Engineer Gas Turbine

Profile

• * years of total experience and * years in the field of Reliability and Safety Engineering.

• Life data analysis

• Reliability prediction (Mechanical systems using NPRD data and NSWC)

• Accelerated Life Testing (ALT) test plan protocol preparation and execution, post data analysis

• Reliability growth testing and analysis of test data

• FMEA/FMECA (System level/ part level)

• Fault Tree Analysis (FTA)

• Functional Hazard Analysis (FHA)

• Risk Analysis / Safety Analysis

• System Reliability (Using RBD)

• System Safety Analysis- PSSA/SSA

• MMEL – Master Minimum Equipment List

• Expertise in implementing ARP 4761

• Expertise in implementing ARP 4754

Software proficiency:

• Reliasoft – Weibull ++7, ALTA 6 Pro, RGA6, Blocksim6

• Relex 2007- Prediction, FMEA, RBD, FTA

• CAFTA

• Minitab 14

• MS Excel

Educational Qualification:

• Master of Technology in Reliability Engineering from IIT Kharagpur

• Bachelors in Aeronautical Engineering from AeSI, New Delhi

• CRE (Certified Reliability Engineer) from ASQ, USA

• Six Sigma GB Certified from GE India Technology Center

Experience:

After MTech started career as a Reliability Engineer with GE India Technology Centre in 2006 Jun 5th, dealt with Condition based maintenance and Life data analysis of Gas Turbines.

In 2008 Jan, moved to HCL Technologies as a Lead Engineer (Reliability), it is a service company for Aero, Medical, Auto and HiTech domains. My contributions mainly in the fields of Medical equipement Reliability and Aerospace Safety projects and Training the people in HCL on Reliability and Safety analysis. I have been promoted as Technical Leader –Reliability in Jan 09, from then leading a team for client MEGGITT for their Reliability and Safety compliance requirements.

I have also trained the HCL ERS teams on PPM module and Statistics part of CMMi implementation.

Presently, I have started my own company to serve the clients needs in the field of Statistics and Reliability Engineerin

Life data analysis

Case study: Condition Based Maintenance

This is an ongoing project for all models of Gas Turbines designed by the company; involve Statistical and Reliability analysis based on the condition of the Gas Turbine components in the field to optimize the life decisions regarding Remove, Repair and Replacement at component and system level. This also helps to increase the availability of Gas Turbine by reducing unwanted shut down of the Gas Turbine. It achieve the goals of the contractual requirements with the customer also allows to skip few cycles of maintenance with the confidence given by Reliability analysis

Reliability growth Analysis

Case study: Reliability growth Analysis, Gas turbine combustor seal

The objective of the project is to validate the new designed part of Gas Turbine, involves Reliability growth analysis of a new design of cloth seal used between combustor and turbine section of the Gas Turbine, field data is collected for old design (metal seal) and cloth seal and modeled using Duane Growth model. This project allowed extending the inspection interval of the Combustor.

Tools: Weibull++7, RGA 6,

Approach

The data was collected for all cloth seal failures before and after the design changes, all the data collected in Cumulative fired Hours of the gas turbine at respective failures. The entire fleet of gas turbine data has been segregated to separate out the cloth seal failures from the pool of different other failures, Duane model has been used for the Analysis.

Reliability Prediction and FMEA

Case study: for Pump – Motor Assembly

Introduction:

Carried out reliability analysis and FMEA for Brushless DC Motor driven Fuel Booster Pump. The project included prediction of Mean Time between Failure (MTBF), Mean Time between Critical Failure (MTBCF) and Failure Mode & Effects Analysis (FMEA) for the complete mechanical interface that includes pump and brushless motor assembly. The objective of the analysis is to assess reliability of the pump during the design phase so as to identify appropriate design task for addressing the concern during early phase of development. Analysis provided quantitative assessment of design reliability of BLDC fuel booster pump which was compared with existing brushed motor reliability.

Approach Followed:

1. MTBF

The mathematical model is used to predict the total failure rate of the functional groups / sub-system using failure rate of each constituent part.

All the individual mechanical part data is obtained from the NPRD data base.

2. MTBCF

Mean time between critical failures (MTBCF) provides an assurance against critical functional failure of the pump. Failure modes that cause total loss of pump function or may lead to fire hazard have been considered as critical failures which have been referred from FMEA.

The respective mode failure rate has been calculated for estimation of overall pump MTBCF.

3. FMEA

The analysis carried to the component level and the failure effect on the system has been assessed.

Fault Tree Analysis (FTA) for Wheel Brake System

Introduction:

FTA is top down deductive failure analysis. Developed multiple Fault Trees using system information including functional details and redundancy of Wheel Brake System. The system include brake unit / actuator, Electro Hydraulic Servo Valve (EHSV) based brake control valve, Shut off valve and controller.

Tools:

Cafta

Approach

Developed logic tree with system information for all critical failure conditions of the system. Identified all contributing failure causes leading top event of the tree. Substituted failure data for all contributing failure events and estimated top event failure probability. Identified single failure conditions leading to top event and assessed reliability and safety of the system.

Personal Information

• Nationality : Indian

• Gender : Male

• Marital Status : Married

• Father’s Name : A. Koteswara Rao

• Languages known : Telugu, English, Hindi

Place: Bangalore

Date: Jan 06, 2011 (Anil Kumar Ammina)

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