Development of maintainability index for mechanical systems

A procedure based on a digraph and matrix method is developed for evaluation of maintainability index of mechanical systems. Features which characterize or ease in maintenance of a system are identified and are called the maintainability attributes. Consideration of these attributes and their interrelations are rudiment in evaluating the index. This is modeled in terms of a Maintainability Attributes Digraph for the system. Nodes in the digraph represent these attributes and their interrelations are represented by the edges. The digraph is represented by one-to-one matrix for development of a maintainability expression, which is characteristic of the system. A Variable Maintainability Attributes Facilitation Permanent Matrix is defined to develop maintainability expression (VPF-m) which is also useful in comparing two systems. Maintainability Index of the system is obtained from the permanent of the matrix or from the maintainability expression by substituting numerical values of the attributes and their interrelations. A higher value of the index implies good maintainability of the system. The ideal value of maintainability index (I_mi) is also obtained from the matrix expression, which is useful in assessing relative maintainability, I_r, of the system alternative. The procedure is useful in design and development of maintainable systems. A step by step procedure for evaluation of maintainability index is also suggested and is illustrated by means of an example.     

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.     

Maintainability design and evaluation of mechanical systems based on tribology

Maintainability of mechanical systems based on tribology is suggested and evaluated in this paper. Tribo-features of mechanical systems, which characterise maintainability are identified and are modelled in terms of tribo-maintainability digraph. The nodes in the digraph represent the tribo-features and edges represent the degree of influence among the features. A matrix, one to one representation of the digraph, is defined to develop system maintainability expression (SPF-t) based on the tribology. It is also useful in comparing the various design alternatives from tribo-maintainability point of view. Maintainability is evaluated from the tribo-maintainability index, obtained from SPF-t (i.e. permanent of the matrix) by substituting the numerical values of the features and their interdependence. A higher value of the index implies better maintainability of the systems. The proposed methodology also guides designers in enhancing the maintainability of a system by appropriately incorporating tribo-features. An example to illustrate the methodology is also presented.     

Individual latent error detection: is there a time and a place for the recall of past errors?

A task carried out in error creates a latent condition that can result in a future undesirable outcome if the error is not detected later. The paper presents a study of the relatively under-researched phenomenon of post-task latent error detection. Focusing on UK naval aircraft maintenance, it was hypothesised that time, location and systems cues influence individual latent error detection amongst naval air engineers who experience the phenomenon. The systems view of human error is combined with a multi-process approach to post-task latent error research, for which findings suggest that distributed cognition across the entire socio-technical system may be influential in post-task latent error detection. Directions for future research will be of benefit to those interested in furthering safety resilience using a systems approach to minimise the consequences arising from latent error.

Relevance to human factors/ergonomics theoryThe nature and extent of post-task latent error detection is explored using a systems approach, for which distributed cognition across the entire socio-technical system appears influential. The aim of current research is to develop interventions to further mitigate for latent errors and thus advance the systems application of ergonomics theory.     

Identification and Assessment of Factors Influencing Human Reliability in Maintenance Using Fuzzy Cognitive Maps

Human element forms an inevitable part of maintenance activity and gets affected by a variety of interacting factors, ranging from environmental, organizational, job factors, and so on to personal characteristics, which bring in inherent variability in its reliability. Assessment of impact of these factors is, therefore, critical for human reliability estimation in maintenance. In every probabilistic risk, safety or maintenance analysis, human reliability does act as an effective aspect to assess implications of various aspects of the human performance. But the main constraint with various human reliability analysis methods is in judging the important human performance influencing factors. Because of high degree of uncertainty and variability that characterizes the plant maintenance environment, it is proposed to use the soft computing technique of fuzzy cognitive maps in exploring the importance of performance shaping factors in maintenance scenario. For this purpose, the maintenance environment is modeled in terms of factors affecting human reliability using cognitive maps. The causal relationships among these factors are explored and simulations performed to quantify its effect on the human reliability. The applicability of the methodology is demonstrated through an example. Copyright © 2013 John Wiley & Sons, Ltd.     

Training needs analysis—a human factors analysis tool

Human factors (HF) engineers have contributed to the reduction of human error, by improving user performance through the design of the user interface. However, there still remains a requirement for user training. This is especially true for complex, high risk processes employing new technology. Reduced manning and downskilling are putting increased pressures on users who, in many activities, still remain the last level of safety protection. In responding to this need, HF engineers now employ a range of tools and methods during the design process, which assist in identifying the training media and training design. Training needs analysis (TNA) offers a structured methodology to facilitate the information gathering process and identify any shortfall between current user performance and that demanded by new technology and designs. By the use of these methods and tools the potential for human error can be reduced, for the following reasons: (a) improved user performance (b) better designed and more efficient training systems. Existing TNA methods have been better suited to the study of existing equipment. This paper describes the training requirements process, and proposes a usable methodology for contractors conducting a TNA in the design of new systems/equipment. It is of particular use where information on the operation or maintenance may be limited.     

Estimating and ranking the impact of human error roots on power grid maintenance group based on a combination of mathematical expectation,Shannon entropy,and TOPSIS

Due to the importance of electrical grid reliability, analysis and evaluation of human error in the maintenance of electrical networks should be also considered seriously. The root causes of these errors must be identified and prioritized to plan for human error reduction. One of the objectives of the present study is to identify and predict these roots for power transmission maintenance groups from organizational, job position, communication, individual, and supervision aspects along with the relationships between these factors. In particular, this paper demonstrates that supervisor behavior as an external factor has a significant effect on maintenance personnel error. For this reason, special attention has been paid to identifying and controlling human factors from a supervisory point of view in this study. This paper also provides a method for detecting the extent of the expected influence of these roots on each personnel, since human error has a random nature. This is done based on the law of mathematical expectation. Finally, a method is suggested to rank roots based on greater effectiveness and evaluate personnel with higher error expectations. The proposed method is a combination of intermediate methods, Shannon entropy, and technique for order of preference by similarity to ideal solution (TOPSIS). The origins of the four human errors between 2014 and 2018 related to the two experts of Fars Electricity Maintenance Contractor Company are compared by the proposed method.     

人误模式、影响与严重度分析方法

人因失误已成为复杂系统最主要的事故源之一，而人误分析技术存在着缺乏一致性和使用困难等问题。本文将故障模式，影响与严重度分析方法进行人因特征化改造，提出人误模式，影响与严重度分析方法，规范化地分析人因失误的故障模式与影响，根本原因及严重度和相应的人因失误防范策略。     

工业系统监控作业中的人因失误研究综述

目的 对工业系统监控作业中的人因失误相关研究进行梳理和分析,以了解其研究现状及发展趋势。方法 通过文献研究法,梳理并界定人因失误的概念,归纳出人因失误的性质与特征。通过对监控作业的演变研究,总结出目前工业系统数字化监控作业的人因特征。从核电、航空、轨道交通、电力系统等行业出发,分析监控作业人员的认知行为模型,探究人因失误产生机制,梳理人因失误辨识方法,分析其在工业系统监控作业中的适用性,识别监控作业中人因失误的影响因素。结论 随着数字化监控界面的发展及作业情境的变化,监控作业人员的认知过程和行为响应方式都发生了改变,需要不断丰富人因失误理论,探究人因失误机理,为工业系统监控作业中人因失误管控提供理论依据。     

综掘工作面人因失误模型

煤矿综掘工作面是由人、机器设备和环境组成的复杂生产系统,其工作面环境条件易变、作业空间狭窄、视觉环境差等,对机器设备的可靠性,以及工人的作业效率及身心健康都有重要的影响。通过理论和实际调研的结合,在研究综掘工作面人-机-环境关系的基础上,借鉴统计理论,建立人因失误模型,运用参数估计进行统计分析,量化人因失误致因因子,求解人子系统的可靠性指标,深入分析人因失误行为发生的类型、行为因子。     

Risk analysis of human error in interaction design by using a hybrid approach based on FMEA,SHERPA, and fuzzy TOPSIS

User experience is the focus of interaction design, and designing for errors is crucial for improving user experience. One method of designing for errors is to identify human errors and then initiate corrective actions on high-risk errors to reduce their adverse effects. In this study, we proposed a hybrid approach for risk analysis of human error concerning user experience of interactive systems. In this approach, systematic human error reduction and prediction approach (SHERPA) is first adopted to identify human error concerning user experience. Subsequently, failure mode and effect analysis (FMEA) is used to analyze the risk factors of the error, including occurrence, severity, and detection. Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is then used to calculate the risk priority number to rank the errors. Finally, corrective actions for high-risk errors are recommended. An in-vehicle information system was used to demonstrate the proposed approach. The results indicated that the proposed approach can effectively analyze the risk of human error concerning user experience and be used as a universal reliability approach for improving user experience in interaction design.     

Human Reliability Analysis of Roof Bolting Operation in Underground Coal Mines

Investigations have shown that human error is the most common cause of roof bolting injuries. Human error probability estimation has become a critical issue for human reliability analysis (HRA) of roof bolting operation. Specialist judgment plays a crucial role in quantifying human error probability in the field because of limited availability of empirical data. However, the aggregation of specialist judgment is typically not carried out in a formal way in HRA. In this paper, an approach to combine Bayesian methodology and the success likelihood index method was to build a computable model using information from specialists for HRA of roof bolting operation. A numerical example was used to illustrate the application of the proposed methodology. Copyright © 2015 John Wiley & Sons, Ltd.     

人误模式与原因因素分析

将人误模式分为显现型和潜在型两类.显现型人误模式主要体现在时间、行为、目标、顺序四维时空特性上,而潜在的人误模式是基于认知过程与组织的,需要从微观与宏观两方面对其进行分类.影响人为失误的原因归结为个人、技术、组织、环境四类因素.将人误作为一个事件来进行分析,构建了概念上的人误原因层次诊断模型,它包括原因主因素、子因素和子子因素层等.以人误模式为切入点,对这些因素的诊断采用了人误原因的回溯性分析方法,具体过程为:一般行为条件描述-确定可能的人误模式-确定可能的人误原因因素-匹配判断.     

人误因素树构建技术

运用人误因素辨识多视图法进行因素辨识，建立了详细的因素辨识表；把人的行为分为系统状态监测、状态分析、目标分析、方案确定和行为执行5个阶段，分别各个阶段可能的人误原因及模式；根据因素辨识和人误原因及模式，分析结果，以组织视图为例阐述人误因素树的构建过程，最终得到了一个完整的人误因素树。     

Human error and time of occurrence in hazardous material events in mining and manufacturing

Human error has played a role in several large-scale hazardous materials events. To assess how human error and time of occurrence may have contributed to acute chemical releases, data from the Hazardous Substances Emergency Events Surveillance (HSEES) system for 1996-2003 were analyzed. Analyses were restricted to events in mining or manufacturing where human error was a contributing factor. The temporal distribution of releases was also evaluated to determine if the night shift impacted releases due to human error. Human error-related events in mining and manufacturing resulted in almost four times as many events with victims and almost three times as many events with evacuations compared with events in these industries where human error was not a contributing factor (10.3% versus 2.7% and 11.8% versus 4.5%, respectively). Time of occurrence of events attributable to human error in mining and manufacturing showed a widespread distribution for number of events, events with victims and evacuations, and hospitalizations and deaths, without apparent increased occurrence during the night shift. Utilizing human factor engineering in both front-end ergonomic design and retrospective incident investigation provides one potential systematic approach that may help minimize human error in workplace-related acute chemical releases and their resulting injuries.     

Application of a human error framework to conduct train accident/incident investigations

Accident/incident investigations are an important qualitative approach to understanding and managing transportation safety. To better understand potential safety implications of recently introduced remote control locomotive (RCL) operations in railroad yard switching, researchers investigated six railroad accidents/incidents. To conduct the investigations, researchers first modified the human factors analysis and classification system (HFACS) to optimize its applicability to the railroad industry (HFACS-RR) and then developed accident/incident data collection and analysis tools based on HFACS-RR. A total of 36 probable contributing factors were identified among the six accidents/incidents investigated. Each accident/incident was associated with multiple contributing factors, and, for each accident/incident, active failures and latent conditions were identified. The application of HFACS-RR and a theoretically driven approach to investigating accidents/incidents involving human error ensured that all levels of the system were considered during data collection and analysis phases of the investigation and that investigations were systematic and thorough. Future work is underway to develop a handheld software tool that incorporates these data collection and analysis tools.     

飞行机组人为差错风险分析方法研究

提出了一个新的飞行机组人为差错风险评估方法F HECA,识别和分析航空公司的机组人为差错风险。该方法在对机组人为差错类型进行总结和分类的基础上,选取人为差错严重度作为评价指标,将该指标中的3个变量人为差错概率、人为差错后果严重度、人为差错影响概率与灰色综合评价法结合,定量评估机组人为差错的严重度,实现机组人为差错风险评估。通过实例分析验证此方法可用于分析机组人为差错风险,为飞行训练和飞行操作手册内容的改进提供技术支持,是民航人为因素研究中可借鉴的一种方法。     

A digraph approach to TQM evaluation of an industry

Different total quality management (TQM) environments may be suggested to an organization for improving the quality of products, customer satisfaction, competitiveness and profitability by TQM experts. This paper identifies factors responsible for the TQM environment. All these factors are interacting with each other by different amounts. An attempt has been made to develop a mathematical model of the TQM environment from these interacting factors using a graph theoretic approach. In the graph theoretic model, a directed graph or digraph is used to represent abstract information of the system using directed edges, which is useful for visual analysis. The matrix model developed from the digraph is useful for computer processing. A permanent value of multinomial developed from the matrix represents the environment uniquely by a single number/index, which is useful for comparison, ranking and optimum selection. The method is quite flexible to accommodate new factors and market dynamics in global business in a bid to go for continuous improvement and breakthrough improvement in the environment, product, process and intellectual property rights (IPR).     

Human error in European air traffic management: the HERA project

The majority of accidents in hazardous activities are caused by human error. This problem is not new, and a good deal of research, application, and development of practical techniques for the analysis, prediction and reduction of human errors or their negative effects, has occurred in a range of industries. Whilst human error within flight operations has for some time been the centre of exhaustive research and debate, a similar analysis within the field of air traffic management (ATM) is not so comprehensive. Therefore, it may be that ATM can learn from other industries.This paper deals with an approach to ATM incident analysis that is being developed in the European ATM arena. This new approach aims to determine how and why human errors are contributing to incidents, and thus how to improve human reliability within a high-reliability system. This developing approach is called ‘HERA’ — Human Error in ATM Project.The paper reports on a formative part, or phase 1, of a project that reviewed the theoretical and practical literature to determine the best conceptual framework upon which to base an ATM incident analysis tool. The conceptual framework chosen is that of human performance from an information processing perspective, which has been adapted to make it more contextually relevant to ATM. A prototype structure was adopted for a technique with which to analyse ATM incidents. This paper summarises the review of the literature surveyed, and briefly describes the structure of the prototype technique.     

Determination of human error patterns: The use of published results of official enquiries into system failures

Official enquiries into large scale system failures may be used to interpret events according to the various types of human error which were committed. For example there are errors in operation of the system, in maintenance practices etc. Twelve well documented disasters are analysed and the conclusion emerges that operator error predominates. This fact is not suprising, reflecting as it does the short time span in which operators have to make decisions, compared to the other players such as designers, maintenance men etc. This conclusion has implications for the other human disciplines involved. For example designers should conceive systems which will be less prone to operator error, while management should support operators in whatever way possible to increase their effectiveness.