Preventive Maintenance Tasks Research Articles

A branch and bound algorithm to minimize total tardiness of jobs in a two identical-parallel-machine scheduling problem with a machine availability constraint

This research focuses on the problem of scheduling jobs on two identical parallel machines that are not continuously available with the objective of minimizing total tardiness. After processing a given number of jobs, each machine requires a preventive maintenance task, during which the machine cannot process jobs. We present dominance properties and lower bounds, and develop a branch and bound algorithm using these properties and lower bounds as well as an upper bound obtained from a heuristic algorithm. Performance of the algorithm is evaluated through a series of computational experiments on randomly generated instances and results are reported.

Production Planning and WIP Assignment for Wafer Fabrication Tools With Availability Constraints

This paper deals with a short-term production plan of a single toolset during a shift at a semiconductor fabrication plant. We propose a cost-based optimization model that seeks to minimize the cost of the shift while meeting the following conditions: 1) the shift produces its required output, measured in work-in-process (WIP) levels; 2) preventive maintenance (PM) tasks are carried out in compliance with the manufacturer's recommended PM policy; and 3) the equipment undergoes cleaning operations, as recommended by the manufacturer, in a way that minimizes the production of blank wafers (a by-product of the cleaning process). A linear programming model is formulated and a practical procedure is provided to solve this production plan problem. Data from a real fab are used to demonstrate the optimality and applicability of the proposed approach. Results of various sensitivity analyzes further demonstrate how the model can be used to analyze the impact of changes in cost parameters, WIP levels and production rate parameters on the optimal solution.

Combining Reliability-Centered Maintenance with Planning Methodology and Applications in Hard Chrome Plating Plants

This article explains the application of the Reliability-Centered Maintenance (RCM) approach to developing maintenance planning in Hard Chrome Plating plants. The key to the RCM purpose is an effectual maintenance planning of plant components inherent in their reliability value. Also, this research aims to reduce machine downtime maintenance that stems from machine breakdown and to select preventive maintenance activities based on the engineering reliability for the machine parts. The first step of the research involves setting a priority for critical parts of the Hard Chrome Plating machine. After that, we analyze the damage and risk level data by using Failure Mode and Effects Analysis (FMEA) for calculating a suitable reliability parameter. The final step is to select the preventive maintenance task. As a result of this research, the failure rate of the plant can be reduced 9.22% and the machine availability rate of the plant is increased to 80.34% accordingly. Following this theme, a maintenance plan for the plant is conducted with respect to this RCM concept. Application of the RCM approach revealed that the key time between plant equipment failures and the likelihood of abrupt equipment failures are reduced.

An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks

Offshore wind turbine blades are subject to multiple types of internal and external damages. Internal damages (such as fatigue, wear and cracks) are generally caused by system degradation, whereas the external damages (such as icing, wind and wave shocks) result from harsh marine environments. In this paper, we investigate an optimal opportunistic condition-based maintenance (OCBM) policy for a multi-bladed offshore wind turbine system subjected to stress corrosion cracking (SCC) and environmental shocks. When the length of a crack in a blade reaches critical size D, the blade breaks and it has to be replaced by a new one. An environmental shock is minor with probability 1−p and catastrophic with probability p (0≤p≤1). A minor shock causes an instant drop in power output without resulting in any system failure, whereas a catastrophic shock stops the wind turbine and requires system replacement. When the length of a crack in one of the blades exceeds a threshold d (<D), it undergoes a major repair and a preventive maintenance (PM) action is performed on the other blade(s); otherwise, a planned PM task is conducted for the whole system when its operational age attains a value of T (>0). The problem is to simultaneously determine the optimal control parameters d⁎ and T⁎ such that the average long-run maintenance cost per blade per unit time is minimized. The explicit expression of the objective function is derived and under certain conditions, the existence and uniqueness of the optimal solution are shown for the infinite-horizon case. The proposed maintenance model is tested on a three-bladed wind turbine and its performance over the system life cycle is evaluated using a Monte-Carlo simulation technique.

A degradation model for maintenance improvement in respect of cost and availability

Purpose – The purpose of this paper is to highlight the need for degradation data in order to improve the reliability and the mean residual life estimation of a specific item of equipment and to adapt the preventive maintenance tasks accordingly. Design/methodology/approach – An initial reliability model which uses a degradation-based reliability model that is built from the collection of hitting times of a failure threshold. The proposed maintenance model is based on the cost/availability criterion. The estimation of both reliability and optimum time for preventive maintenance are updated with all new degradation data that are collected during operating time. Findings – An improvement for the occurrences of maintenance tasks which minimizes the mean cost per unit of time and increases the availability. Practical implications – Inspection tasks to measure the degradation level should be realized at least one time for each item of equipment at a specific time determined by the proposed methodology. Originality/value – The introduction of a criterion which helps the maintainer to decide to postpone or not the preventive replacement time depending on the measured degradation level of a specific item of equipment.

Optimal Preventive Maintenance Planning for Water Spray System of Drum Shearer

Water spray system is one of the most important parts of rock cutting machines, especially the drum shearer. Field data shows that the maintenance of this system is time-consuming and causes major downtimes in the coal mines’ production process. Therefore, it is essential to find an optimum preventive maintenance task and intervals, to reduce the downtime and minimize the associated costs of the machine. In this paper, in order to suggest an optimum preventive maintenance plan, a parametric failure and reliability analysis was done on available data from an Iranian longwall coal mine over the two years. A reliability-based cost modelling was implemented to identify the optimum maintenance interval and frequencies of restoration for the water spray system. In the study, a cost rate function was introduced in which an as-good-as-new effectiveness for restoration actions is considered. The results of the analysis showed that the minimum maintenance cost per unit of time for the studied machine, $19.54/hour, will be achieved within a range of intervals i.e. T=136 hours to T=142 hours.

Preventive Maintenance Scheduling for Multicogeneration Plants with Production Constraints Using Genetic Algorithms

This paper describes a method developed to schedule the preventive maintenance tasks of the generation and desalination units in separate and linked cogeneration plants provided that all the necessary maintenance and production constraints are satisfied. The proposed methodology is used to generate two preventing maintenance schedules, one for electricity and the other for distiller. Two types of crossover operators were adopted, 2-point and 4-point. The objective function of the model is to maximize the available number of operational units in each plant. The results obtained were satisfying the problem parameters. However, 4-point slightly produce better solution than 2-point ones for both electricity and water distiller. The performance as well as the effectiveness of the genetic algorithm in solving preventive maintenance scheduling is applied and tested on a real system of 21 units for electricity and 21 units for water. The results presented here show a great potential for utility applications for effective energy management over a time horizon of 52 weeks. The model presented is an effective decision tool that optimizes the solution of the maintenance scheduling problem for cogeneration plants under maintenance and production constraints.

Heuristic for production scheduling on job-shop plants considering preventive maintenance tasks

Heuristic for production scheduling on job-shop plants considering preventive maintenance tasks

Heuristic for production scheduling on job-shop plants considering preventive maintenance tasks

The simultaneous analysis of production scheduling and preventive maintenance task attracts special attention of researchers due to its complexity and therefore the necessity to seek efficient methods for solving this kind of combinatorial problems. This paper presents a heuristic approach to solve this issue on job shop plants. The solution method includes a linear programming model, based on the Traveling

A condition-based maintenance of a dependent degradation-threshold-shock model in a system with multiple degradation processes

This paper proposes a condition-based maintenance strategy for a system subject to two dependent causes of failure: degradation and sudden shocks. The internal degradation is reflected by the presence of multiple degradation processes in the system. Degradation processes start at random times following a Non-homogeneous Poisson process and their growths are modelled by using a gamma process. When the deterioration level of a degradation process exceeds a predetermined value, we assume that a degradation failure occurs. Furthermore, the system is subject to sudden shocks that arrive at the system following a Doubly Stochastic Poisson Process. A sudden shock provokes the total breakdown of the system. Thus, the state of the system is evaluated at inspection times and different maintenance tasks can be carried out. If the system is still working at an inspection time, a preventive maintenance task is performed if the deterioration level of a degradation process exceeds a certain threshold. A corrective maintenance task is performed if the system is down at an inspection time. A preventive (corrective) maintenance task implies the replacement of the system by a new one. Under this maintenance strategy, the expected cost rate function is obtained. A numerical example illustrates the analytical results.

Effect of preventive maintenance intervals on reliability and maintenance costs of wind turbine gearboxes

AbstractAs many of the installed wind turbines (WTs) get older or approach their design life, there will be a drive to keep extending the lives of the main components especially the gearbox. The challenge of operations and maintenance will potentially be even more as there will be a need to keep the cost to a minimum. Similarly, as years of experience of operating WTs accumulate, knowledge about the behaviour and failure of subsystems is gained as well. Also with good documentation and repository of historical operational, performance and failure data, future decisions of operations and maintenance can be taken on the basis of insights from past experience. This paper presents an approach for implementing preventive maintenance (PM) by using historical failure data to determine the optimal PM interval required to maintain desired reliability of a typical module or subassembly. This paper builds upon previous research in the area of WT gearbox reliability analysis and prediction, taking it further by examining the relationships between the frequency of a PM task and the reliability, availability and maintenance costs. The approach presented demonstrates how historical in‐service failure data can be used in PM task selection based on the minimum maintenance cost and maximum availability. Available historical field failure data of the high speed module of a Vestas 2MW WT gearbox is used to validate the approach and show its practicality. The results of this study are then presented—indicating that choosing the right PM interval based on the minimum unit maintenance cost and maximum availability also improves WT gearbox reliability. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Lot Streaming and Preventive Maintenance in a Multiple Product Permutation Flow Shop with Intermingling

A mathematical model forlot streaming problem with preventive maintenance was proposed. A mixed-integer linear model for multiple-product lot streaming problems was also developed. Mixed-integer programming formulation was presented which will enable the user to identify optimal sublot sizes and sequences simultaneously. Two situations were considered:1) all machines were available, and 2) all machines needed preventive maintenance tasks. For both situations a new mixed-integer formulation was developed. To demonstrate the practicality of the proposed model, numerical example was used. It showed that the percentage of make span reduction due to lot streaming in permutation flow shop is 54% when compared to consistent sublots with intermingling case.

Mixed-integer Formulation for Integration of Lot Sizing and Lot Streaming Problem with Scheduled Preventive Maintenance

In this study, a mathematical model for the integration of lot sizing and flow shop scheduling with lot streaming was proposed. A mixed-integer linear model for multi-product lot sizing and lot streaming problem was developed. Mixed-integer programming formulation is proposed which will enable user to identify optimal production quantities, inventory levels, sub lot sizes and sequences simultaneously. Two situations where considered: 1) all machines are available and 2) all machines need preventive maintenance tasks. For both situations a new mixed-integer formulation is developed. To demonstrate the practicality of the proposed model, numerical example was used. It is shown that, the best makespan can be achieved through consistent sublots with intermingling cases as compared to non-intermingling cases.

Smart manufacturing: Handling preventive actuator maintenance and economics using model predictive control

Integrating components and systems of the manufacturing process is an important area of research to enable the future development and deployment of the Smart Manufacturing paradigm. An economic model predictive control (EMPC) scheme is proposed that effectively integrates scheduled preventive control actuator maintenance, process economics, and process control into a unified methodology. To accomplish this goal, a Lyapunov‐based EMPC (LEMPC) scheme is formulated for handling changing number of online actuators (i.e., changing number of manipulated inputs). Closed‐loop stability under the proposed LEMPC is proven. Subsequently, the LEMPC is applied to a chemical process network used for benzene alkylation to demonstrate that the LEMPC can maintain stability and improve dynamic economic performance of the process network in the presence of changing number of available control actuators resulting from scheduled preventive maintenance tasks. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2179–2196, 2014

RELIABILITY-CENTERED MAINTENANCE FOR SPRAY JETS OF COAL SHEARER MACHINE

Spray jets constitute one of the most important parts of each type of rock cutting machine, especially the drum shearer. This system cools the cutting picks and controls the dust emission. The blockage of spray jets causes the coal shearer machine to stop automatically. Therefore, the reliable performance of this system assists the achievement of a smooth coal cutting operation. Field's data shows that the maintenance of this system is time-consuming and causes major downtimes in the production process. Therefore, it is essential to find an optimum preventive maintenance task and intervals, to reduce the downtime and minimize the associated costs of the machine. The aim of this paper is to identify an applicable and effective maintenance task, with its associated interval, for management of the failure modes of the spray jets of coal shearers. A case study has been conducted on spray jets of double-drum shearer machine in Tabas Coal Mine in Iran. In the study, the RCM approach is used to select an applicable and effective maintenance task. The failure data were analyzed using a parametric approach to evaluate the reliability of the spray jets, and to estimate the reliability parameters. A reliability-based cost modeling has been implemented to identify the optimum maintenance interval and frequencies of restoration for the spray jets. In the study, a cost rate function (CRF) has been introduced in which an as-good-as-new (AGAN) effectiveness for restoration actions is considered. The CRF also considers restoration and repair times, and takes into account the costs associated with repair and restoration, and the opportunity cost of the equipment's lost production due to maintenance downtime, to arrive at the most cost-effective maintenance intervals. The results of the analysis have shown that the minimum cost per unit of time, $46.5/h, will be achieved within a range of intervals i.e., T = 210 h to T = 260 h .

Evaluation of the adequacy of maintenance tasks using the failure consequences of railroad vehicles

The purpose of this study is to improve the efficiency, reliability and safety related to railroad maintenance tasks through an evaluation of the consequences of failures. The brake system was selected based on the failure data obtained from railroad vehicles in operation as one of the safety systems in railroad vehicles. The failure causes, failure effects, and the criticality of the failure mode were drawn for 62 failure modes of the braking system through the use of an FMECA for the 30 sub-devices having primary functions. The various maintenance tasks for the braking system were categorized into the 62 failure modes and failure consequences using the FMECA and the logic of maintenance decisions. Braking systems manufactured by the same manufacturer and operated by two different operators were studied in an effort to analyze preventive maintenance and to evaluate the adequacy of preventive maintenance tasks for the 62 failure modes. Based on results of the evaluation of these preventive maintenance tasks, new maintenance tasks were proposed, and concrete cost-cutting effects were determined from the calculation of the maintenance time and expected costs, using a preventive maintenance template developed specifically for railroad vehicles.

OPTIMISING COMBAT TRACKED VEHICLE MAINTENANCE WITH RCM

The article deals with the application of the RCM methodology in this case of combat tracked vehicles used in the Czech Republic Armed Forces and with the problems which appeared during the project, and it describes procedures how to solve them. A practical application of the methodology is demonstrated with the example of the vehicle drive-train. Using the RCM methodology, relatively simple design adjustments were recommended and a package of preventive maintenance tasks was developed to effectively reduce the intensity of the drive-train’s failures and its maintenance costs. The results of the analysis of the drive-train failures also showed that the time schedule of some time-directed tasks of preventive maintenance is not established well. Based on the results of the vehicle monitoring, a model describing the LCC dependence on the duration of time interval to the accomplishment of such preventive maintenance tasks was presented. The proposed model then enabled one to optimise the periodicity of scheduled preventive maintenance. In practice, a set of suggested measures in the area of design and preventive maintenance was implemented. The results of the subsequent monitoring of the vehicles in service show that the implementation of the recommended measures resulted in the improvement of vehicle availability as well as in the reduction of its LCC.

A joint production scheduling approach considering multiple resources and preventive maintenance tasks

In reality, preventive maintenance (PM) tasks usually include lubrication, cleaning, inspection, adjustment, alignment and/or replacement. They should be planned before failure occurs, aiming to improve the overall reliability and availability of the production system. In the literature on PM scheduling, researchers usually consider maintenance as a single task and schedule it together with the production schedule. This may result in poor predictions on maintenance scheduling since different kinds of PM tasks have different maintenance intervals and require different durations. Production also involves various kinds of resources, such as plastics production requiring injection machines and moulds. These resources require different sets of maintenance treatment. If maintenance schedules for different resources are not harmonised, the planned production will be disturbed dramatically by the non-availability of resources. In this aspect, this paper proposes a joint scheduling (JS) method to handle production–maintenance scheduling that considers multiple resources and maintenance tasks. A genetic algorithm approach is applied to hypothetical numerical examples with the objective of minimising the makespan. The numerical solutions obtained show that the proposed JS method significantly reduces the makespan in this new scheduling problem.

A bi-criteria flow-shop scheduling with preventive maintenance

In this study, a bi-criteria flow-shop scheduling with preventive maintenance tasks is considered. The objective function of the scheduling is the minimization of the makespan and for the preventive maintenance is the minimization of the sum of the earliness and tardiness between theoretical and actual frequency for two machines. The integer programming model is presented and can be solved only small size problems. For large size problem, four meta-heuristics methods are presented. Two genetic algorithms (NSGAII and SPEAII) are implemented. 2 new versions of NSGAII (noted HY-NSGAII) and SPEAII (noted HY-SPEAII) based on Johnson algorithm are presented. To evaluate the proposed approaches several tests and metrics are proposed.

Optimized Midterm Preventive Maintenance Outage Scheduling of Thermal Generating Units

This paper addresses the midterm preventive maintenance outage scheduling problem of thermal generating units which is becoming increasingly important due to the aging of power generation fleet. In this context, a novel midterm preventive maintenance outage scheduler is proposed based on decision tree and mixed integer linear formation which explicitly considers the thermal units aging momentum in terms of failure rate. This allows the system operators to determine the thermal units' maintenance outage window based on the cost/benefit analysis of preventive maintenance tasks while optimizing the time interval between consecutive maintenance tasks. Additionally, the division of the year-long midterm horizon into several time blocks in the proposed model provides a unique opportunity for parallel processing and computational saving. The proposed approach is tested on the IEEE Reliability Test System (IEEE-RTS). The results presented reveal the accuracy and efficiency of the proposed approach.