Preventive Maintenance Scheduling Research Articles

An Optimal Scheduling for Medical Equipment Preventive Maintenance Over a Finite Planning Horizon Using Ant Colony Algorithm

The importance of preventive maintenance management has been gradually recognized specially with the great attention to the role of health technology management. Finding the optimal schedule to perform preventive maintenance for medical equipment is rarely considered in the literature. This research suggests using ant colony optimization method to solve the problem of finding the optimal preventive maintenance schedule. We developed 2 versions of the algorithm, both starting from a prioritized medical equipment list and differing in the heuristic function. The experimental results indicate the effectiveness of the ant colony optimization algorithm for this kind of problems.

Preventive Maintenance Optimization and Comparison of Genetic Algorithm Models in a Series–Parallel Multi-State System

Abstract In this research, different optimization models are developed to solve the preventive maintenance (PM) optimization problem in a maintainable multi-state series–parallel system. The objective is to determine for each component in the system the maintenance period minimizing a cost function under the constraint of required availability and for a specified horizon of time. Four genetic models based on the cost associated with maintenance schedule and availability characteristic parameters are constructed and analyzed. They are genetic algorithm (GA), hybridization GA and local search (GA-LS), fuzzy logic controlled GA (FLC-GA), and hybridization FLC-GA and LS. The experiment analyzes and compares the efficiency between them. These experiments investigate the effect of the parameters of the GA on the structure of optimal PM schedules in multi-state multi-component series–parallel systems. Results show that the hybridization FLC-GA and LS outperform the other algorithms.

Technical control of digital code autoblock system

The purpose of the work is to identify the characteristic features of the technical control of the digital code autoblock system, their advantages and disadvantages, to analyze the possibility of using them to diagnose the condition of the autoblock devices and to set tasks for the development of new diagnostic complexes.To achieve this goal, a theoretical analytical method and a method of functional analysis were used.The analysis of existing and prospective means of remote control and technical diagnostics of auto-blocking devices showed that existing systems have insufficient information content, they are aimed mainly at controlling discrete parameters, which, in turn, does not allow them to build a subsystem of decision support on their basis. It was proposed to use the centralized-distributed principle of diagnostic data processing to develop a new system of technical diagnostics, to include a decision support subsystem in their structure, which would reduce the amount of effort required to service autoblock devices and shorten the time for recovery after the occurrence of damage .As a result of the research, it was revealed that the existing means of automatic control of automatic blocking can’t provide a full assessment of the condition of the distillation devices of signaling and blocking, and proposed criteria for the development of new systems of technical diagnostics with increasing the number of diagnostic information and its automatic analysis.The results of the analysis can be used in practice to select the means for technical control of autoblock devices, as well as for the further development of autoblock diagnosis systems, which allows a gradual transition from a scheduled preventive maintenance model to maintenance according to the actual state of the monitored devices.

Demand Response Resources' Allocation in Security-Constrained Preventive Maintenance Scheduling via MODM Method

Security-constrained preventive maintenance (PM) scheduling is addressed as a crucial issue particularly coping with new challenges of smart grids. Under the smart grid environment, demand response resources (DRRs) are considered as virtual power plants in energy policy decisions, which affect the controllability of the power system, ranging from short term to long term. In this paper, an economic model of responsive loads is represented based upon price elasticity of demand and customers' benefit function. In order to investigate the impacts of DRRs on PM scheduling, a multiobjective security-constrained PM scheduling incorporating demand response programs (DRPs) is introduced. Total system expenditures, including operation and maintenance costs, reserve cost, and total incentive due to participating in DRPs, are contemplated as the first objective; and the second one is generated emissions over the scheduling time horizon. Utilizing the lexicographic method as one of the multiobjective decision-making techniques, the maintenance scheme, commitment status, energy and reserve scheduling are determined along the scheduling horizon. Furthermore, the actual potential for customers' participation in DRPs, optimum locations, and multifarious optimal incentive in per bus are also derived. Several analyses are carried out on the IEEE-RTS to confirm the capability of the proposed framework.

Integrated scheduling of preventive maintenance and renewal projects for multi-unit systems with grouping and balancing

This paper studies preventive maintenance and renewal scheduling for multi-unit systems. We develop an integrated optimization method to schedule preventive maintenance and renewal projects by grouping them and simultaneously finding the optimal balance between them. Grouping and balancing are resource utilization techniques to reduce the costs of maintenance without reducing the level of maintenance. We next model the problem as a pure integer linear programming formulation to minimize the costs of maintenance and renewal projects and their relevant preparatory works and downtime costs over the planning horizon. We use a numerical experiment with sensitivity analysis to illustrate the model, and the potential cost reductions that using such an integrated model may lead to. Applications of this model arise in the maintenance of railways, roadways, electricity distribution networks, and distributed pipeline assets. Due to the complexity of the model, two heuristic algorithms based on decomposition approach with problem-specific cutting planes are applied to tackle the problem. Experimental results show that our integrated optimization approach performs well in reducing the cost of preparatory works through proper scheduling. Finally, a case study for the maintenance of railway track shows that using our integrated approach reduces the maintenance and renewal costs by up to 14% as compared with the spreadsheet based approach used currently at the operation.

Opportunistic preventive maintenance scheduling for serial-parallel multistage manufacturing systems with multiple streams of deterioration

This paper proposes a novel opportunistic preventive maintenance (PM) scheduling methodology for the serial-parallel multistage manufacturing systems (SP-MMSs), where PM is performed to improve both the reliability and product quality. A SP-MMS has two essential characteristics: (i) the products can go through different process routes; (ii) the deterioration of a machine will not only affect the key product characteristics (KPCs) formed at the current stage but also propagate to downstream stages and then affect the KPCs formed there. Consequently, the propagation of machine deterioration along different routes will generate multiple streams of deterioration. This phenomenon is mathematically modeled to evaluate the quality of final products. The PM scheduling is based on the modeling of total maintenance cost including minimal repair cost, quality loss and PM-related costs. Firstly, a tentative PM schedule is made for each individual machine by minimizing the corresponding total maintenance cost. Secondly, the tentative PM schedules of all machines are further adjusted to obtain the optimal PM schedule for the system by jointly considering the economic dependence and control of final product quality. A case study shows that the methodology can ensure reasonably high reliability and final product quality for the system with a low total maintenance cost.

Bayesian failure-rate modeling and preventive maintenance optimization

New results are derived for the optimal preventive maintenance schedule of a single item over a finite horizon, based on Bayesian models of a failure rate function. Two types of failure rate functions—increasing and bathtub shapes—are considered. For both cases, optimality conditions and efficient algorithms to find an optimal maintenance schedule are given. A Bayesian parametric model for bathtub-shaped failure rate functions is used, while the class of increasing failure rate functions are tackled by an extended gamma process. We illustrate both approaches using real failure time data from the South Texas Project Nuclear Operating Company in Bay City, Texas.

Strategic maintenance scheduling in an islanded microgrid with distributed energy resources

This paper addresses passive and active preventive maintenance scheduling in an islanded microgrid with storage and renewable energy sources. At first, under a centralized framework, a single-level cost-minimization formulation for passive maintenance scheduling is developed and used as a benchmark in the operation. An independent microgrid operator is responsible for the operation in this framework. Then, through a bi-level formulation, the active maintenance scheduling and operation is carried out with profit-maximization objective. These two developed frameworks provide the houses with opportunity to earn profit and the regulator and the operator to analyze the performance of the system. The bi-level formulation is transformed into a single-level problem through Karush–Kuhn–Tucker conditions. Furthermore, the proposed model provides the capability of incorporating condition monitoring data into the operation. The model is validated through a test system and the outcomes demonstrate the advantages, applicability and challenges of utilizing the proposed model.

Joint production and preventive maintenance scheduling for a single degraded machine by considering machine failures

Production scheduling and maintenance planning are two interdependent issues that most often have been investigated independently. Although both preventive maintenance (PM) and minimal repair affect availability and failure rate of a machine, only a few researchers have considered this interdependency in the literature. Furthermore, most of the existing joint production and preventive maintenance scheduling methods assume that machine is available during the planning horizon and consider only a possible level for PM. In this research, an integrated model is proposed that coordinates preventive maintenance planning with single-machine scheduling to minimize the weighted completion time of jobs and maintenance cost, simultaneously. This paper not only considers multiple PM levels with different costs, times and reductions in the hazard rate of the machine, but also assumes that a machine failure may occur at any time. To illustrate the effectiveness of the suggested method, it is compared to two situations of no PM and a single PM level. Eventually, to tackle the suggested problem, multi-objective particle swarm optimization and non-dominated sorting genetic algorithm (NSGA-II) are employed and their parameters are tuned Furthermore, their performances are compared in terms of three metrics criteria.

Toward an Integrated Approach of HV and MV Circuit-Breakers Optimization Maintenance Planning and Reliability Assessment: A Case Study

This paper investigates technical and organizational tools to improve maintenance planning performances. Indeed, maintaining a high level of reliability and availability of a Medium Voltage electrical network protection system such as the Medium Voltage and High Voltage circuit-breaker and its numerical protection relay at a low operating expenses cost is one of the most critical and challenging tasks for MV electrical distribution network operators. This work has mainly two goals. Firstly, to propose an operating expenses budget function that evaluates the Planned Scheduled Preventive Maintenance Policy combined with a Condition-based maintenance fora real series-parallel multi-assets MV electrical distribution system with active redundancy under the reliability and the maintenance frequency visits of these components. Secondly, to implement an integrated genetic algorithm approach in order to look for the optimal perfect and planned preventive maintenance scheduling policy and condition-based maintenance that minimizes the maximum operating expenses cost of the entire system.The method determines the optimal schedule of preventive maintenance actions based on minimization both reliabilty and operating expenses costs. Conclusions and recommendations for practice are made on the basis of obtained results.

Lease-Oriented Opportunistic Maintenance for Multi-Unit Leased Systems Under Product-Service Paradigm

With many industries increasingly relying on leased equipment and machinery, many original equipment manufacturers (OEMs) are turning to product-service packages where they deliver (typically lease) the physical assets. An integrated service contract will be offered for the asset. A classic example being Rolls Royce power-by-the-hour aircraft engines. Service contracts offered by original equipment manufacturers have predominantly focused on maintenance and upkeep activities for a single asset. Interestingly enough, manufacturing industries are beginning to adopt the product-service paradigm. However, one of the unique aspects in manufacturing settings is that the leased system is often not a single asset but instead a multi-unit system (e.g., an entire production line). In this paper, we develop a lease-oriented maintenance methodology for multi-unit leased systems under product-service paradigm. Unlike traditional maintenance models, we propose a leasing profit optimization (LPO) policy to adaptively compute optimal preventive maintenance (PM) schedules that capture the following dynamics: (1) the structural dependencies of the multi-unit system, (2) opportunistic maintenance of multiple system components, and (3) leasing profit savings (LPSs). We demonstrate the performance of our multi-unit maintenance policy by using a leased automotive manufacturing line and investigate its impact on leasing profits.

An uncertain programming model for preventive maintenance scheduling

PurposeThe purpose of this paper is to illustrate an uncertain programming model for scheduling of preventive maintenance (PM) actions. The PM scheduling, in which PM actions are performed under fixed intervals, is solved by grey systems theory.Design/methodology/approachThe paper applied the grey evaluation method based on triangular whitenization weight functions which includes two classes: endpoint evaluation method and center-point evaluation method.FindingsTwo methods give the same results based on endpoint and center-point triangular whitenization weight functions. For validation, the results were compared by Cassady’s method.Originality/valueThe scheduling of PM is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. It is helpful to reduce the outage loss on frequent repair/replacement parts and avoid lack of maintenance of the equipment by controlling the equipment maintenance frequency.

Joint optimization of preventive maintenance and production scheduling for parallel machines system

Joint optimization of preventive maintenance and production scheduling for parallel machines system

Preventive Maintenance Scheduling Sequence for Bottleneck Equipment in a Manufacturing Line

This paper analyzes preventive maintenance scheduling of bottleneck equipment in a line concept of a wafer manufacturing line that has buffer in between equipment. After the start-up of the manufacturing, it has implemented time based maintenance and counter based maintenance without any fix sequence. The maintenance team will select in advance the date and time of the actual preventive maintenance to be perform and making sure all resources are planned. Then maintenance team implemented a Preventive Maintenance sequence which gives the lowest impact in production loss without sacrificing equipment’s quality and safety. This Preventive Maintenance Scheduling sequence is the best suitable method for manufacturing equipment that has buffer in between equipment which is arranged in a line concept. It has also been tested and proven in a wafer manufacturing industry.

Assessment of Equipment Utilization and Maintenance Schedule at a Dental Institution in Bengaluru, India

ABSTRACT Introduction Quality of diagnostic and treatment care provided to patients largely depends on the availability of sophisticated medical equipment. Regular equipment maintenance helps in providing quality care and maintaining utilization coefficient (UC) of the medical equipment. Equipment utilization is the evaluation of medical equipment necessity, appropriateness, and efficiency of the use in diagnosing and treating a patient. If equipment shows UC of more than 50%, it is said to be a good investment. Objective To assess UC of dental institution equipment along with their maintenance schedule to increase operational efficiency. Materials and methods An observational study was conducted at a 250 chaired dental institution in Bengaluru in 2015 to calculate the use coefficient of medical equipment. Maintenance schedule was also recorded for all the equipment. Necessary permissions were obtained before starting the study. Results Around 50% of these medical equipments were underutilized. Only four equipments had preventive maintenance schedule under which services usually provided every 4 months. Most of the equipment did not have any maintenance contract. Conclusion It should be an earnest endeavor of the management and users to optimize the equipment utilization to obtain maximum return on capital invested. In an era of cost-intensive medical care, every equipment being installed in health care institutions need to be fully and properly utilized. Clinical Significance Findings of this study will enable the administrators to ensure that the equipment is in proper working condition to provide optimal patient care. How to cite this article Gupta V, Gupta N, Sarode GS, Sarode SC, Patil S. Assessment of Equipment Utilization and Maintenance Schedule at a Dental Institution in Bengaluru, India. World J Dent 2017;8(2):104-108.

A 0/1 mixed integer linear programming approach to establish an effective preventive maintenance policy for power plant

Most generating unit maintenance scheduling packages consider the preventive maintenance schedule of generating units over a one or two year operational planning period in order to minimise the total operating cost while satisfying system energy requirements and maintenance constraints. This problem consists of ascertaining which generating units must be halt production. The generating unit is to be examined regularly for safety. It is very important because a failure in a power station may cause a general breakdown in an electric network. The main consequence is that the electricity demand of customers will not be satisfied in such cases. Therefore, reliability is the key point used in the methodology presented. The problem is approached as an optimisation issue. The model is developed by determining the objective function which is the net unit power reserve. Some constraints are used to obtain desired output.0/1 mixed integer linear programming is used to solve the model reached. A practical approach is carried out by implementing the model in a power plant. The result obtained is a schedule that allows the efficient organisation of preventive maintenance over a specific time.

Implementing a Preventive Maintenance Planning Model for Computer Numerical Control (CNC) Milling Machine

Preventive maintenance is early access or pre-planned maintenance of the problems occur in any machinery units and it has become the important part of today’s industry to avoid breakdown as it can save costly faults, keep Continues production with standardize machinery, reduce waste and also important for safety of deployment. The paper describes the way to avoid breakdown in CNC’s by using time based scheduled preventive maintenance for different parameters, while taking 20 CNC machines under observation. PM sheet of CNC’s is divided into parts over time for different parameters like chuck pressure inspection is kept in daily basis list while ATC Arm in 4 month check list. Some parameters set on the basis of theoretical studies of material fatigue life and some on experimental basis in the resultant sheet. The developed sheet could help manufacturers to figure out the problems in CNC’s on their usage over time range, simply the sheet can be taken as survey of performance of CNC’s. Also a proper planed PM sheet can save a valuable amount of money on maintenance.

Appraisal of eco-friendly Preventive Maintenance scheduling strategy impacts on GHG emissions mitigation in smart grids

The electricity sector as a crucial source of GHGs (Greenhouse Gases) plays a pivotal role in energy and climate policies. In this regard, specialists endeavor to present a comprehensive and efficient plan including environmental as well as economic aspects. However, in a smart energy system, an ability to control both supply-side and demand-side is provided. This paper presents a methodology of economic and emission PM (Preventive Maintenance) scheduling while concentrating on DRRs (Demand Response Resources) as one of the aspects of smart environments to handle emitted GHGs and expenditures. The nominated structure aims to minimizing system expenditures as well as GHGs emissions over the time horizon. In one hand, PM scheduling is a highly complicated problem and, DRRs consideration makes it even more complicated; overcome this complexity, the problem is implemented in GAMS (General Algebraic Modeling System) environment. Furthermore, the compromise between multifarious targets is performed by Entropy technique to reflect system conditions, while arbitrary compromising cannot be an acceptable solution. In order to evaluate the capability of DRRs in declining GHGs as well as expenditures, it has been applied to IEEE-RTS. The results indicate that considerable reduction is occurred by increasing the number of DRRs in the system.

A Genetic Algorithm Approach for Multi-category Preventive Maintenance Scheduling

In the literature, preventive maintenance (PM) tasks are treated as one category of work such that they were interchangeable in scheduling. It is not practical in the real production system as different categories of maintenance tasks should be independent. Thus, this work modeled a new Production-Maintenance Scheduling (PMS) problem that considered different categories of maintenance with different maintenance intervals and durations. To solve the new problem, we developed a genetic algorithms approach named the Second Generation of Genetic Algorithms with Dominant Gene (GADGII). The numerical results showed that the proposed GADGII outperforms the traditional GADG with shorter makespans.

Maintenance Cost Optimization of Faulty Gearbox under Continuous Vibration Measurement Monitoring

Maintenance management for the gearbox systems aims at reducing the overall maintenance cost and improving the availability of the systems. Since the maintenance costs represent a substantial portion of the total life cycle costs, reliability and maintenance management of the gearbox systems have drawn increasing interests for the reduction of these costs. This paper considers a condition-based maintenance optimization for continuously degrading systems under continuous rotational vibration acceleration monitoring. After maintenance, the states of the system are randomly distributed with residual damage. An optimization technique is used to solve the preventive maintenance problem for faulty (cracked) gear tooth system. The situations where cracked gear tooth system has several ranges of performance levels are considered. To enhance cracked gear tooth system availability, possible preventive maintenance schedules are performed and affect strongly the effective age. Moreover, the technique is used to generate an optimal sequence of maintenance actions providing system working with the desired level of reliability during its lifetime with minimal maintenance cost rate. A single stage gearbox is used for this study, where multi-time tests were carried on healthy and faulty gearboxes individually. The measured and filtered rotational vibration acceleration was collected where hazard lifetime (LT) was determined at failure based on the Weibull distribution with assured reliability. The results indicate that the saving expected costs of either health or faulty gearbox, the basic maintenance cost (C), availability (AV) and maintenance basic cost and availability (CAV) savings have been estimated. On the other hand, the operating time between failure and optimum points for C, AV and CAV savings are all considered.