-m system has an additional penalty cost for system failures. We consider a binary variable for a possible scheduled inspection’s time, in which 1 indicates performing a planned inspection at that time, and 0 shows no inspection to be performed. Thus, our goal is to find the optimal vector of binary decision variables which results in the minimum total cost of the system. A recursive formula is developed to calculate the expected number of minimal repairs, replacements and downtime of soft-type components. However since obtaining the expected values from the mathematical formula is cumbersome, we develop a simulation model to obtain the total expected cost for a given non-periodic inspection scheme. We then integrate the simulation model with a genetic algorithm to obtain the optimal inspection scheme.

An EOQ model with stepwise ordering cost and the finite planning horizon under carbon cap-and-trade regulations

2021 ◽  
Vol 10 (3) ◽  
pp. 337-350
Author(s):  
Tzu-Chia Chen ◽  
Shu-Yan Yu
Keyword(s):  
Low Cost ◽  
Planning Horizon ◽  
Finite Horizon ◽  
Optimal Order ◽  
Fixed Cost ◽  
Cap And Trade ◽  
Total Cost ◽  
Eoq Model ◽  
Finite Planning Horizon ◽  
Ordering Quantity

In this study, under the carbon cap-and-trade mechanism, the ordering cost presents a stepwise function for ordering quantity, and the optimal economic ordering quantity model aims to explore the manufacturer's total cost minimization in the finite planning horizon, in combination with the actual situation that the product will produce carbon emissions during transportation and storage. The economic order quantity (EOQ) model with stepwise ordering cost is applicable to the decision environment in which goods are utilized by sea, by rail or by air (e.g., the order cost is charged in addition to the basic fixed cost, the importer of raw materials will pay an additional freight related to delivery, such as the rent for the use of container numbers.). A heuristic algorithm is also proposed to analyze the relevant properties of the optimal solution of the model and to solve the optimal order times and quantities of the manufacturer under the constraint of carbon policy.We further compared the optimal order times with the case without carbon constraint and the order times corresponding to the manufacturer's realization of the minimum carbon emission, and obtained the conditions for the manufacturer to achieve low cost and low emission under the carbon policy.Finally, the theoretical results of the model are verified by numerical examples,and the influence of relevant parameters on the inventory strategy of manufacturers is discussed. The results show that under the carbon cap-and-trade policy, there is an optimal ordering strategy that minimizes the total cost of the manufacturer in the finite horizon. When the demand of the manufacturer is under finite horizon and the carbon policy is equal to the specific multiplier of orders, the manufacturer can achieve a win-win result of low cost and low emissions.

Optimizing preventive maintenance over a finite planning horizon in a semi-Markov framework

2020 ◽  
Author(s):  
Antonio Sánchez Herguedas ◽  
Adolfo Crespo Márquez ◽  
Francisco Rodrigo Muñoz
Keyword(s):  
Preventive Maintenance ◽  
Recurrence Relations ◽  
Direct Calculation ◽  
Planning Horizon ◽  
Practical Implementation ◽  
Practical Application ◽  
Mathematical Solution ◽  
Accumulated Reward ◽  
Finite Planning Horizon

Abstract This paper describes the optimization of preventive maintenance (PM) over a finite planning horizon in a semi-Markov framework. In this framework, the asset may be operating, and providing income for the asset owner, or not operating and undergoing PM, or not operating and undergoing corrective maintenance following failure. PM is triggered when the asset has been operating for τ time units. A number m of transitions specifies the finite horizon. This system is described with a set of recurrence relations, and their z-transform is used to determine the value of τ that maximizes the average accumulated reward over the horizon. We study under what conditions a solution can be found, and for those specific cases the solution τ* is calculated. Despite the complexity of the mathematical solution, the result obtained allows the analyst to provide a quick and easy-to-use tool for practical application in many real-world cases. To demonstrate this, the method has been implemented for a case study, and its accuracy and practical implementation were tested using Monte Carlo simulation and direct calculation.

scholarly journals Preventive maintenance policy on leasing by considering the usage rate

2018 ◽  
Vol 204 ◽  
pp. 02016
Author(s):  
Moh. Jufriyanto ◽  
Nani Kurniati ◽  
Ade Supriatna
Keyword(s):  
Preventive Maintenance ◽  
Failure Time ◽  
Equipment Failure ◽  
Maintenance Policy ◽  
Time Duration ◽  
Maintenance Costs ◽  
Operational Conditions ◽  
Penalty Cost ◽  
Usage Rate ◽  
Preventive Maintenance Policy

The needs of the consumers about the functionality of a product and increase maintenance costs of equipment caused the prices of products and treatments to be expensive. Therefore, the company considers the lease rather than buy it. Leasing provides interesting strategy when dealing with expensive equipment. Policy maintenance that is done to the product that has decreased performance. Minimum repair done to fix failed equipment in order to return to operational condition, while imperfect preventive maintenance to improve the operational conditions of the equipment to avoid failure. Time duration for a minimum repair neglected. The lessor will charge a penalty (penalty cost) if the lease equipment failure. Mathematical model built for the minimization cost of maintenance policy. In the final part, the numerical experiment are given to show the maintenance policy taking into account the rate of usage (usage rate) by knowing the minimization the resulting costs.

scholarly journals Asymptomatic individuals can increase the final epidemic size under adaptive human behavior

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Baltazar Espinoza ◽  
Madhav Marathe ◽  
Samarth Swarup ◽  
Mugdha Thakur
Keyword(s):  
Planning Horizon ◽  
Infection Risk ◽  
Epidemiological Models ◽  
Epidemic Size ◽  
Behavioral Adaptations ◽  
Future State ◽  
Final Epidemic Size ◽  
Asymptomatic Individuals ◽  
The Impact ◽  
Finite Planning Horizon

AbstractInfections produced by non-symptomatic (pre-symptomatic and asymptomatic) individuals have been identified as major drivers of COVID-19 transmission. Non-symptomatic individuals, unaware of the infection risk they pose to others, may perceive themselves—and be perceived by others—as not presenting a risk of infection. Yet, many epidemiological models currently in use do not include a behavioral component, and do not address the potential consequences of risk misperception. To study the impact of behavioral adaptations to the perceived infection risk, we use a mathematical model that incorporates the behavioral decisions of individuals, based on a projection of the system’s future state over a finite planning horizon. We found that individuals’ risk misperception in the presence of non-symptomatic individuals may increase or reduce the final epidemic size. Moreover, under behavioral response the impact of non-symptomatic infections is modulated by symptomatic individuals’ behavior. Finally, we found that there is an optimal planning horizon that minimizes the final epidemic size.

scholarly journals Green Inventory Supply Chain Model with Inflation under Permissible Delay in Finite Planning Horizon

2019 ◽  
Vol 4 (5) ◽  
pp. 123-131
Author(s):  
Seema Saxena ◽  
Vikramjeet Singh ◽  
Rajesh Kumar Gupta ◽  
Nitin Kumar Mishra ◽  
Pushpinder Singh
Keyword(s):  
Supply Chain ◽  
Planning Horizon ◽  
Chain Model ◽  
Supply Chain Model ◽  
Finite Planning Horizon

Design of robust layout for unequal area dynamic facility layout problems with flexible bays structure

2020 ◽  
Vol 18 (4) ◽  
pp. 361-392
Author(s):  
Irappa Basappa Hunagund ◽  
V. Madhusudanan Pillai ◽  
Ujjani Nagegowda Kempaiah
Keyword(s):  
Simulated Annealing Algorithm ◽  
Facility Layout ◽  
Dynamic Environment ◽  
Planning Horizon ◽  
Content Type ◽  
Robust Approach ◽  
Penalty Cost ◽  
Proposed Model ◽  
Total Penalty ◽  
Flexible Bay Structure

Purpose The purpose of this paper is to develop a mathematical model for the design of robust layout for unequal area-dynamic facility layout problem with flexible bay structure (UA-DFLP with FBS) and test the suitability of generated robust layout in a dynamic environment. Design/methodology/approach This research adopts formulation of a mathematical model for generating a single layout for unequal area facility layout problems with flexible bay structure under dynamic environment. The formulated model for the robust layout formation is solved by developing a simulated annealing algorithm. The proposed robust approach model for UA-DFLP with FBS is validated by conducting numerical experiments on standard UA-DFLPs reported in the literature. The suitability of the generated robust layout in a dynamic environment is tested with total penalty cost criteria. Findings The proposed model has given a better solution for some UA-DFLPs with FBS in comparison with the adaptive approach’s solution reported in the literature. The total penalty cost is within the specified limit given in the literature, for most of the layouts generated for UA-DFLPs with FBS. In the proposed model, there is no rearrangement of facilities in various periods of planning horizon and thus no disruptions in operations. Research limitations/implications The present work has limitations that when the area and aspect ratio of the facilities are required to change from one period to another, then it is not possible to make application of the robust approach-based formulation to the dynamic environment facility layout problems. Practical implications Rearrangement of facilities in adaptive approach disrupts the operations whereas in the proposed approach no disruption of production. The FBS approach is more suitable for layout planning where proper aisle structure is required. The solution of the proposed approach helps to create a proper aisle structure in the detailed layout plan. Thus, easy interaction of the material handling equipment, men and materials is possible. Originality/value This paper proposes a mathematical formulation for the design of robust layout for UA-FLPs with FBS in a dynamic environment and an efficient simulated annealing algorithm as its solution procedure. The proposed robust approach generates a single layout for the entire planning horizon. This approach is more useful for facilities which are difficult/sensitive to relocate in various periods of the planning horizon.

Simulation of Manufacturing Production Line Based on Arena

2014 ◽  
Vol 933 ◽  
pp. 744-748 ◽  
Author(s):  
Seyed Mojib Zahraee ◽  
Saeed Rahimpour Golroudbary ◽  
Ahmad Hashemi ◽  
Jafar Afshar ◽  
Mohammadreza Haghighi
Keyword(s):  
Computer Simulation ◽  
Simulation Model ◽  
Production Line ◽  
Manufacturing Systems ◽  
Waiting Times ◽  
Controversial Issues ◽  
Manufacturing Companies ◽  
Total Cost ◽  
Manufacturing Line

One of the controversial issues in manufacturing systems is bottleneck. Managers and engineers are trying to find methods to eliminate the bottlenecks and waiting times in the production line. More over the manufacturing companies are striving to sustain their competiveness by decreasing the bottlenecks, total cost and increasing the productivity. The objective of this study is applying the computer simulation to analysis the production line bottlenecks. To achieve this goal a color manufacturing line was selected as a case study and the basic application of arena 13.9 software. Finally the some modifications in the simulation model are proposed to improve the production line as well as to decrease the bottleneck.

Order statistics, Poisson processes and repairable systems

1976 ◽  
Vol 13 (03) ◽  
pp. 519-529 ◽  
Author(s):  
Douglas R. Miller
Keyword(s):  
Order Statistics ◽  
Point Processes ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Renewal Processes ◽  
Repairable Systems ◽  
Homogeneous Poisson Process ◽  
Necessary And Sufficient ◽  
Non Homogeneous Poisson Process ◽  
Weibull Process

Necessary and sufficient conditions are presented under which the point processes equivalent to order statistics of n i.i.d. random variables or superpositions of n i.i.d. renewal processes converge to a non-degenerate limiting process as n approaches infinity. The limiting process must be one of three types of non-homogeneous Poisson process, one of which is the Weibull process. These point processes occur as failure-time models in the reliability theory of repairable systems.

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