Effective Maintenance Policy Research Articles

Liquid level detection in porcelain bushing type terminals using piezoelectric transducers based on auto-encoder networks

Liquid level of internal silicone oil is about the safety operation of high voltage porcelain bushing type (PBT) terminals, and its regular inspection can effectively prevent the security risks caused by oil leaks. In this paper, a deep learning detection method based on local wavelet features and unsupervised feature fusion is proposed to quantitatively detect the internal liquid level of high voltage PBT terminals. Firstly, ultrasonic guided wave signals are divided into many segments by a sliding window and all segments are transformed into wavelet domain to catch the local time-frequency information. After preliminary selection according to the monotonic trends, the features are fed into a deep learning method named auto-encoder networks for unsupervised feature fusion. Finally, a two-layer neural network is employed to regress the liquid level based on fused features. The experiments were conducted in different liquid level, and detection data are divided into model training set and testing set. The mean detection error of proposed method is only 0.034 m when the accuracy of training set is 0.1 m, and 0.0543 m when the accuracy of training set is 0.2 m. In liquid level detection experiments, proposed method also shows good robustness in limited training samples condition and low label accuracy condition, and better detection performance than PCA and STFT method. Experimental results demonstrate that proposed method can directly diagnosis the internal liquid level in PBT terminals and provide an effective maintenance policy.

Condition Assessment of Roadway Bridges: From Performance Parameters to Performance Goals

Deterioration of bridges due to ageing and higher demands, induced by increased traffic load, require the development of effective maintenance policies and intervention strategies. Such concern should be aimed at ensuring the required levels of safety, while optimally managing the limited economic resources. This approach requires a transversal advance; from the element level, through the system level, all the way to the network level. At the same time intervention prioritisation based on the importance of the system (bridge) inside the network (e.g. highway), or of the single structural element inside the bridge is dependent. The first step in bridge condition assessment is the verification of safety and reliability requirements that is carried out using the traditional prescriptive (deterministic) approach or the current performance- based (probabilistic) approach. A critical issue for efficient management of infrastructures lies in the available knowledge on condition and performance of bridge asset. This information is obtained using a collection of significant Performance Parameters at one or more of the three levels (element, system, and network). Traditional techniques for estimation of Performance Parameters rely on already established visual inspection. However, a more reliable description of the system performance is obtained through Non-Destructive Testing and Structural Health Monitoring. Condition assessment essentially pertains to the check of compliance with Performance Goals and requires the definition and computation of Performance Indicators. They are calculated directly from Performance Parameters or from physical models calibrated using the Performance Parameters collected on the structure. Paper overviews the steps to bridge condition assessment regarding safety and reliability.

Optimal preventive maintenance strategy for leased equipment under successive usage-based contracts

In the context of equipment leasing, maintenance service is usually bundled with the leased equipment and offered by the lessor as an integrated package under a lease contract. The lessor is then responsible to prescribe an effective maintenance policy to keep the equipment operational in an economical way. This paper investigates upgrade and preventive maintenance (PM) strategies for industrial equipment during successive usage-based lease contracts with consideration of a warranty period, from the lessor's perspective. The accelerated failure time model and age reduction model are adopted to capture the effect of usage rate and imperfect PM/upgrade on the equipment reliability, respectively. More importantly, since equipment usage rates may vary across different lease contracts, this study develops an age correspondence framework to characterise usage rate shifts between successive lease periods. The optimal upgrade degree and the optimal number and level of PM actions are progressively updated for each upcoming lease period to minimise the total expected lease servicing cost, by considering the usage rate and maintenance implementation history. Numerical studies show that under given cost structures, periodical PM activities within each lease period tends to outperform the pre-leasing upgrade actions, though both of them can reduce the lease servicing cost.

A value-based maintenance optimization method for failure prevention based on reliability modeling of a hybrid assembly system

The effective maintenance policy for the fixtures of the assembly system will guarantee good process capability and product quality to a great extent. Traditional maintenance schedules for the assembly system, such as a constant reliability index as the maintenance trigger, are always based on the fixed maintenance threshold in engineering practice. It always results in down time of the process, unqualified products or the excessive maintenance costs. The aim of this paper is to present a method to optimize the maintenance schedules for a serial-parallel hybrid assembly system. Based on the production chain definition of the hybrid system, a reliability evaluation method by integrating the process performance of the hybrid assembly system and product qualities is proposed. On the basis of the reliability method, a value-based preventive maintenance optimization policy for the fixture components is presented to prevent system failures. Compared with the traditional reliability threshold method for maintenance, the proposed maintenance method generates more value on the premise that the system status and product quality are guaranteed. A case study is used to illustrate the proposed method and validate the effectiveness and advantages.

A Just-in-Time Inventory Model with Preventive Maintenance and Defect Rate

In competitive market environments, businesses employ Just-In-Time (JIT) systems not only to reduce costs, but also to enhance their business partnerships. Although product quality level is essential for maintaining competitiveness, traditional inventory models do not consider defect rate, which is the main determinant of product quality. Also, in real working environments, machines break down after long operating times, which increases product defect rate. Therefore, an effective preventive maintenance policy is needed to ensure that machinery is reliable. Reworking defective items is another important inventory problem. To answer the above questions regarding varying defect rate, preventive maintenance and rework, this study developed an integrated two-echelon inventory model to determine the best production quantity, delivery frequency and preventive maintenance schedule under JIT production and delivery policy. The model results can be used to minimize total cost.

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.

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

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

Maintenance and Work-rest Scheduling in Human-machine System According to Fatigue and Reliability

Most manufacturers use human-machine systems to produce high-quality products. Dealing with human-machine systems is very complicated since not only machines should be utilized in proper condition but also appropriate environment should be provided for human resources. Most manufacturers have a maintenance plan for machines but many of them do not have a proper work-rest schedule for human resources. Considering this fact we emphasis on human role in human-machine systems maintenance and propose a mathematical model that obtains the optimal work-rest schedule for humans based on fatigue-recovery models and the optimal maintenance policy for machines based on reliability level. The performance of proposed model was examined by some instances and the obtained results indicate this model can provide effective maintenance policy for human-machine systems.

Educational building conditions and the health of users

In order to maintain a healthy learning environment, diagnosis and management of defects in the educational facility are paramount. The preliminary results of the ongoing research reported here seek to identify defects associated with educational buildings and their effects on the health of polytechnic students and staff in Nigeria. A questionnaire survey, including 34 defects based on a post-occupancy evaluation (POE) was used to establish relationships with the health of polytechnic students and staff. Two hundred (200) respondents were randomly selected based on their schools (faculty) within Lagos State Polytechnic. Descriptive and inferential statistics were used for analysis of the collected data. The results of the study indicate that defects such as plumbing and dampness problems, cobwebs and dust, are prominent in the institution. Also the relationship between building conditions (defects) and health problems was established, with the predictors of the health problems. Based on the findings, it is important for designers and managers of facilities within tertiary institutions to develop and implement design and maintenance policies targeted at minimizing the likelihood of plumbing, dampness, electrical, cobweb and dust problems in educational buildings due to the health risks induced by the defects. It is evident that effective maintenance schedules and policies should be put in place to ensure that facilities are not left to decay before replacement.

Maintenance and work-rest scheduling in Human-machine system according to fatigue and reliability

Most manufacturers use human-machine systems to produce high-quality products. Dealing with human-machine systems is very complicated since not only machines should be utilized in proper condition but also appropriate environment should be provided for human resources. Most manufacturers have a maintenance plan for machines but many of them do not have a proper work-rest schedule for human resources. Considering this fact we emphasis on human role in human-machine systems maintenance and propose a mathematical model that obtains the optimal work-rest schedule for humans based on fatigue-recovery models and the optimal maintenance policy for machines based on reliability level. The performance of proposed model was examined by some instances and the obtained results indicate this model can provide effective maintenance policy for human-machine systems.

Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics.

In numerous industrial applications where safety, efficiency, and reliability are among primary concerns, condition-based maintenance (CBM) is often the most effective and reliable maintenance policy. Prognostics, as one of the key enablers of CBM, involves the core task of estimating the remaining useful life (RUL) of the system. Neural networks-based approaches have produced promising results on RUL estimation, although their performances are influenced by handcrafted features and manually specified parameters. In this paper, we propose a multiobjective deep belief networks ensemble (MODBNE) method. MODBNE employs a multiobjective evolutionary algorithm integrated with the traditional DBN training technique to evolve multiple DBNs simultaneously subject to accuracy and diversity as two conflicting objectives. The eventually evolved DBNs are combined to establish an ensemble model used for RUL estimation, where combination weights are optimized via a single-objective differential evolution algorithm using a task-oriented objective function. We evaluate the proposed method on several prognostic benchmarking data sets and also compare it with some existing approaches. Experimental results demonstrate the superiority of our proposed method.

Optimization of Paper Making System using Genetic Algorithm

Objectives: In the current work, a paper making system has been under consideration for its availability and optimisation. The objective of this paper is to optimize input variables of the paper making system, to maximize system availability. Methods/Analysis: Paper making system consists of mainly, six subsystems connected in series configuration. For analysis, Repair rates, failure rates, Transition rates and PM rates of each subsystem is taken from maintenance history sheets. Markov process with probabilistic approach is used to model the system for availability with ideal PM and faulty PM. Steady state availability is obtained by using normalizing condition. The optimization of a system availability is executed by genetic algorithms. Findings: Findings present in paper show a significant improvement in the system availability. With ideal PM the availability has been increase upto 93.43% whereas in case of faulty PM the availability has been increase upto 91.89%. Novelty/Improvement: The optimization would help the analysts to design and planning more effective preventive maintenance and repair rate policies.

시설물 안전 및 유지관리 성과 평가에 관한 연구 - 시설물 안전등급 변화를 중심으로 -

최근 인프라 투자는 신규 건설 중심에서 기 시공된 시설의 효율적인 운영과 유지관리로 패러다임이 전환되고 있다. 이와 함께 시설물 노후화에 따른 안전에 대한 국민적 관심이 증폭되고 있다. 본 연구에서는 한국시설안전공단의 시설물관리종합정보시스템에 등록되어 있는 1994년부터 2014년까지의 시설물 유지관리 관련 데이터를 바탕으로 점검진단지수와 보수보강지수 등의 정량적 분석 방법론을 적용하여 유지관리 활동의 성과를 평가하였다. 또한 과거에 비해 현재 시설물의 안전도가 어느 정도 향상되었는지 안전등급 데이터를 토대로 분석을 실시하였다. 분석 결과 우리나라 시설물의 안전성은 과거 대비 크게 향상된 것으로 나타났으며 안전성이 향상된 요인으로는 정기적인 안전점검과 그에 따른 보수 보강 활동의 결과로 추정해 볼 수 있다. 본 연구를 통해 도출 된 결과는 향후 시설물의 유지관리 정책 및 전략 수립에서 기초적 자료로 활용이 가능할 것으로 판단된다. Recently, the paradigm shift of new construction into efficient operation and maintenance of infrastructure is seen. Also, concerns about infrastructure safety, especially the aged infrastructure, are on the increase. This study evaluates the current status of infrastructure safety and maintenance using data from 1994 to 2014 in Facility Management System operated by Korea Infrastructure Safety Corporation. Also, a quantitative analysis of safety performance of infrastructure is conducted to find out the enhancement of infrastructure safety in Korea. It was found that safety of facilities in Korea have been enhanced for the past decades. Improvement of safety performance of facilities is attributed to periodic safety inspection and repair and reinforcement. The result of the study can be used as a basic material for efficient and effective facility maintenance policies and strategies.

Stochastic behaviour analysis of power generating unit in thermal power plant using fuzzy methodology

The aim of this research is to study the stochastic behaviour of a PGU (power generating unit) of a medium size coal fired thermal power plant using fuzzy methodology (FM). The PN approach was used to depict series and parallel configurations of the subsystems constituting the PGU. To study the failure dynamics of the considered system, various reliability parameters such as failure rate, repair time, MTBF, ENOF, availability and reliability of the system were computed using fuzzy λ-τ approach. RCA was conducted to determine the failure causes of various subsystems of the PGU. FMEA was carried out to determine the RPN scores of the various failure causes of different components. On the basis of these RPN scores, critical components were identified and ranked on the basis of criticality. Further, the limitations of the traditional FMEA approach were overcome by introducing a Fuzzy decision support system (FDSS). Findings of this study would be communicated to field engineers/system analysts of the considered system to help them understand and anticipate system behavior, and implement appropriate and effective maintenance policies for improving system availability.

Fault Prognosis with Stochastic Modelling on Critical Points of Discrete Processes

The primary role of a machine tool is produce the good quality parts, but a machine tool goes always through a process of degradation and wear which will affect the accuracy and precision of machining and the quality of products. Therefore, monitoring the degradation of machine tool and quantifying its health is very important. The degradation level of a machine can be qualified by an index which is called health indicator (HI). Based on the HI, fault prognosis can provide the Remaining Useful Life (RUL) of machine which is useful for an effective maintenance policy, thus, that helps to increase efficiency of operations and manufacturing. However, the HI is not usually predetermined in most Discrete Manufacturing Processes (DMP). This paper presents a new method of HI extraction based on the degradation reconstruction. The HI is then modeled with a stochastic process. For the online supervision, the RUL is estimated for each inspection time.

Opportunistic maintenance (OM) as a new advancement in maintenance approaches

Purpose – This paper reviews the literature on opportunistic maintenance (OM) as new advance maintenance approach and policy. The purpose of this paper is to conceptually identify common principle and thereby provide absolute definition, concept and characteristics of this policy. Design/methodology/approach – A conceptual analysis was conducted on various literatures to clarify a number of principle and concepts as a method for understanding information on OM. The analysis involves the process of separating the compound terms used in the literatures into a few parts, analyse them and then recombining them to have more clear understanding of the policy. Findings – The paper discussed the maintenance approach, genealogy, principle, concept and applications of OM both in numerical analysis and real industry. OM policy is developed based on combination of age replacement policy and block replacement policy and in practical; OM is applied as the combination of corrective maintenance which is applied when any failure occurred, with preventive maintenance (PM) – a planned and scheduled maintenance approach to prevent failure to happen. Any machine shutdown or stoppages due to failure is the “opportunity” to conduct PM even though it is not as planned. The characterization of OM was provided in order to present its theoretical novelty for researchers and practical significance for industries. Practical implications – To date, there is no publication that reviews the OM in-depth and provides clear understanding on the topic. Therefore, this paper aims to show lineage of OM and the current trend in researches. This discussion will pave the way of new research areas on this optimal maintenance policy. Clear definition and principle of OM provided in this paper will trigger interest in its practicality as well as aid industries to understand and conduct OM in operation plant. Originality/value – This paper discussed the available literature about OM in various perspectives and scopes for further understanding of the topic by maintenance management professionals and researchers. Therefore, OM can be widely studied and applied in real industry as it is an effective and optimal maintenance policy.

The role of maintenance in improving company's competitiveness and profitability

Purpose – The purpose of this paper is to examine the role of maintenance in improving company's competitiveness and profitability. In the first part the paper aims to discuss the potential improvement areas from the company perspective. Second part of this paper examines maintenance impact on company's business. Design/methodology/approach – An empirical case study was utilized aiming to provide an understanding of the role of maintenance in improving company's business. The empirical data for this study were collected from a Slovenian textile company. A gap analysis was used in order to address the research problem and to identify potential improvement areas. Findings – Based on the gap analysis, the results suggest that from respondents’ points of view, maintenance practices related to condition-based maintenance approach represent the highest opportunity for improvement. The most notable empirical results of the case study showed that around 3 per cent of additional profit could be generated at weaving machine, especially if all unplanned stoppages and loss of quality due to decrease in the productivity would be prevented. Practical implications – This paper demonstrates to managers the potential benefits of maintenance policy in terms of productivity, quality and profitability. In this regard, this paper builds on a premise that company can gain higher performance benefits using more effective maintenance policy. Originality/value – The proposed conceptual model contributes to the existing literature by showing the interactions between maintenance and company's competitiveness and profitability. Empirical findings of this study therefore, acknowledge maintenance's potential of increasing the overall profit. In addition this study advances prior studies by utilizing a gap analysis which is rare in this type of research.

Forecasting and maintenance problem under subcontracting constraint with transportation delay

In this paper, a forecasting production/maintenance optimization problem has been proposed with a random demand and single machine M1 on a finite horizon. The function rate of the machine M1 is depending on the production rate for each period of the forecasting horizon. In order to satisfy the customer, a subcontracting assures the rest of the production through machine M2 with transportation delay. An analytic formulation of the problem has been proposed using a sequential computation of the optimal production plan for which an optimal preventive maintenance policy has been calculated based on minimal repair. Firstly, we find, the optimal production plans of principal and subcontracting machines, which minimises the total production and inventory cost for the cases without and with returned products under service level and subcontracting transportation delay. Secondly, we determine a joint effective maintenance policy with the optimal production plan, which integrates the various constraints for the production rates, the transportation delay and the returned production deadline. Numerical results are presented to highlight the application of the developed approach and sensitivity analysis shows the robustness of the model.

English

The National Department of Public Works has the responsibility of providing office accommodation to all state departments nationally, The objectives of the paper are to establish a base for evaluating the performance of the process and secondly investigate the performance against this base. Critical success factors were found to be: Better site search and space management, Effective maintenance policy, Extensive feasibility studies, Standardised lease agreements, Effective property management, Sustainable site procurement and Client-driven service delivery. In the performance evaluation it was found that turn-around times were poor due to lack of resources, asset registers were incomplete, the frequency and quality of maintenance services rendered were unsatisfactory, and the implementation of Public Private Partnerships (PPPs) in the procurement of new sites were not seen as adequate partly due to political pressures. Key words: Office accommodation; state departments; provision of accommodation; process of accommodation, state departments.

An integrated GA-DEA algorithm for determining the most effective maintenance policy for a k -out-of- n problem

This paper presents a novel hybrid GA-DEA algorithm in order to solve multi-objective $$k$$ -out-of- $$n$$ problem and determine preferred policy. The proposed algorithm maximizes overall system reliability and availability, while minimizing system cost and queue length, simultaneously. To meet these objectives, an adaptive hybrid GA-DEA algorithm is developed to identify the optimal solutions and improve computation efficiency. In order to improve computation efficiency genetic algorithm (GA) is used to simulate a series production line and find the Pareto-optimal solutions which are different values of $$k$$ and $$n$$ of $$k$$ -out-of- $$n$$ problem. Data envelopment analysis is used to find the best $$k$$ and $$n$$ from Genetic Algorithm's Pareto solutions. An illustrative example is applied to show the flexibility and effectiveness of the proposed algorithm. The proposed algorithm of this study would help managers to identify the preferred policy considering and investigating various parameters and scenarios in logical time. Also considering different objectives result in Pareto-optimal solutions that would help decision makers to select the preferred solution based on their situation and preference.