A Case Study of GAMM (Graphical Analysis for Maintenance Management) Applied to Water Pumps in a Sewage Treatment Plant,Chile

This article presents a case for practical application of the GAMM method, which has been developed and published by the authors. The GAMM method supports decision making in the overall maintenance management, through the visualization and graphical analysis of data. In addition, it allows for the identification of anomalous behavior in the equipment analyzed, whether derived from its own operations, maintenance activities, improper use of equipment or even as a result of design errors in the equipment itself. As a basis for analysis, the GAMM method uses a nonparametric estimator of the reliability function using all historical data or, alternatively, part of the history, allowing it to perform an analysis even with limited available data. In the case study presented, the GAMM method has been used to analyze two existing equipment parts in a sewage treatment plant located in Chile. The equipment analyzed were two progressive cavity pumps (BCP) which are part of the industrial process in the treatment plant. Both pumps are the same make and model and subjected to the same maintenance program, but one had a higher failure rate compared to its counterpart. The application of the GAMM method has identified deficiencies in each of the pumps being studied, thus improving decision‐making and problem‐solving process related to the maintenance of the pumps. RCM methodology was used to draft a new maintenance plan. Copyright © 2013 John Wiley & Sons, Ltd.     

Graphical Analysis for Operation Management: A Graphical Method to Support Operation Decision Making

This paper proposes a graphical method to easy decision‐making in industrial plants operations. The proposed tool ‘Graphical Analysis for Operation Management (GAOM) method’ allows to visualizing and analyzing production‐related parameters, integrating assets/systems maintenance aspects. This integration is based on the Total Productive Maintenance model, using its quantitative management techniques for optimal decision‐making in day‐to‐day operations. On the one hand, GAOM monitors possible production target deviations, and on the other, the tool illustrates different aspects to gain control on the production process, such as availability, repair time, cumulative production, or overall equipment effectiveness. Through appropriate information filtering, individual analysis by class of intervention (corrective maintenance, preventive maintenance, or operational intervention) and production level can be developed. Graphical Analysis for Operation Management (GAOM) integrates maintenance information (number of intervention, type of intervention, required/not required stoppage) with production information (cumulative production, cumulative defective products, and cumulative production target) during a certain timeframe (cumulative calendar time, duration of intervention). Then the tool computes basic performance indicators supporting operational decision‐making. GAOM provides interesting graphical outputs using scatter diagrams integrating indicators on the same graph. GAOM is inspired in the Graphical Analysis for Maintenance Management method, published by the authors (LB, AC, and PV) in 2012. Copyright © 2015 John Wiley & Sons, Ltd.     

Analysing Operating Data to Measure the Maintenance Performance*

Effective maintenance decision‐making depends on information obtained by analysing system operating data. In this paper, we present a method to measure the daily, weekly, monthly and long‐term performance of the corrective repair and preventive maintenance by analysing the operating data. Operating data from a bus fleet, served successively in two routes, were observed for over 6 years. The proportional intensity model is used to evaluate the environment effects, which include temperature, humidity and rainfall. Two composite models are proposed to analyse the interplay of events, which include repair/maintenance arrival/finished time, cost, repair/maintenance number and time between failures. A maintenance performance scorecard is developed to present a snapshot of the bus fleet maintenance performance, which can assist maintenance planning and management. Copyright © 2014 John Wiley & Sons, Ltd.     

维修工程管理研究与发展综述

综述了近几十年来维修工程管理的研究与发展，如人工智能、故障诊断、机器状态监测技术(如振动分析、红外检测、热录像仪等)、预测和预防性维修(PPM)、全员生产维修(TPM)和主动性维修(PM)等，论述了综合应用机器实时状态监测与故障诊断、人工智能、计算机通讯技术以及先进的维修管理理念的集成质量控制与维修系统，最后提出一种目前世界领先的远程智能维修系统。内容包括：实践应用中的维修管理评估、智能和集成维修管理、状态监测维修中的智能预测决策支持系统(IPDSS)、设备状况衰退趋势预测——人工神经网络方法、IPDSS支持的维修管理、故障诊断中的人工智能应用、基于可靠性的预防性维修安排和远程智能维修系统。     

Maintenance and Condition-Based Maintenance

1IntroductionSystem reliability and availability have been widely studied in the literature because of their preva-lence in industry systems. Maintaining a high or required level of reliability and availability is oftenan essential requisite.Up to the 1950′s a fix it when it breaks′philosophy (BM, break maintenance) was mostly imple-mented due to lack of engineering knowledge in certain areas. The regular inspection regime of time-based maintenance (PM, preventive maintenance) was later in…     

A full history proportional hazards model for preventive maintenance scheduling

This paper is concerned with the development of a realistic preventive maintenance (PM) scheduling model. A heuristic approach for implementing the semi-parametric proportional-hazards model (PHM) to schedule the next preventive maintenance interval on the basis of the equipment's full condition history is introduced. This heuristic can be used with repairable systems and does not require the unrealistic assumption of renewal during repair, or even during PM. Two PHMs are fitted, for the life of equipment following corrective work and the life of equipment following PM, using appropriate explanatory variables. These models are then used within a simulation framework to schedule the next preventive maintenance interval. Optimal PM schedules are estimated using two different criteria, namely maximizing availability over a single PM interval and over a fixed horizon. History data from a set of four pumps operating in a continuous process industry is also used to demonstrate the proposed approach. The results indicate a higher availability for the recommended schedule than the availability resulting from applying the optimal PM intervals as suggested by using the conventional stationary models. © 1997 John Wiley & Sons, Ltd.     

设备管理及维护信息系统的开发与应用

设备管理及维护信息系统是预防性设备维护的重要基础,对于机械制造企业提高设备管理水平和维护工作效率有重要意义。通过对企业实际情况的深入调查,分析了企业设备管理的信息需求及维护工作业务流程,开发了设备管理及其维护信息系统。该软件系统主要包括系统管理、设备维修资源管理、设备故障信息管理、维修工作管理、维修决策和维修数据分析六部分。该系统已在汽车零部件制造企业中实施。     

Maintenance Strategies and Failure‐Cost Model for Medical Equipment

This paper proposes a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of the equipment. The proposed model is simulated in Scilab using real data extracted from maintenance history of anaesthesia machine from Draeger. The analysis using survival approach reveals that conducting preventive maintenance on the selected medical equipment had a positive impact on survival of equipment. The model is then used to analyse the cost of maintenance scenarios, and an appropriate scenario is proposed for anaesthesia machine. A new failure‐cost model is developed, which may be used to calculate the number of failures of equipment and the annual maintenance cost. The proposed models may be used as a planning tool for selecting maintenance strategies for various medical equipments. Copyright © 2014 John Wiley & Sons, Ltd.     

Study on the Methods of Equipment Maintenance Management

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Modeling Failure Process and Quantifying the Effects of Multiple Types of Preventive Maintenance for a Repairable System

In this paper, we consider a repairable system whose failures follow a non‐homogenous Poisson process with the power law intensity function. The system is subject to corrective and multiple types of preventive maintenance. A corrective maintenance has a minimal effect on the system; however, a preventive maintenance may reduce the system's age. We assume the effects of different preventive maintenance on the system are not identical and derive the likelihood function to estimate the parameters of the failure process as well as the effects of preventive maintenance. Moreover, we derive the conditional reliability and the expected number of failures between two consecutive preventive maintenance types. The proposed methods are applied to a real case study of four trucks used in a mining site in Canada. Copyright © 2016 John Wiley & Sons, Ltd.     

考虑维修时间和惩罚的租赁设备维护策略研究

针对租赁设备维修时间的不确定性,建立考虑维修时间随机性的等周期预防性维护策略。该策略在考虑租赁设备维修时间随机性的同时,综合考虑对出租方的维修惩罚,包括维修时间惩罚、故障总次数惩罚以及可用度惩罚等因素对总成本的影响。从出租方的角度出发,建立以出租方总成本最小为目标的预防性维护策略优化模型。用MATLAB仿真求解出模型的最优预防性维护计划。算例分析表明,考虑租赁设备维修时间随机性和维修惩罚使租赁设备的维护更符合实际情况,能为租赁企业提供有效的设备维护策略。     

Optimization of maintenance policy using the proportional hazard model

The evolution of system reliability depends on its structure as well as on the evolution of its components reliability. The latter is a function of component age during a system's operating life. Component aging is strongly affected by maintenance activities performed on the system. In this work, we consider two categories of maintenance activities: corrective maintenance (CM) and preventive maintenance (PM). Maintenance actions are characterized by their ability to reduce this age. PM consists of actions applied on components while they are operating, whereas CM actions occur when the component breaks down. In this paper, we expound a new method to integrate the effect of CM while planning for the PM policy. The proportional hazard function was used as a modeling tool for that purpose. Interesting results were obtained when comparison between policies that take into consideration the CM effect and those that do not is established.     

面向环境的设备维护管理与再制造工程集成模式

在分析再制造工程与设备维护管理的理论体系及二者关系的基础上,从有效利用资源、提升设备的使用效能的角度出发,运用质量功能展开(Quality Function Display,简称QFD)方法,提出了一种面向环境需求的设备维护管理和再制造工程的集成模式。     

Human Factors Effects and Analysis in Maintenance: A Power Plant Case Study

This paper proposes a methodical approach for identifying and reducing human error in maintenance activities, the human factors effect and analysis. Human factors effect and analysis presents a roadmap for selecting significant human factors affecting maintenance management as well as the most effective solutions using cost–benefit analysis. Safety and operational consequences of each human factor are compared to preventive and recovery risk controls to select the preferred risk control method. Because human factor programs are not implemented in many maintenance departments, quantitative data are rare. Thus, expert judgment may help to compare potential solutions. In order to show the applicability of the proposed approach a power plant in Kenya is selected as a case study. Procedure usage, fatigue, knowledge and experience, and time pressure are identified as the most important human factors. Training, task planning /shift management, knowledge management, scheduling as well as incident report programs are the most cost‐effective solutions for performing human factors program. The proposed approach would improve system reliability by recognizing human related failures. Furthermore, unexpected incident and accident may be reduced having knowledge about potential risk factors. Copyright © 2016 John Wiley & Sons, Ltd.     

考虑预防维修时间及相关性的多部件系统维护策略

针对动车组关键系统维修过程中涉及部件数量多、维修时间长、维修费用高的特点，提出了预防维修时间、故障相关性、经济相关性3重因素影响下的多部件系统机会维护策略。首先对多部件建立部件故障率模型。在此基础上，考虑预防维修时间，将部件层预防维修成本分为独立时间成本和依赖时间成本，对经济相关性进行建模，再以系统维修费用率最小为优化目标建立系统层维护模型，并应用遗传算法求解。最后通过算例表明，相较于考虑单一因素的维修策略，所提维修策略可降低系统维修成本10%及以上，验证了考虑维修时间和部件联合相关性的必要性和有效性。     

全员生产维护管理体系的开发与实施

回顾设备现代管理的理论基础，介绍了全员生产维护的特点，阐述了全员生产维护管理体系的开发与实施过程。     

Modeling and Analysis of Complex Equipment Maintenance Dynamics

An equipment maintenance system is naturally a complex dynamical system. The effective mamanagement must be based on the knowledge of the system＇s intrinsic dynamics. And the strueture of the maintenance system determines its behavior. This paper analyzes the basic structures and elements of a maintenance system for complex multi-components equipment. The maintenance system is considered as a dynamic system whose behavior is influenced by its structure＇s feedback and interaction, and the system＇s available resources. Building the dynamical model with Simulink, we show some results about the maintenance system＇s nonlinear dynamics, ods. The model can be used for understanding and which operational adjustments of maintenance which are never given by stochastic process methdetermining maintenance system behavior, towards n of maintenance requirements and timely supply of maintenance resources can be made in a more informed way.     

An Analysis of the Deferences between Old and New Maintenance Concepts

Beforethe'50s,maintenancemainlywasakindofskillandwasshortofagUidetoSystematictheoryandmaintenanceprocesswasakindofrewordathardtime.AsdevelOPmentofdelveofintellectUalization,automationofequipment,maintenancecostrosesteeply.Availabilitywascontinuouslydecreasing,andexistingmaintenanceProcesscouldnotadapttoobjectiverequirements.From1960,thecivilaviationofAmericahadexploredthebasiclawofaoplanemaintenanceintheuseofmodemsciencetechnology[l].UPtothelate'6()s,reliability-centeredmaintenancetheorywa…     

The Method of Mission Oriented Maintenance

In a real application,equipment in good condition sometimes have to be repaired because the equipment does not satisfy the requirements of the mission; However, it is not necessary to repair some equipment with failures because the failures do not affect the mission completion. In these cases, maintenance activity guided by present maintenance methods may sometimes affect the mission completion in time or bring about extra maintenance. To over-come the shortage of present maintenance methods, we propose an idea and method of mission oriented maintenance (MOM) to deal with the maintenance policy on these kinds of prob-lems. This method can work out different maintenance policies corresponding to different missions with full consideration of missions and mission requirements for the equipment.     

Generalized non‐stationary preventive maintenance model for deteriorating repairable systems

This paper deals with a practical approach for the analysis and modelling of preventive maintenance (PM) data for repairable systems which have an increasing failure frequency and/or increasing severity. The concept and testing for the trend of severity of corrective work (CO) and PM are discussed. A framework for statistical analysis of interarrival times and downtimes due to CO/PM is proposed. A generalized non‐stationary model for scheduling PM to maximize availability is suggested. The effect of severity on scheduling PM activities is shown through sensitivity analysis. Copyright © 2002 John Wiley & Sons, Ltd.