scholarly journals Two-sided M-Bayesian limits of credibility of reliability parameters in the case of zero-failure data and a case study

2020 ◽  
Vol 15 (1/2) ◽  
pp. 89
Author(s):  
Wanyi Dai ◽  
Siqi Li ◽  
Mei Zhang ◽  
Yueming Hu ◽  
Dongfang Mei
Keyword(s):  
Reliability Parameters ◽  
Failure Data

Overview of Wind Turbine Field Failure Databases: A Discussion of the Requirements for an Analysis

2018 ◽  
Author(s):  
Roozbeh Bakhshi ◽  
Peter Sandborn
Keyword(s):  
Statistical Analysis ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farms ◽  
Onshore Wind ◽  
Failure Times ◽  
Reliability Parameters ◽  
Failure Data ◽  
Offshore Installations ◽  
Field Failure

With renewable energy and wind energy in particular becoming mainstream means of energy production, the reliability aspect of wind turbines and their sub-assemblies has become a topic of interest for owners and manufacturers of wind turbines. Operation and Maintenance (O&M) costs account for more than 25% of total costs of onshore wind projects and these costs are even higher for offshore installations. Effective management of O&M costs depends on accurate failure prediction for turbine sub-assemblies. There are numerous models that predict failure times and O&M costs of wind farms. All these models have inputs in the form of reliability parameters. These parameters are usually generated by researchers using field failure data. There are several databases that report the failure data of operating wind turbines and researches use these failure data to generate the reliability parameters through various methods of statistical analysis. However, in order to perform the statistical analysis or use the results of the analysis, one must understand the underlying assumptions of the database along with information about the wind turbine population in the database such as their power rating, age, etc. In this work, we analyze the relevant assumptions and discuss what information is required from a database in order to improve the statistical analysis on wind turbines’ failure data.

scholarly journals Assessing the annual risk of vehicles being hit by a rainfall-induced landslide: a case study on Kennedy Road in Wan Chai, Hong Kong

2020 ◽  
Vol 20 (6) ◽  
pp. 1833-1846 ◽  
Author(s):  
Meng Lu ◽  
Jie Zhang ◽  
Lulu Zhang ◽  
Limin Zhang
Keyword(s):  
Hong Kong ◽  
Failure Probability ◽  
Slope Failure ◽  
Failure Time ◽  
Suggested Method ◽  
Risk Level ◽  
Annual Number ◽  
Failure Data ◽  
Moving Vehicles

Abstract. Landslides threaten the safety of vehicles on highways. When analyzing the risk of a landslide hitting moving vehicles, the spacing between vehicles and the types of vehicles on the highway can be highly uncertain and have often been omitted in previous studies. Using a highway slope in Hong Kong as a case study, this paper presents a method for assessing the risk of moving vehicles being hit by a rainfall-induced landslide; this method also allows for the possible number of different types of vehicles hit by the landslide to be investigated. In this case study, the annual failure probability of the slope is analyzed based on historical slope failure data from Hong Kong. The spatial impact of the landslide is evaluated based on an empirical run-out prediction model. The consequences of the landslide are assessed using probabilistic modeling of the traffic, which can consider uncertainties in the vehicle spacing, vehicle types and slope failure time. Using the suggested method, the expected annual number of vehicles and people hit by the landslide can be conveniently calculated. This method can also be used to derive the cumulative frequency–number of fatalities curve for societal risk assessment. Using the suggested method, the effect of factors like the annual failure probability of the slope and the density of vehicles on the risk level of the slope can be conveniently assessed. The method described in this paper can provide a new guideline for highway slope design in terms of managing the risk of landslides hitting moving vehicles.

scholarly journals RELIABILITY IMPROVEMENT METHODOLOGY FOR CONSUMER PRODUCTS - A CASE STUDY

2013 ◽  
pp. 88-92
Author(s):  
SHAIK HUSSAIN BASHA ◽  
SUDHANGSHU CHAKRAVORTY
Keyword(s):  
Consumer Products ◽  
Design Modification ◽  
Root Cause ◽  
Reliability Improvement ◽  
Failure Data ◽  
World Class ◽  
Warranty Cost ◽  
Field Reliability ◽  
Field Failure

The objective of every industry is to bring world-class quality products to the market in shortest possible time with least expenses. To meet this objective manufacturer’s always remains non compliant with Reliability requirement of the products due to which field failure rate increases and in turn increases the warranty cost. In this work, an attempt has been made to improve the field reliability for consumer product through a proposed step by step Reliability Improvement Methodology. The proposed methodology includes analysis of field failure data, failure analysis for identifying root cause, experimental investigation to confirm root causes, design modification recommendations and improvement validation through accelerated testing. Further, this analysis helps the manufacturers in warranty extension decision making for the existing products and in the improvement of the next generation product’s performance which directly increases the brand image and profits of an organization.

scholarly journals Integration of FMECA and statistical snalysis for predictive maintenance

2021 ◽  
Vol 2 (1) ◽  
pp. 33
Author(s):  
Rabia Ghani
Keyword(s):  
Production Line ◽  
Manufacturing Industry ◽  
Failure Modes ◽  
Remaining Useful Life ◽  
Predictive Maintenance ◽  
Time To Failure ◽  
Failure Data ◽  
Criticality Analysis

<p>The estimation of time-to-failure of machines is of utmost importance in the Manufacturing Industry. As the world is moving towards Industry 4.0, it is high time that we progress from the traditional methods, where we wait for a breakdown to occur, to the prognostics based methods. It is the need of the era to be aware of any incident before it occurs. This study provides application of Statistical-based Predictive maintenance. A BOPP Production line has been considered as a case study for this research. Since the inception of the line in 2013, it is evident that 60% of breakdowns are due to lack of maintenance and timely replacement of bearings. Therefore, the research is based on the application of FMECA (Failure Modes, Effects and Criticality Analysis) to determine which bearing in the production line is most prone to failure and determination of which statistical model best fits the failure data of the most critical bearing. The result provides the best distribution fit for the failure data and the fit can be utilized for further study on RUL (Remaining Useful Life) of the bearing through Bayesian Inference.</p>

scholarly journals ANALYSIS OF DOWNTIME IN A TYPICAL NIGERIAN MULTINATIONAL BOTTLING COMPANY

2020 ◽  
Vol 26 (3) ◽  
pp. 88-96
Author(s):  
ABAFI JOEL ◽  
OKE ADEKOLA
Keyword(s):  
Manufacturing System ◽  
Failure Data

Failure data were extracted from the report book of the case study company. These data were stratified and analysed.Data stratification was pivotal in the separation of failure data into smaller and more defined form based on a predetermined set of criteria. Filler system was found to have the highest percentage failure occurrences; hence a standby filler system became the best option. The study concluded that, although in a production/manufacturing system, downtime is inevitable but it can be limited to the planned downtime with respect to the typical Nigerian multinational bottling company.

Reliability Design and Case Study of a Refrigerator Compressor Subjected to Repetitive Loads

2007 ◽  
Author(s):  
Seong-Woo Woo ◽  
Dennis L. O’Neal ◽  
Yongchan Kim
Keyword(s):  
Failure Modes ◽  
Design Parameters ◽  
Refrigeration Cycle ◽  
Life Testing ◽  
Reliability Design ◽  
Analysis And Design ◽  
Reliability Parameters ◽  
Design Changes ◽  
Field Failure

A newly designed crank shaft of a compressor for a side-by-side (SBS) refrigerator was studied. Using standard mass and energy conservation balances, a variety of compressor loads typically found in a refrigeration cycle were analyzed. The laboratory failure modes and mechanisms were compressor locking and crank shaft wear. These were similar to those of the failed samples in the field. Failure analysis, accelerating life testing (ALT), and corrective action were used to identify the key reliability parameters and their level. The design parameters of the crank shaft included the hole locations and the groove of the crank shaft used for oil lubrication, crank shaft hardness, and thrust washer interference. Based on the analysis and design changes, the B1 life of the new design is now over 10 years with a yearly failure rate of 0.01 percent. A procedure was recommended for refrigerator parts design which included five steps.

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