AN NEW ALGORITHIM FOR IMPROVING RELIABILITY OF A SERIES BASED DESIGNED SYSTEM BY INCREASING ELECTRONIC COMPONENTS RELIABILITY

Similar documents
LESSON 6 MANAGERIAL ROLES IN SMALL BUSINESS

TAGUCHI APPROACH TO DESIGN OPTIMIZATION FOR QUALITY AND COST: AN OVERVIEW. Resit Unal. Edwin B. Dean

POLI 457 Human Resource Development and Management

Software Project Risk Assessment and Effort Contingency Model Based on COCOMO Cost Factors

Intelligently Choosing Testing Techniques

PRODUCT-MIX ANALYSIS WITH DISCRETE EVENT SIMULATION. Raid Al-Aomar. Classic Advanced Development Systems, Inc. Troy, MI 48083, U.S.A.

Generational and steady state genetic algorithms for generator maintenance scheduling problems

Modeling Software Project Defects With Fuzzy Logic Maps

Using the SA-CMM as a Tool for Estimating the User and Management Costs for Software Acquisition Projects

Foundation Certificate in Project Management

A Study on North East Corner Method in Transportation Problem of Operations Research and using of Object Oriented Programming Model

A Variable Capacity Parallel Machine Scheduling Problem

Why Does It Cost How Much? Edwin B. Dean * NASA Langley Research Center Hampton VA

A case study on Measurement of Degree of Performance of an Industry by using Lean Score Technique

Basic Linear Programming Concepts. Lecture 2 (3/29/2017)

SUMMARY OF MODULE The goals of a project are formulated after gathering facts and having discussions

Explaining the Increase in the Australian Average House Completion Time: Activity-based versus Workflow-based Planning

A reverse discount model for dynamic demands. Abhishek Chakraborty. Indian Institute of Management Calcutta

DEA Model: A Key Technology for the Future

RELIABILITY, AVAILABILITY AND MAINTAINABILITY CONCEPTS

The optimization of an industrial pneumatic supply system

Application of Statistical Methods to Analyze Groundwater Quality

A comparative study of ASM and NWCR method in transportation problem

Locational Marginal Pricing (LMP): Basics of Nodal Price Calculation

Chapter #2: Cost Concepts and Design Economics

Effect of Transportation Model on Organizational Performance: A Case Study of MTN Nigeria, Asaba, Delta State, Nigeria

Inventory Model Involving Controllable Lead Time through New Approach

Application of AHP in Education Legislation Project. Ying-ying YAO and Yong-sheng GE *

Measuring Promotion Effectiveness in Times of Increased Consumer Spending WHITE PAPER

The Use of Multi-Attribute Utility Theory to Address Trade-Offs for the Balanced Scorecard

Applying Quality Engineering Technique to Improve Wastewater Treatment

Operational Availability Modeling for Risk and Impact Analysis

ACTIVITY SCHEDULING IN THE DYNAMIC, MULTI-PROJECT SETTING: CHOOSING HEURISTICS THROUGH DETERMINISTIC SIMULATION. Robert C. Ash

Study on Management Accounting Change Management and Innovation Dongxia Liu 1

Presented by Renaldo de Jager 11-1

Integration of JIT /MRP in inventory systems. Abstract:

Choosing a TSO Supplier

DYNAMIC TESTING OF FULL-SCALE 11-STORY RC BUILDING AND ITS 3-STORY STRUCTURAL PART: COMPARISON OF THE RESULTS AND SEISMIC RESISTANCE ESTIMATION

Feedforward aeration control of a Biocos wastewater treatment plant

STRENGTH OF PLATES OF RECTANGULAR INDUSTRIAL DUCTS

Methodology for Selecting the Preferred Networked Computer System Solution for Dynamic Continuous Defense Missions

Numerical investigation of tradeoffs in production-inventory control policies with advance demand information

International Journal of Advanced Research in Computer Science and Software Engineering

AN EXPERIMENTAL ANALYSIS OF ADVERTISING STRATEGIES

1. Introduction to Operations Research (OR)

LMP Implementation in New England

L & L Mitigation Aid for Effective Project Management System

The Impact of Design Rework on Construction Project Performance

EFFECT OF RIBS AND STRINGER SPACINGS ON THE WEIGHT OF AIRCRAFT COMPOSITE STRUCTURES

December 25, 2017 CHAPTER 4 SUPPORTING PLANNING AND CONTROL: A CASE EXAMPLE

Genetic Algorithms and Sensitivity Analysis in Production Planning Optimization

Software Reliability Modeling with Test Coverage: Experimentation and Measurement with A Fault-Tolerant Software Project

ISSN Number: Modelling Time-Constrained Software Development. Dr. Antony Powell Department of Management Studies, University of York

A Field Operational Test With Young Volunteers Driving With ISA in Combination With Incentive For Not Speeding

Supply Chain Management: Supplier Selection Problem with multi-objective Considering Incremental Discount

UNIVERSITY OF NOTTINGHAM. Discussion Papers in Economics DOES PRODUCT PATENT REDUCE R&D?

Using Software Process Simulation to Assess the Impact of IV&V Activities 1

Short-Run Manufacturing Problems at DEC 2. In the fourth quarter of 1989, the corporate demand/supply group of Digital

DEVELOPMENT OF A DYNAMIC PROGRAMMING MODEL FOR OPTIMIZING PRODUCTION PLANNING. the Polytechnic Ibadan, Mechatronics Engineering Department; 3, 4

A General Framework for Infrastructure System Reliability Modelling and Analysis

APPLYING OF AHP METHODOLOGY AND WEIGHTED PROPERTIES METHOD TO THE SELECTION OF OPTIMUM ALTERNATIVE OF STOCK MATERIAL

Industry Perspectives on FERC Standard Market Design

Hyperknowledge in Practice - Users Attitudes to Active DSS

Reliability Analysis Techniques: How They Relate To Aircraft Certification

Steven W. Hays Gambrell 431. (803) Office Hours: 4-6 W Office: Gambrell 339

Activity Based Costing for Construction Companies

By: Adrian Chu, Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington November 12, 2009.

Application of a Genetic Algorithm to improve an existing solution for the. General Assignment Problem.

RFID: ROI Opportunities after the Sunk Cost. Teodor D. Simeonov

Project Planning, Scheduling and Preparation of Quality Assurance Control Documents

A Strategic Outlook for Managing Information and Communication Technology: An Overview

Project and Production Management Prof. Arun Kanda Department of Mechanical Engineering Indian Institute of Technology, Delhi

The Impact of Information Technology and Internet in the Construction Industry

Strategic Managerial Finance

Business Process Re-engineering and Automation(BPRA)

Chapter-3. Software Metrics and Reliability

e-commerce, a New Strategy for Marketplaces

Information System of Scenario Strategic Planning

Evaluating Effectiveness of Software Testing Techniques With Emphasis on Enhancing Software Reliability

OPTIMIZATION OF ROCK STONE SELECTION IN SHORE PROTECTION PROJECTS - CASE STUDY: GAZA BEACH CAMP SHORE PROTECTION PROJECT

TRANSPORTATION PROBLEM FOR OPTIMALITY

Available online at ScienceDirect. Procedia Engineering 186 (2017 )

The importance of Balanced Scorecard in business operations

Chapter 3. Information Systems Development. McGraw-Hill/Irwin. Copyright 2007 by The McGraw-Hill Companies, Inc. All rights reserved.

Journal of Multidisciplinary Engineering Science and Technology (JMEST) ISSN: Vol. 1 Issue 5, December

B.H. Far

Management tenth edition

COURSE CONTENT. Course title & the credit unit: Computer-aided Design and Computer-aide Manufacturing (2 UNITS) Course status - compulsory

On the exact calculation of the mean stock level in the base stock periodic review policy

Resource Critical Path Approach to Project Schedule Management

C. Wohlin, P. Runeson and A. Wesslén, "Software Reliability Estimations through Usage Analysis of Software Specifications and Designs", International

Using the Analytic Hierarchy Process in Long-Term Load Growth Forecast

Information Systems Development

BUSINESS ECONOMICS. 16: Project Appraisal and Impact Analysis PAPER NO. 16 : PROJECT APPRAISAL AND IMPACT ANALYSIS MODULE NO. 6 : FEASIBILITY STUDY

CHAPTER 4 A FRAMEWORK FOR CUSTOMER LIFETIME VALUE USING DATA MINING TECHNIQUES

An Integrated Three-Tier Logistics Model

Effect of Spacing of Grid Beam and its Depth on Peripheral beams in Grid Floor Frame

Management. Prof. S P Bansal Vice Chancellor Maharaja Agrasen University, Baddi

COPYRIGHTED MATERIAL RELIABILITY ENGINEERING AND PRODUCT LIFE CYCLE 1.1 RELIABILITY ENGINEERING

BEST PRACTICES IN BUSINESS PROCESS REDESIGN: SURVEY RESULTS AMONGST DUTCH AND UK CONSULTANTS

Transcription:

AN NEW ALGORITHIM FOR IMPROVING RELIABILITY OF A SERIES BASED DESIGNED SYSTEM BY INCREASING ELECTRONIC COMPONENTS RELIABILITY Sanjay 1, Anita 2, Shashank 3, Seema 4, Prof. [Dr.] K.K. Saini 5 1,2,3,4,5 Dronacharya College of Engineering, Gurgaon, (India) ABSTRACT Reliability engineers are very often called upon to make decisions as to whether to improve a certain electronic component or components in order to achieve minimum required system reliability in small scale industry (SSI). (Note: This minimum required system reliability is for a specified time.) There are two approaches to improving the reliability of a system: fault avoidance and fault tolerance. Fault avoidance is achieved by using highquality and high-reliability electronic components and is usually less expensive than fault tolerance. Fault tolerance, on the other hand, is achieved by redundancy. Redundancy can result in increased design complexity and increased costs through additional weight, space, etc. Before deciding whether to improve the reliability of a system by fault tolerance or fault avoidance, a reliability assessment for each electronic component in the system should be made. In this paper series designed based system reliability is discussed where reliability of system is increased by increasing electronic components reliability in small scale industry. Keywords: System Reliability, Fault Tolerance, Fault Avoidance, Redundancy & Design Complexity. I. INTRODUCTION Modern systems and devices (electronic systems, electronic devices and components, electrical and mechanical systems) are made to operate under a number of extreme environmental and operating conditions. The resulting stresses can affect the working-life of the electronic components and test their endurance to the limit. Failure of systems and devices can be categorized in a number of ways such that major failures, minor failures, parametric failures, catastrophic failures etc. System which we dealt in this work will be followed by boundary condition. Output of these systems depends upon the output of Electronic Components used in the system. There are small and simple systems or big and complex systems. Small systems may be like electronic toys, weighing machines, calculators etc. and big systems may be like complicated Aircraft monitoring systems, Missile detection and shooting system, Banking system, Mobile system etc. System will do production or it will be directly related to the revenue generation. In both the cases operation has to be done successfully. System may be any but analysis of it should be thoroughly. Otherwise there may fault occur at later stage. Cost factor play important role if the electronic component is to be changed or not. If cheap and easily available electronic component is changed before it expected life than the reliability of the system will remain as required. Otherwise if we change after the 1939 P a g e

failure than complete system will come at stand still and it will effect the production as well as revenue generation. Electronic components whose chances of failure are more than they should be connected in parallel. In summery electronic components should be replaced before their expected life. It is better to avoid group replacement. It depends on the cost factor of electronic component whether it has to be replaced individually or in group. II. DESIGN ANALYSIS Once the reliability values for the components have been quantified, an analysis can be performed in order to determine if that system's reliability goal will be met. If it becomes apparent that the system's reliability will not be adequate to meet the desired goal at the specified mission duration, steps can be taken to determine the best way to improve the system's reliability so that it will reach the desired target. In a system with three electronic components connected reliability-wise in series. The reliabilities for each component for a given time are: R 1 = 70%, R 2 = 80% and R 3 = 90%. A reliability goal, R G = 85%, is required for this system. The current reliability of the system is: ------------ (1) Obviously, this is far short of the system's required reliability performance. It is apparent that the reliability of the system's constituent electronic components will need to be increased in order for the system to meet its goal. First, it will be tried to increase the reliability of one electronic component at a time to see whether the reliability goal can be achieved. Figure 1.2 shows that even by raising the individual component reliability to a hypothetical value of 1 (100% reliability, which implies that the component will never fail), the overall system reliability goal will not be met by improving the reliability of just one component. The next logical step would be to try to increase the reliability of two components. The question now becomes: which two? One might also suggest increasing the reliability of all three components. A basis for making such decisions needs to be found in order to avoid the "trial and error" aspect of altering the system's components randomly in an attempt to achieve the system reliability goal. As the reliability goal for the preceding example could not be achieved by increasing the reliability of just one component. There are cases, however, where increasing the reliability of one component results in achieving the system reliability goal. Consider, for example, a system with three components connected reliability-wise in parallel. Three electronic components connected parallel wise will make the system to work in better way as if one system fails then other system are there to cover up. Thus for better production parallel system is preferred than series system. 1940 P a g e

International Journal of Advance Research In Science And Engineering http://www.ijarse.com Figure 1.2: Change in System Reliability if A Three-Unit Series System Due to Increasing The Reliability of Just one Component. The reliabilities for each component for a given time are: R 1 = 60%, R 2 = 70% and R 3 = 80%. A reliability goal, R G = 99%, is required for this system. The initial system reliability is: ---------- (2) The current system reliability is inadequate to meet the goal. Once again, we can try to meet the system reliability goal by raising the reliability of just one of the three components in the system. III. RELIABILITY GOAL OF SYSTEM CAN BE IMPROVED BY CHANGING RELIABILITY OF ELECTRONIC COMPONENTS As reliability for the system is fixed for specific problem in system, thus it can be improved by improving reliability of individual electronic components. From Figure 1.3, it can be seen that the reliability goal can be reached by improving Component 1, Component 2 or Component 3. The reliability engineer is now faced with another dilemma: which component's reliability should be improved? This presents a new aspect to the problem of allocating the reliability of the system. 1941 P a g e

International Journal of Advance Research In Science And Engineering http://www.ijarse.com Figure 1.3: Meeting a Reliability Goal Requirement by Increasing a Component's Reliability. Since we know that the system reliability goal can be achieved by increasing at least one unit, the question becomes one of how to do this most efficiently and cost effectively. We will need more information to make an informed decision as to how to go about improving the system's reliability. IV. COST VALUES TO THE RELIABILITIES OF THE SYSTEM S COMPONENTS How much does each component need to be improved for the system to meet its goal? How feasible is it to improve the reliability of each component? Would it actually be more efficient to slightly raise the reliability of two or three components rather than radically improving only one? In order to answer these questions, we must introduce another variable into the problem: cost. Cost does not necessarily have to be in rupees. It could be described in terms of non-monetary resources, such as time. By associating cost values to the reliabilities of the system's components, we can find an optimum design that will provide the required reliability at a minimum cost. There is always a cost associated with changing a design due to change of vendors, use of higher-quality materials, retooling costs, administrative fees, etc. The cost as a function of the reliability for each component must be quantified before attempting to improve the reliability. Otherwise, the design changes may result in a system that is needlessly expensive or over designed. Developing the "cost of reliability" relationship will give the engineer an understanding of which components to improve and how to best concentrate the effort and allocate resources in doing so. The first step will be to obtain a relationship between the cost of improvement and reliability. The preferred approach would be to formulate the cost function from actual cost data. This can be done from past experience. However, there are many cases where no such information is available. For this reason, a general (default) behavior model of the cost versus the component's reliability was developed for performing reliability optimization. One needs to quantify a cost function for each component, C i, in terms of the reliability, R i, of each component, or: This function should: 1. Look at the current reliability of the component, R Current. ----------------- (3) 1942 P a g e

2. Look at the maximum possible reliability of the component, R Max. 3. Allow for different levels of difficulty (or cost) in increasing the reliability of each component. It can take into account: o Design issues. o Supplier issues. o State of technology. o Time-to-market issues, etc. V. CONDITIONS ADHERED TO COST FUNCTION Thus, for the cost function to comply with these needs, the following conditions should be adhered to: 1. The function should be constrained by the minimum and maximum reliabilities of each component (i.e. reliability must be less than one and greater than the current reliability of the component or at least greater than zero). 2. The function should not be linear, but rather quantify the fact that it is incrementally harder to improve reliability. For example, it is considerably easier to increase the reliability from 90% to 91% than to increase it from 99.99% to 99.999%, even though the increase is larger in the first case. 3. The function should be asymptotic to the maximum achievable reliability. VI. CONCLUSIONS In this work following conclusions are made: Each electronic components reliability cannot be improved after certain parameters. It is practically not feasible to improve the reliability of every electronic component in every case. It is actually be more efficient to slightly raise the reliability of two or three components rather than radically improving only one. REFERNCES [1]. Lloyd, D.K. and M. Lipow, Reliability, Management, and Mathematics, Prentice- Hall, Englewood Cliffs, 2003. [2]. Roberts, N.H., Mathematical Methods in Reliability Engineering, McGraw Hill, New York, 2002. [3]. Killen, Carroll G., Factors Influencing Electronic Components Reliability, Proceedings of the Thirty Sixth Annual Conference On Electronic Components, New York, July 2001. [4]. Miles, Raymond C., Statistical Design- A Means To Better Products Of Lower Cost, IRE Transactions of the Professional Group on Reliability and Quality Control Of Electronic Components, April 2000. [5]. Tall, M.M., Component Failure Problem In Electronic Equipment, pp. 156-160, Proceedings of Symposium, Progress in Quality Electronic Components, May 5-7, 2001,Washington, D.C. [6]. Osche, R. A., Electronic Applications Reliability Review For Small Scale Industry, Issue No. 3, 1999, RETMA, pp. 3-5, Reliability Of Electronic Systems in Small Scale Industry. [7]. Qarris, V. and Hall, M.M., Prediction of Electronic Equipment Reliability in Small Scale Industry AIEE Summer General Meeting, Swampsctt, Mass., June, 2000 1943 P a g e

[8]. Myers, R.H., K.L. Wong and H.M. Gordy, Reliability Engineering for Electronic Systems, John Wiley, New York, 1994. [9]. Dummer, G.W.A. and N. Griffin, Electronic Reliability - Calculation and Design, Pergamon Prss, Oxford,1990. 1944 P a g e