Reliability block diagram (RBD) and fault tree analysis (FTA) approaches for estimation of system reliability and availability – a case study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Balaraju Jakkula ◽  
Govinda Raj Mandela ◽  
Murthy Ch S N
Keyword(s):  
Failure Modes ◽  
Block Diagram ◽  
Probability Distributions ◽  
Fault Tree Analysis ◽  
Likelihood Estimation ◽  
Parametric Estimation ◽  
Data Sets ◽  
Content Type ◽  
Best Fit

PurposeIn the present worldwide situation, the survival of a business is a major crucial aspect. The business cannot be succeeded unless it produces the anticipated production levels. Achievement of this can be possible only by maintaining the equipment into an adequate level. Load-Haul-Dumpers (LHDs), as the main workhorse and massive transporting machines, are highly utilized in underground mining operations. Despite the usage of LHDs, these are prone to the uneven and unexpected occurrence of potential failures. These are causes to minimize the production and productivity of capital intensive equipment. To get a good profitability index, it is very necessary to have the required levels of equipment reliability and availability. Estimation of reliabilities and availabilities play a critical role in the performance evaluation of equipment.Design/methodology/approachBy keeping the significance of the present research work in view in this research paper one of the well appropriate techniques such as fault tree analysis (FTA) was utilized to assess the reliability of the LHD system based on the function flow diagram. Best fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K-S) test. Parametric estimation of theoretical probability distributions was done by utilizing the maximum likelihood estimation (MLE). Failure rate of each LHD system has computed based on the best fit results from “Isograph Reliability Workbench 13.0”. Reliability configuration of each LHD system has modeled using reliability block diagram (RBD), as well as the FTA.FindingsIndependent and identical distribution (IID) assumption of data sets was validated through statistic U-test (Chi Squared test). On the basis of test results, the data sets are in accordance with IID assumption. Therefore renewal process approach has been utilized for further investigation. Allocations of best fit distribution of data sets were made by the utilization ofK-S test. Parametric estimation of theoretical probability distributions was made by utilizing maximum likelihood estimation (MLE) method. Reliability of each individual subsystem has been computed according to the best fit distribution. The deductive method called RBD was utilized to investigate the given system reliability by analyzing with graphical representations of logic system and observed highest percentage of reliability as 69.44% (LH29). FTA has been utilized to investigate the availability percentage of a system and observed highest percentage value as 79.51% (LH29). This technique also helps to identify the most critical parts/cut sets by using Fussell-Vesely (F-V) importance measure.Research limitations/implicationsAs the reliability analysis is one of the complex techniques, it requires strategic decision-making knowledge for the selection of methodology to be used. As the present case study was from a public sector company, operating under financial constraints the conclusions/findings may not be universally applicable.Originality/valueThe present study throws light on this equipment that need a tailored maintenance schedules, partly due to the peculiar mining conditions, under which they operate. This analysis provides the information on several aspects such as present working condition of the machines, occurrence of various potential failure modes, influence of failure modes on its performance and reliable life aspects etc. Also, these investigations asses the forecasting of necessary managerial practices or control measures like possible design modifications and replacement actions of components to ensure the required levels of availability and utilization of the equipment. Both qualitative and quantitative analysis of FTA has been performed to determine the minimal/most influencing cut sets of the system and to estimate overall system availability within the work environment. Based on the computed results reasons for performance drop of each machine was identified and suitable recommendations were suggested to improve the performance of capital intensive systems.

Maintenance management of load haul dumper using reliability analysis

2019 ◽  
Vol 26 (2) ◽  
pp. 290-310 ◽  
Author(s):  
Balaraju Jakkula ◽  
Govinda Raj M. ◽  
Murthy Ch.S.N.
Keyword(s):  
Reliability Analysis ◽  
Probability Distributions ◽  
Parametric Estimation ◽  
Maintenance Management ◽  
Data Sets ◽  
Content Type ◽  
Theoretical Probability ◽  
Reliability Level ◽  
Kolmogorov Smirnov ◽  
Best Fit

Purpose Load haul dumper (LHD) is one of the main ore transporting machineries used in underground mining industry. Reliability of LHD is very significant to achieve the expected targets of production. The performance of the equipment should be maintained at its highest level to fulfill the targets. This can be accomplished only by reducing the sudden breakdowns of component/subsystems in a complex system. The identification of defective component/subsystems can be possible by performing the downtime analysis. Hence, it is very important to develop the proper maintenance strategies for replacement or repair actions of the defective ones. Suitable maintenance management actions improve the performance of the equipment. This paper aims to discuss this issue. Design/methodology/approach Reliability analysis (renewal approach) has been used to analyze the performance of LHD machine. Allocations of best-fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K–S) test. Parametric estimation of theoretical probability distributions was made by utilizing the maximum likelihood estimate (MLE) method. Findings Independent and identical distribution (IID) assumption of data sets was validated through trend and serial correlation tests. On the basis of test results, the data sets are in accordance with IID assumption. Therefore, renewal process approach has been utilized for further investigation. Allocations of best-fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K–S) test. Parametric estimation of theoretical probability distributions was made by utilizing the MLE method. Reliability of each individual subsystem has been computed according to the best-fit distribution. In respect of obtained reliability results, the reliability-based preventive maintenance (PM) time schedules were calculated for the expected 90 percent reliability level. Research limitations/implications As the reliability analysis is one of the complex techniques, it requires strategic decision making knowledge for the selection of methodology to be used. As the present case study was from a public sector company, operating under financial constraints the conclusions/findings may not be universally applicable. Originality/value The present study throws light on this equipment that need a tailored maintenance schedule, partly due to the peculiar mining conditions, under which they operate. This study mainly focuses on estimating the performance of four numbers of well-mechanized LHD systems with reliability, availability and maintainability (RAM) modeling. Based on the drawn results, reasons for performance drop of each machine were identified. Suitable recommendations were suggested for the enhancement of performance of capital intensive production equipment. As the maintenance management is only the means for performance improvement of the machinery, PM time intervals were estimated with respect to the expected rate of reliability level.

Reliability, availability and maintainability (RAM) analysis for wine packaging production line

2018 ◽  
Vol 35 (3) ◽  
pp. 821-842 ◽  
Author(s):  
Panagiotis Tsarouhas
Keyword(s):  
Production Line ◽  
Failure Modes ◽  
Probability Distributions ◽  
Data Sets ◽  
Effect Analysis ◽  
Content Type ◽  
Factors Affecting ◽  
Potential Factors ◽  
Ram Analysis ◽  
Best Fit

Purpose The purpose of this paper is to provide results for a complete reliability, availability, and maintainability (RAM) analysis utilizing data sets from a production system in a wine packaging line. Through the illustrated case study, the author demonstrates how RAM analysis is very useful for deciding maintenance intervals, and for planning and organizing the adequate maintenance strategy. Design/methodology/approach RAM analysis has been done for each machine by using failures data. The parameters of some common probability distributions, such as Weibull, exponential, lognormal, and normal distributions, have been estimated by using the Minitab software package. An investigation to determine which of these distributions provide the best fit for characterizing the failure pattern at machine and line level has been made. Reliability and maintainability of both wine packaging and its machines has been estimated at different mission times with their best fit distribution. High maintainability issues and potential factors with their potential failure modes were presented, through failure mode and effect analysis process. Findings Analysis of the total downtime, breakdown frequency, reliability, and maintainability characteristics of different machines shows that: first, the availability for the wine packaging line was 91.80 percent, and for the remaining 8.2 percent the line is under repair. Second, about two failures per shift are displayed on the line, whereas for the mean time-to-repair (TTR) a failure is 24 minutes. Third, there is no correlation between the time-between-failures and the TTRs for the wine packaging line. Fourth, the main three factors affecting the maintainability process in the production line are: resources availability, manpower management, and maintenance planning procedures. Originality/value This study is anticipated to serve as an illuminating effort in conducting a complete RAM analysis in the much advertised field of wine packaging production line which on the other hand so little has been published on operational availability and equipment effectiveness. It can also be useful to serve as a valid data source for winery product manufacturers, who wish to improve the design and operation of their production lines.

scholarly journals Improving Decision-Making Grid based on interdependence among failures with a case study in the steel industry

2019 ◽  
Vol 31 (2) ◽  
pp. 167-182 ◽  
Author(s):  
Arash Shahin ◽  
Ashraf Labib ◽  
Soroosh Emami ◽  
Mahdi Karbasian
Keyword(s):  
Decision Making ◽  
Asset Management ◽  
Block Diagram ◽  
Fault Tree Analysis ◽  
Content Type ◽  
Steel Making ◽  
Physical Asset ◽  
Mean Time ◽  
Continuous Casting Plant

Purpose Decision-Making Grid (DMG) is used for determining maintenance tactics and is associated with the reliability and risk management of assets. In this grid, decision making is performed based on two indicators of Mean Time to Repair (MTTR) and frequency of failures. The purpose of this paper is to improve DMG by recognizing interdependence among failures. Design/methodology/approach Fault Tree Analysis and Reliability Block Diagram have been applied for improving DMG. The proposed approach has been examined on eight equipment of the steel making and continuous casting plant of Mobarakeh Steel Company. Findings Findings indicate different positions of equipment in the cells of the new grid compared to the basic grid. Research limitations/implications DMG is limited to two criteria of frequency of failures and MTTR values. In both basic and new DMGs, cost analysis has not been performed. The application of the proposed approach will help the reliability/maintenance engineers/analysts/managers to allocate more suitable maintenance tactics to equipment. This, in turn, will enhance the equipment life cycle and availability as the main objectives of physical asset management. Originality/value A major limitation of basic DMG is that the determined tactic based on these two indicators might not be an appropriate solution in all conditions, particularly when failures are interdependent. This has been resolved in this paper.

AI and privacy concerns: a smart meter case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jillian Carmody ◽  
Samir Shringarpure ◽  
Gerhard Van de Venter
Keyword(s):  
Private Information ◽  
Personal Information ◽  
Consumer Information ◽  
Data Sets ◽  
Smart Meter ◽  
Smart Meters ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Legislation

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.

Interval type-2 fuzzy inference-based failure mode and effect analysis model in a group decision-making setting

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
İlker Gölcük
Keyword(s):  
Failure Modes ◽  
Fuzzy Inference ◽  
Real Life ◽  
Effect Analysis ◽  
Inference System ◽  
Content Type ◽  
Proposed Model ◽  
Interval Type

PurposeThis paper proposes an integrated IT2F-FMEA model under a group decision-making setting. In risk assessment models, experts' evaluations are often aggregated beforehand, and necessary computations are performed, which in turn, may cause a loss of information and valuable individual opinions. The proposed integrated IT2F-FMEA model aims to calculate risk priority numbers from the experts' evaluations and then fuse experts' judgments using a novel integrated model.Design/methodology/approachThis paper presents a novel failure mode and effect analysis (FMEA) model by integrating the fuzzy inference system, best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) methods under interval type-2 fuzzy (IT2F) environment. The proposed FMEA approach utilizes the Mamdani-type IT2F inference system to calculate risk priority numbers. The individual FMEA results are combined by using integrated IT2F-BWM and IT2F-WASPAS methods.FindingsThe proposed model is implemented in a real-life case study in the furniture industry. According to the case study, fifteen failure modes are considered, and the proposed integrated method is used to prioritize the failure modes.Originality/valueMamdani-type singleton IT2F inference model is employed in the FMEA. Additionally, the proposed model allows experts to construct their membership functions and fuzzy rules to capitalize on the experience and knowledge of the experts. The proposed group FMEA model aggregates experts' judgments by using IT2F-BWM and IT2F-WASPAS methods. The proposed model is implemented in a real-life case study in the furniture company.

Three configurations of corporate innovation programs and their interplay

2019 ◽  
Vol 23 (1) ◽  
pp. 90-113 ◽  
Author(s):  
Michael Kötting ◽  
Andreas Kuckertz
Keyword(s):  
Design Methodology ◽  
Innovation System ◽  
Case Study Approach ◽  
Content Type ◽  
Study Approach ◽  
Innovation Activities ◽  
Strategic Innovation ◽  
Corporate Innovation ◽  
Best Fit

Purpose The success of corporate innovation is based less upon the success of a single innovation program than on a holistic and overarching corporate innovation system integrating various activities. Taking this perspective, the purpose of this paper is to extend existing research on the design of innovation programs. Design/methodology/approach Utilizing an inductive theory-building case study approach, this study provides a detailed analysis of how one of the largest and most successful German technology companies structures its many innovation activities. Findings The analysis identifies key elements of innovation programs and suggests three configurations that illustrate how these generic elements can be structured so as to offer the best fit with the underlying logic of the respective innovation program. Furthermore, this study highlights how the identified configurations come together to deliver overarching strategic innovation goals. Originality/value Existing research too often focuses solely on single innovation programs. The current research is among the first to take a holistic and overarching perspective, considering different innovation programs within a single company and analyzing their configuration and their interplay.

scholarly journals Supply chain risk assessment approach for process quality risks

2017 ◽  
Vol 34 (7) ◽  
pp. 940-954 ◽  
Author(s):  
Abhijeet Ghadge ◽  
Xie Fang ◽  
Samir Dani ◽  
Jiju Antony
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Supply Chain ◽  
Failure Modes ◽  
Design Stage ◽  
Security Risks ◽  
Content Type ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Purpose The purpose of this paper is to proactively analyse and mitigate the root causes of the product and security risks. The case study approach examines the effectiveness of the fuzzy logic approach for assessing the product and process-related failure modes within global supply chain context. Design/methodology/approach The case study of a Printed Circuit Board Company in China is used as a platform for conducting the research. Using data triangulation, the data are collected and analyzed through interviews, questionnaires, expert opinions and quantitative modelling for some interesting insights. Findings Fuzzy logic approach for failure mode and effect analysis (FMEA) provides a structured approach for understanding complex behaviour of failure modes and their associated risks for products and processes. Today’s managers should conduct robust risk assessment during the design stage to avoid product safety and security risks such as recalls. Research limitations/implications The research is based on the single case study and multiple cases from different industry sectors may provide some additional insights. Originality/value The study attempts to mitigate the root causes of product and processes using fuzzy approach to FMEA in supply chain network.

scholarly journals Forensic triage of email network narratives through visualisation

2014 ◽  
Vol 22 (4) ◽  
pp. 358-370 ◽  
Author(s):  
John Haggerty ◽  
Sheryllynne Haggerty ◽  
Mark Taylor
Keyword(s):  
Qualitative Data ◽  
Data Sets ◽  
Content Type ◽  
Electronic Evidence ◽  
Relevant Evidence ◽  
Novel Approach ◽  
Potential Sources ◽  
Digital Investigation ◽  
Tools And Techniques

Purpose – The purpose of this paper is to propose a novel approach that automates the visualisation of both quantitative data (the network) and qualitative data (the content) within emails to aid the triage of evidence during a forensics investigation. Email remains a key source of evidence during a digital investigation, and a forensics examiner may be required to triage and analyse large email data sets for evidence. Current practice utilises tools and techniques that require a manual trawl through such data, which is a time-consuming process. Design/methodology/approach – This paper applies the methodology to the Enron email corpus, and in particular one key suspect, to demonstrate the applicability of the approach. Resulting visualisations of network narratives are discussed to show how network narratives may be used to triage large evidence data sets. Findings – Using the network narrative approach enables a forensics examiner to quickly identify relevant evidence within large email data sets. Within the case study presented in this paper, the results identify key witnesses, other actors of interest to the investigation and potential sources of further evidence. Practical implications – The implications are for digital forensics examiners or for security investigations that involve email data. The approach posited in this paper demonstrates the triage and visualisation of email network narratives to aid an investigation and identify potential sources of electronic evidence. Originality/value – There are a number of network visualisation applications in use. However, none of these enable the combined visualisation of quantitative and qualitative data to provide a view of what the actors are discussing and how this shapes the network in email data sets.

scholarly journals A zonal safety analysis methodology for preliminary aircraft systems and structural design

2018 ◽  
Vol 122 (1255) ◽  
pp. 1330-1351 ◽  
Author(s):  
Z. Chen ◽  
J. P. Fielding
Keyword(s):  
Failure Modes ◽  
Hazard Analysis ◽  
Fault Tree Analysis ◽  
Cost Effective ◽  
Safety Analysis ◽  
Design Tool ◽  
Assessment Process ◽  
Design Stage ◽  
Preliminary Design

ABSTRACTZonal Safety Analysis (ZSA) is a major part of the civil aircraft safety assessment process described in Aerospace Recommended Practice 4761 (ARP4761). It considers safety effects that systems/items installed in the same zone (i.e. a defined area within the aircraft body) may have on each other. Although the ZSA may be conducted at any design stage, it would be most cost-effective to do it during preliminary design, due to the greater opportunity for influence on system and structural designs and architecture. The existing ZSA methodology of ARP4761 was analysed, but it was found to be more suitable for detail design rather than preliminary design. The authors therefore developed a methodology that would be more suitable for preliminary design and named it the Preliminary Zonal Safety Analysis (PZSA). This new methodology was verified by means of the use of a case study, based on the NASA N3-X project. Several lessons were learnt from the case study, leading to refinement of the proposed method. These lessons included focusing on the positional layout of major components for the zonal safety inspection, and using the Functional Hazard Analysis (FHA)/Fault Tree Analysis (FTA) to identify system external failure modes. The resulting PZSA needs further refinement, but should prove to be a useful design tool for the preliminary design process.

A practical introduction to methods for analyzing longitudinal data in the presence of missing data using a marijuana price survey

2015 ◽  
Vol 5 (2) ◽  
pp. 137-148 ◽  
Author(s):  
Jeremy N.V Miles ◽  
Priscillia Hunt
Keyword(s):  
Missing Data ◽  
Statistical Power ◽  
Criminal Psychology ◽  
Likelihood Estimation ◽  
Data Sets ◽  
Applied Psychology ◽  
Artificial Data ◽  
Data Set ◽  
Content Type ◽  
Biased Estimates

Purpose – In applied psychology research settings, such as criminal psychology, missing data are to be expected. Missing data can cause problems with both biased estimates and lack of statistical power. The paper aims to discuss these issues. Design/methodology/approach – Recently, sophisticated methods for appropriately dealing with missing data, so as to minimize bias and to maximize power have been developed. In this paper the authors use an artificial data set to demonstrate the problems that can arise with missing data, and make naïve attempts to handle data sets where some data are missing. Findings – With the artificial data set, and a data set comprising of the results of a survey investigating prices paid for recreational and medical marijuana, the authors demonstrate the use of multiple imputation and maximum likelihood estimation for obtaining appropriate estimates and standard errors when data are missing. Originality/value – Missing data are ubiquitous in applied research. This paper demonstrates that techniques for handling missing data are accessible and should be employed by researchers.

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