Minimum Maintenance Cost Research Articles

A Study on the Contact Ellipse and the Contact Pressure During the Wheel Wear through Passing the Tracks including Several Sharp Curves

Wheel wear has been a concern in the railway for several decades. Studying the form change of the wheel/rail contacts in particular railways consisting of sharp curves helps to identify the risk of severe or catastrophic wear to minimize maintenance costs in order to be competitive in the transportation business. In this paper, the wheel/rail contact was studied on the particular railways. The experimental measurement of wheel profiles was used as an input to Hertz Contact Theory (HCT). It was found that: 1) for these railways the wheel flange is highly worn; 2) a 5th order polynomial function is appropriate to model the wear behavior of the critical wheel; 3) the minimum and maximum contact ellipse surface areas occur in Sd=22.29 mm and Sd=32 mm, respectively; 4) the maximum and minimum surface areas of the contact ellipse occur at points in which the contact pressure are minimum and maximum, respectively; and finally 5) the flange thickness region between 25 to 29 mm can be chosen as an appropriate range for the wheel maintenance purposes.

Quantitative analysis of a conceptual system dynamics maintenance performance model using multi-objective optimisation

This paper presents a quantitative analysis of a conceptual, system dynamics (SD) model by the application of multi-objective optimisation (MOO). The SD model investigates the strategic development of maintenance performance, using a system view of maintenance costs, while the execution of MOO evaluates multiple simulation runs, seeking the simultaneous trade-off solutions of the three conflicting objectives: maximise availability, minimise maintenance costs, and minimise maintenance consequential costs. The study explores three scenarios that represent companies at different states of developed maintenance performance. The application of this integrated, simulation-based optimisation approach reveals multiple analyses of system behaviour of the SD model, which are presented in a compact format to a decision-maker. Actually, notwithstanding the application to a conceptual model, the study results make explicit the nonlinearity between invested maintenance cost and its consequent effects. Furthermore, the approach demonstrates the contribution to the process of strengthening the usefulness of the conceptual maintenance performance model.

АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ СИСТЕМИ УПРАВЛІННЯ ВИРОБНИЧИМИ ЗАПАСАМИ

Розглянуто проблеми на шляху діяльності виробничого підприємства під час управління запасами та їх аналіз. Вивчено особливості ефективного використання запасів у сучасних умовах. На підставі наукових досліджень учених та практиків виділено показники, які необхідно обчислювати та аналізувати для покращення фінансового стану підприємства. Здійснено аналіз з метою управління запасами за даними конкретного виробничого підприємства

A Goal Programming Optimization Model for The Allocation of Liquid Steel Production

This research was conducted in one of the largest steel companies in Indonesia which has several production units and produces a wide range of steel products. One of the important products in the company is billet steel. The company has four Electric Arc Furnace (EAF) which produces liquid steel which must be procesed further to be billet steel. The billet steel plant needs to make their production process more efficient to increase the productvity. The management has four goals to be achieved and hence the optimal allocation of the liquid steel production is needed to achieve those goals. In this paper, a goal programming optimization model is developed to determine optimal allocation of liquid steel production in each EAF, to satisfy demand in 3 periods and the company goals, namely maximizing the volume of production, minimizing the cost of raw materials, minimizing maintenance costs, maximizing sales revenues, and maximizing production capacity. From the results of optimization, only maximizing production capacity goal can not achieve the target. However, the model developed in this papare can optimally allocate liquid steel so the allocation of production does not exceed the maximum capacity of the machine work hours and maximum production capacity.

Application of chaos discrete particle swarm optimization algorithm on pavement maintenance scheduling problem

Particle swarm optimization (PSO) is one of the most popular and successful optimization algorithms used for solving single objective and multi-objective optimization problems. It is found that the Multi objective particle swarm optimization (MOPSO) has ability to find the optimal solution quickly and more efficient than other optimization algorithms. In this paper, a discrete (binary) MOPSO with chaos methods is developed and applied to pavement maintenance management. The main objective of this research is to find optimal maintenance and rehabilitation plan for flexible pavement with minimum maintenance cost and maximum pavement performance. This research is the first attempt to combine the crossover operation with velocity and position with multi objective PSO algorithm. The results show that the improvements in pavement performance and cost objectives are 94.65 and 54.01% respectively, while the improvement in execution time is 99.9%. In addition, it is found that the developed algorithm is able to converge to the optimal solution quickly, comparing with another PSO algorithm.

Economic Optimal HVAC Design for Hybrid GEOTABS Buildings and CO2 Emissions Analysis

In the early design phase of a building, the task of the Heating, Ventilation and Air Conditioning (HVAC) engineer is to propose an appropriate HVAC system for a given building. This system should provide thermal comfort to the building occupants at all time, meet the building owner’s specific requirements, and have minimal investment, running, maintenance and replacement costs (i.e., the total cost) and energy use or environmental impact. Calculating these different aspects is highly time-consuming and the HVAC engineer will therefore only be able to compare a (very) limited number of alternatives leading to suboptimal designs. This study presents therefore a Python tool that automates the generation of all possible scenarios for given thermal power profiles and energy load and a given database of HVAC components. The tool sizes each scenario properly, computes its present total cost (PC) and the total CO 2 emissions associated with the building energy use. Finally, the different scenarios can be searched and classified to pick the most appropriate scenario. The tool uses static calculations based on standards, manufacturer data and basic assumptions similar to those made by engineers in the early design phase. The current version of the tool is further focused on hybrid GEOTABS building, which combines a GEOthermal heat pump with a Thermally Activated System (TABS). It should further be noted that the tool optimizes the HVAC system but not the building envelope, while, ideally, both should be simultaneously optimized.

A condition-based opportunistic maintenance strategy for multi-component system

As a new dynamic maintenance strategy, the condition-based opportunistic maintenance strategy for multi-component system is presented in this work. In the strategy, the degeneration of each component is described by Weibull proportional hazards model or Weibull proportional intensity model, and the condition indicator is defined to characterize the operating state of each component. Then, when and how to maintain a component can be confirmed by comparing the value of the condition indicator with that of the maintenance threshold function. Condition-based maintenance will be implemented on a component if the value of its condition indicator exceeds that of its condition-based maintenance threshold function. Meanwhile, opportunistic maintenance will also be implemented on a component if the value of its condition indicator exceeds that of its opportunistic maintenance threshold function. The two maintenance threshold functions can be determined by minimizing maintenance cost. Finally, taking the wind turbine as an example of a multi-component system, simulation analyses are described to validate the feasibility and effectiveness of the condition-based opportunistic maintenance strategy.

Relating strategic time horizons and proactiveness in equipment maintenance: a simulation-based optimization study

Identifying sustainable strategies to develop maintenance performance within the short-termism framework is indeed challenging. It requires reinforcing long-term capabilities while managing short-term requirements. This study explores differently applied time horizons when optimizing the tradeoff between conflicting objectives, in maintenance performance, which are: maximize availability, minimize maintenance costs, and minimize maintenance consequence costs. The study has applied multi-objective optimization on a maintenance performance system dynamics model that contains feedback structures that explains reactive and proactive maintenance behavior on a general level. The quantified results provide insights on how different time frames are conditional to enable more or less proactive maintenance behavior in servicing production.

Mathematical Model of Corrective Maintenance Based on Operability Checks for Safety Critical Systems

Maintenance based on equipment operability checks is widely used for technical systems of various physical nature. For commercial and military aircraft such checks are carried-out after a certain amount of time according to specific maintenance programs. Therefore, great attention in the research literature is paid to the mathematical modeling of maintenance on the basis of equipment operability checks. In this study, a mathematical model of corrective maintenance with operability checks at discrete times for the safety critical systems is considered. The criterion of the corrective maintenance effectiveness is proposed to provide a given level of operational reliability with minimum maintenance costs. A finite time interval is considered for modeling the moments of the system operability checks. The graph of decision making is analyzed for imperfect operability checks and the probabilities of possible decisions are determined. Analytical equations for the operational reliability and expected maintenance costs are derived for an arbitrary distribution of time to failure. The criteria of determining optimal policies of sequential checks are formulated. Numerical examples illustrate the developed theory. For the first time it has been shown that conditional probabilities of correct and incorrect decisions when checking system operability are dependent on the time of failure and parameters of the degradation model. Numerical calculations have shown that in the case of mixing deteriorating systems with different initial time points of operation, the interval between operability checks converges to a constant periodicity.

Integration of maintenance systems

Excellence in maintenance is imperative in highly competitive market because it resulted into minimum maintenance cost, high equipment effectiveness, maximum reliability of the system, high quality of the products, low delivery time, high flexibility, safety etc. Any maintenance system such as Total Productive Maintenance (TPM) or Reliability Centered Maintenance (RCM) or Condition Based Maintenance (CBM) alone cannot achieve the excellence in maintenance but its integration may do. In this paper, an integration of TPM, RCM and CBM is proposed with a maintenance policy to take advantage of their respective strengths. A continuously monitored system subject to degradation due to the imperfect maintenance, where a hybrid hazard rate based on the concept of age reduction factor and hazard rate increase factor to predict the evolution of the system reliability in different maintenance cycles has been assumed.A quantitative decision making model for an integrated maintenance system is derived in order to assess the performance of the proposed maintenance policy. Numerical examples of calculation of optimal preventive maintenance age x and preventive maintenance number N* for the given cost ratio of corrective replacement and predictive preventive maintenance are given.

Remaining Useful Life Based Maintenance Policy for Deteriorating Systems Subject to Continuous Degradation and Shock

In this paper, we present a preventive condition-based maintenance (CBM) policy with imperfect maintenance actions. This model not only includes the continuous degradation caused by usage but also the instantaneous degradation due to the random shocks. Moreover, the remaining useful life (RUL) is introduced into the maintenance policy. Based on the estimated RUL, the degradation level at the next inspection moment is adapted to schedule the preventive maintenance action at the current inspection moment. At last, a numerical example is presented to get the minimum maintenance cost per unit of time and a simulation model is analyzed.

The optimization of databases replication in distributed information systems

New mathematical models of optimal distribution of databases replication in nodes of distributed information systems are formulated by the criteria: minimization of maintenance costs; restricted memory resources; minimizing synchronization time; minimizing the average time needed to search information. Precise solutions of the problems with the use of dynamic programming methods are constructed, Bellman recursive equations are obtained. The general scheme of the computational algorithm using the “greedy” choice procedure is presented and an algorithm for improving the obtained result is proposed. The strategies of greedy choice were investigated, the choice of criteria in the strategy of greedy choice is substantiated. The proposals have been formed regarding the formation of a balance between the accuracy and computational complexity of the algorithm through the introduction of a restricted search strategy. The computational complexity of the algorithm is estimated and its correctness is substantiated.

A cooperative PSO-DP approach for the maintenance planning and RBDO of deteriorating structures

Maintenance planning of structures constitutes a multiple stage decision-making process. Different maintenance strategies will produce various reliability profiles throughout the entire lifetime of structures and result in different maintenance costs. The decision-making process is usually a complex procedure, especially when a variety of alternative maintenance types are available. In this paper, a cooperative PSO-DP method (co-PSO-DP) is proposed for obtaining the optimal solution for the multi-stage multi-option maintenance problem, aiming at achieving minimum maintenance costs under the reliability constraints. The dynamic programming (DP), a key methodology in optimal control theory, integrated with particle swarm optimization (PSO) is developed and applied to determine the optimal maintenance strategy for deteriorating and repairable structures. Thereafter, a total life-cycle cost-based (LCC-based) RBDO model is formulated, in which the initial construction cost together with the subsequent maintenance cost is considered simultaneously and both the structural parameters and the maintenance strategy parameters, including the intervention time and options, are taken as the design variables. Again the proposed co-PSO-DP algorithm is applied to identify the optimal solution of the model. Two examples are presented to illustrate the effectiveness of the proposed method. It is shown that the proposed method can efficiently solve the complex maintenance optimization problem with multi-level intervention options. Compared with the results obtained by using the traditional PSO or GA algorithm, the proposed co-PSO-DP approach exhibits better performance with higher efficiency.

A bi-objective model for vessel emergency maintenance under a condition-based maintenance strategy

When sailing on the open seas, far from onshore dockyards, if a crucial part of the ship’s machinery fails, the ship will experience a costly event that carries a high risk of seriously affecting ship operations. If the ship receives warning of an impending defect, then it can try to sail to a dockyard and simultaneously order the spare parts needed to fix the problem. In this paper, we define this type of maintenance situation as ‘vessel emergency maintenance’. It is a complex problem, due to uncertainties with both the machinery condition development and spare parts delivery. To solve this problem, our paper proposes a bi-objective model under a condition-based maintenance strategy, with the aim of simultaneously minimizing maintenance costs and maximizing ship reliability. Maintenance costs include four things: (1) fuel consumption costs; (2) renting extra vessels; (3) shipping delay penalty costs; and (4) spare parts inventory costs. Ship reliability is represented by the reliability of the ship’s main engine, and can be described through a stochastic process. To solve this bi-objective model, we employ a non-dominated sorting genetic algorithm II (NSGA-II) to generate the Pareto optimal front of the two objectives. A numerical experiment is presented to demonstrate the applicability of the proposed model. The results indicate that the proposed model can provide emergency maintenance decision support for ship operators while they are sailing at sea.

Maintenance Optimization of Industrial Chimneys Exposed to Carbonation

Abstract The paper is focused on the deterioration of industrial reinforced concrete chimneys caused by carbonation. It is considered that a chimney has to be repaired when more than 30% of its surface is affected by visible corrosion-induced cracks. An optimal maintenance strategy aims at the postponement of this state beyond the intended service life of the chimney with minimum maintenance costs.

Penentuan Interval Waktu Pemeliharaan Pencegahan pada Peralatan Sub-Unit RKC 3 di PTX Pabrik Tuban

PT X Tuban Plant has four plants (unit), namely Tuban I, Tuban II, Tuban III and Tuban IV. Each unit plant has three sub units, i.e., Crusher Operations Sub-Unit, Raw Mill, Kiln and Coal Mill (RKC) Sub-Unit and Finish Mill Sub-Unit. RKC 3 Sub-Unit in Tuban III has the highest number of equipment downtime and production loss. Therefore, it was necessary to optimize the time interval of preventive maintenance ( ) and total labor force as part of the company maintenance policy, would also fulfill the required reliability and availability of RKC 3 Sub-Unit. There were two steps in determining Tp optimum. The first step was to obtain the best distribution of the time between failures (TBF) and time to repair (TTR). The next step was to iterate the operating time (Ti) and Tp to determine the minimum preventive maintenance cost rate, reliability and maintainability.This iteration was applied to sub-units of RKC 3 that possesses a series system. Tp at the lowest rate of maintenance costs was the optimum Tp. The optimum Tp for RKC 3 Sub-Unit is 3743,28 hour. The preventive maintenance cost rate for optimum Tp is Rp33.100/hour and the reliability and availability of sub unit are 96,7% and 99,86% respectively.Keywords: reliability, availability, preventive maintenance cost rate, and preventive maintenance

White-box modernization of legacy applications: The oracle forms case study

Software modernization consists of transforming legacy applications into modern technologies, mainly to minimize maintenance costs. This transformation often produces a new application that is a poor copy of the legacy due to the degradation of quality attributes, for example. This paper presents a white-box transformation approach that changes the application architecture and the technological stack without losing business value and quality attributes. This approach obtains a technology agnostic model from the original sources, such a model facilitates the architecture configuration before performing the actual transformation of the application into the new technology. The architecture for the new application can be configured considering aspects such as data access, quality attributes, and process. We evaluate our approach through an industrial case study, the gist of which is the transformation of Oracle Forms applications—where the presentation layer is highly coupled to the data access layer—to multitiered applications.

A comparative study on using meta-heuristic algorithms for road maintenance planning: Insights from field study in a developing country

Abstract Optimized road maintenance planning seeks for solutions that can minimize the life-cycle cost of a road network and concurrently maximize pavement condition. Aiming at proposing an optimal set of road maintenance solutions, robust meta-heuristic algorithms are used in research. Two main optimization techniques are applied including single-objective and multi-objective optimization. Genetic algorithms (GA), particle swarm optimization (PSO), and combination of genetic algorithm and particle swarm optimization (GAPSO) as single-objective techniques are used, while the non-domination sorting genetic algorithm II (NSGAII) and multi-objective particle swarm optimization (MOPSO) which are sufficient for solving computationally complex large-size optimization problems as multi-objective techniques are applied and compared. A real case study from the rural transportation network of Iran is employed to illustrate the sufficiency of the optimum algorithm. The formulation of the optimization model is carried out in such a way that a cost-effective maintenance strategy is reached by preserving the performance level of the road network at a desirable level. So, the objective functions are pavement performance maximization and maintenance cost minimization. It is concluded that multi-objective algorithms including non-domination sorting genetic algorithm II (NSGAII) and multi-objective particle swarm optimization performed better than the single objective algorithms due to the capability to balance between both objectives. And between multi-objective algorithms the NSGAII provides the optimum solution for the road maintenance planning.

Design of the new pedestrian and cycleway bridge in Strabane, Northern Ireland

The new pedestrian and cycleway crossing of the River Mourne in Strabane, Northern Ireland is a slender lightweight cable-stayed structure. The bridge is 96 m long in total, with a main span of 80 m. The bridge is characterised by its inclined main tower, curved in elevation and very slender deck profile. This bridge was designed in such a manner to avoid the use of proprietary damping systems that can be employed to avoid the risk of exceedance of serviceability criteria in similar structures with a view to minimising maintenance costs during the life of the structure. This was achieved using careful dynamic analysis of the structure, wind tunnel testing as well as post-construction testing to validate criteria not explicitly dealt with by the codes of practice. This paper describes analysis and testing undertaken for the dynamic design of this bridge resulting in the client's vision being realised.

Online condition monitoring system for substation and service transformers

Deregulation in power industry accelerates competition among various power companies. These companies are trying to gain maximum profit with minimum maintenance cost. This could be achieved by developing a condition-based monitoring product for the assessment of health of substation and service transformers. This study presents online condition monitoring system (OCMS) for transformers which is useful to replace reactive and preventive maintenance of transformers by predictive maintenance. Proposed OCMS is cost effective, online and accurate tool and it has several features like proposing corrective actions for the benefit of power utilities. Proposed system results are evaluated by comparing with the results obtained from utility model. Proposed OCMS applies only to transformers without abnormal faults such as detected by dissolved gas analysis. It is therefore very different from the other health index algorithms present in the market for condition monitoring of transformers, including in case of abnormal faults.