A Fuzzy Criticality Assessment System of Process Equipment for Optimized Maintenance Management.

yesIn modern chemical plants, it is essential to establish an effective maintenance strategy which will deliver financially driven results at optimised conditions, that is, minimum cost and time, by means of a criticality review of equipment in maintenance. In this article, a fuzzy logic-based criticality assessment system (FCAS) for the management of a local company’s equipment maintenance is introduced. This fuzzy system is shown to improve the conventional crisp criticality assessment system (CCAS). Results from case studies show that not only can the fuzzy logic-based system do what the conventional crisp system does but also it can output more criticality classifications with an improved reliability and a greater number of different ratings that account for fuzziness and individual voice of the decision-makers

Use of COTS functional analysis software as an IVHM design tool for detection and isolation of UAV fuel system faults

This paper presents a new approach to the development of health management solutions which can be applied to both new and legacy platforms during the conceptual design phase. The approach involves the qualitative functional modelling of a system in order to perform an Integrated Vehicle Health Management (IVHM) design – the placement of sensors and the diagnostic rules to be used in interrogating their output. The qualitative functional analysis was chosen as a route for early assessment of failures in complex systems. Functional models of system components are required for capturing the available system knowledge used during various stages of system and IVHM design. MADe™ (Maintenance Aware Design environment), a COTS software tool developed by PHM Technology, was used for the health management design. A model has been built incorporating the failure diagrams of five failure modes for five different components of a UAV fuel system. Thus an inherent health management solution for the system and the optimised sensor set solution have been defined. The automatically generated sensor set solution also contains a diagnostic rule set, which was validated on the fuel rig for different operation modes taking into account the predicted fault detection/isolation and ambiguity group coefficients. It was concluded that when using functional modelling, the IVHM design and the actual system design cannot be done in isolation. The functional approach requires permanent input from the system designer and reliability engineers in order to construct a functional model that will qualitatively represent the real system. In other words, the physical insight should not be isolated from the failure phenomena and the diagnostic analysis tools should be able to adequately capture the experience bases. This approach has been verified on a laboratory bench top test rig which can simulate a range of possible fuel system faults. The rig is fully instrumented in order to allow benchmarking of various sensing solution for fault detection/isolation that were identified using functional analysis

Criticality Analysis for Maintenance Purposes: A Study for Complex In‐service Engineering Assets

The purpose of this paper is to establish a basis for a criticality analysis, considered here as a prerequisite, a first required step to review the current maintenance programs, of complex in‐service engineering assets. Review is understood as a reality check, a testing of whether the current maintenance activities are well aligned to actual business objectives and needs. This paper describes an efficient and rational working process and a model resulting in a hierarchy of assets, based on risk analysis and cost–benefit principles, which will be ranked according to their importance for the business to meet specific goals. Starting from a multicriteria analysis, the proposed model converts relevant criteria impacting equipment criticality into a single score presenting the criticality level. Although detailed implementation of techniques like Root Cause Failure Analysis and Reliability Centered Maintenance will be recommended for further optimization of the maintenance activities, the reasons why criticality analysis deserves the attention of engineers and maintenance and reliability managers are precisely explained here. A case study is presented to help the reader understand the process and to operationalize the mode

Dynamic Risk Analysis of Construction Delays Using Fuzzy-Failure Mode Effects Analysis

Considering the tremendous losses in the worldwide economy caused by construction delays, it is essential to invest in minimizing the risks of delays. In order to make this happen, two measures should be taken: 1) The roots and fundamental causes of delay should be identified and strategies to mitigate their risks be developed (General remedy). 2) The most significant potential causes of delay in each project should be identified and these causes should be given priority to control (Project-Specific Remedy). The current research invests in both of the measures. To provide the general remedy, causes of delay in the construction industry of the United States is investigated through a national survey responded by the 224 construction experts with an average experience of over 27 years. The results of this study rank the criticality of the thirty main causes of construction delay in the U.S construction industry. The focus of the research is on the project-specific remedy. The research aims at designing a tool, which can prioritize different causes based on their criticality. This is crucial as there is often a large number of potential causes and investing in prevention of all of them is not practical. The designed tool is capable of identifying the most critical causes by assessing its status of the potential causes of delay in three elements of criticality which are: 1) The likelihood of occurrence of the cause, 2) the severity of the cause in creating delays (in case it happens), and 3) the resolvability or likelihood of handling the potential cause before it creates a delay, in case it happens. The three elements of assessment are inserted in a designed tool in Matlab®, which uses a fuzzy logic system to generate a “risk priority number’. This number is a representative of the riskiness of each potential cause. The next contribution of the research is a model that is capable of predicting the percentage of delay based on the “fuzzy risk priority number”. This model uses the output of the aforementioned fuzzy inference system to make a prediction about the percentage of delay. The model was tested by comparing its predictions with actual data (the delay that has actually happened) and has been able to predict the amount of delay with an error of less than 20%

Optimization of maintenance performance for offshore production facilities

Master's thesis in Offshore technologyNew technologies are becoming advanced and complex for offshore production facilities. However this advancement and complexity in technology creates a more complicated and time consuming forensic processes for finding causes of failure, or diagnostic processes to identify events that reduce performance. As a result, micro-sensors, efficient signaling and communication technologies for collecting data efficiently, advanced software tools (such as fuzzy logic, neural networks, and simulation based optimization) have been developed, in parallel, to manage such complex assets. Given the nature and scale of ongoing changes on complexities, there are emerging concerns that increasing complexities, ill-defined interfaces, unforeseen events can easily lead to serious performance failures and major risks. To avoid such undesirable circumstances, „just-in-time‟ measures of performance to ensure fully functional is absolutely necessary. The increasing trend in complexity creates a motivation to develop an integrated maintenance management framework to get real-time information to solve problems quickly and hence to increase functional performance (help the asset to perform its required function effectively and efficiently while safeguarding life and the environment). Establishing “just-in-time” maintenance and repairs based on true machine condition maximizes critical asset useful life and eliminates premature replacement of functional components. This thesis focuses on developing an integrated maintenance management framework to establish „just-in-time‟ maintenance and to ensure continuous improvements based on maintenance domain experts as well as operational and historic data. To do this, true degradation of components must be identified. True level of degradation often cannot be inferred by the mere trending of condition indicator‟s level (CBM), because condition indicator levels are modulated under the influence of the diverse operating context. Besides, the maintenance domain expert does not have a precise knowledge about the correlation of the diverse operating context and level of degradation for a given level of condition indicator on specific equipment. Efforts have been made in here to identify the true degradation pattern of a component by analyzing these vagueness and imprecise knowledge. Key words: effective and efficient maintenance strategy, ‘just-in-time’ maintenance, condition based maintenance, P-F interval

Elements of maintenance system and tools for implementation within framework of Reliability Centred Maintenance- A review

For plant systems to remain reliable and safe they must be effectively maintained through a sound maintenance management system. The three major elements of maintenance management systems are; risk assessment, maintenance strategy selection and maintenance task interval determination. The implementation of these elements will generally determine the level of plant system safety and reliability. Reliability Centred Maintenance (RCM) is one method that can be used to optimise maintenance management systems. This paper discusses the three major elements of a maintenance system, tools utilised within the framework of RCM for performing these tasks and some of the limitations of the various tools. Each of the three elements of the maintenance management system has been considered in turn. The information will equip maintenance practitioners with basic knowledge of tools for maintenance optimisation and stimulate researchers with respect to developing alternative tools for application to plant systems for improved safety and reliability. The research findings revealed that there is a need for researchers to develop alternative tools within the framework of RCM which are efficient in terms of processing and avoid the limitations of existing methodologies in order to have a safer and more reliable plant system.

Knowledge Criticality Assessment and Codification Framework for Major Maintenance Activities: A Case Study of Cement Rotary Kiln Plant

Maintenance experts involved in managing major maintenance activities such as; Major overhauls, outages, shutdowns and turnarounds (MoOSTs) are constantly faced with uncertainties during the planning and/or execution phases, which often stretches beyond the organisation’s standard operating procedures and require the intervention of staff expertise. This underpins a need to complement and sustain existing efforts in managing uncertainties in MoOSTs through the transformation of knowledgeable actions generated from experts’ tacit-based knowledge. However, a vital approach to achieve such transformation is by prioritising maintenance activities during MoOSTs. Two methods for prioritising maintenance activities were adopted in this study; one involved a traditional qualitative method for task criticality assessment. The other, a quantitative method, utilised a Fuzzy inference system, mapping membership functions of two crisp inputs and output accompanied by If-Then rules specifically developed for this study. Prior information from a 5-year quantitative dataset was obtained from a case study with appreciable frequency for performing MoOSTs; in this case, a Rotary Kiln system (RKS) was utilised in demonstrating practical applicability. The selection of the two methods was informed by their perceived suitability to adequately analyse the available dataset. Results and analysis of the two methods indicated that the obtained Fuzzy criticality numbers were more sensitive and capable of examining the degree of changes to membership functions. However, the usefulness of the traditional qualitative method as a complementary approach lies in its ability to provide a baseline for informing expert opinions, which are critical in developing specific If-Then rules for the Fuzzy inference system