Lecture 21: Variation Risk Management
|
|
- Lorin O’Brien’
- 6 years ago
- Views:
Transcription
1 Lecture : Variatio Ris Maagemet Quality Types Total Quality Huma resources Maufacturig Orgaizig ad operatig Product ad Services Desig
2 What is variatio? Variatio = Deviatio from omial variatio: the etet to which or the rage i which a thig varies vary: to mae differeces betwee items All processes itroduce variatio ito part dimesios Variatio impacts performace Variatio impacts cost 3 Nomial vs. Variatio Nomial Defiitio the target value that the desig tried to achieve Quality of omial desig Feature set Loo/feel Variatio Defiitio Variatio is the small deviatio from omial itroduced by the eviromet maufacturig process degradatio Quality of desig for variatio Robust to iteral variatio Robust to eteral variatio 4
3 Comple Product 5 Why is this a iterestig problem? There are thousads of articles o variatio ad robust desig but. Compaies cotiue to struggle with variatio ad its effects why? 6 3
4 Did t Taguchi solved this problem already? Desig of Eperimets is oe tool of may used i the variatio ris maagemet process Tolerace desig ad parameter desig methods are limited to sigle cause/effect methods Robust desig methods ca be used for sigle subsystems Other researchers Simulatio tools to predict variatio for particular problems Robust cocept desig 7 What problems have ot bee solved Compleity It is ot eough to loo at sigle cause ad effect, the product (sub-assembly) must be evaluated as a system Prioritizatio There are ot eough resources to improve ad cotrol all processes Data supported processes The data sources are limited 8 4
5 Source of Compleity Compleity Prioritizatio Data Sources Process Variatio Part Dimesio Variatio Subassembly dimesioal variatio Fuctioal Variatio Customer Dissatisfactio Stampig variatio Door pael shape Gap betwee the door ad frame Ecess wid oise ad lea Customer Dissatisfactio Locatig system for - holes Mis-located part Need for a custom shim Ecess weight Customer Dissatisfactio 9 Compleity Methods of Maagig Data Compleity Prioritizatio Data Sources Key characteristics: The set of small set of product features whose variatio will create sigificat loss 0 5
6 Key Characteristics Flowdow Compleity Prioritizatio Data Sources Characteristics of flowdow May layers deep May cotributors Cotour Cross coupled Cotour of the Mai Torque Bo Drag Gap betwee the sis System Assembly Feature Fiture Height Spar Agle of Frot Spar Distace Betwee Spars Etrusio Agle of Rear Spar Process Eample from a medical product Compleity Prioritizatio Data Sources 6
7 Mathematical Model Compleity Prioritizatio Data Sources y y y i y f Product-KCs (= j Subsystem- KCs j l l jl l l Part-KCs (=l- Process- KCs (=l) ij = i f ( ( i, ( i,..., ( ) 3 y i y σ i Variatio Model Compleity Prioritizatio Data Sources = f (, i y = = i y i,..., y σ i ) y i y... σ i y... i σ yi determied usig VSA (variatio systems aalysis) Desig of Eperimets Product/process models 4 7
8 8 5 Matri Represetatio = ( ( ( ( ( ( ( ( ( K M M M M K K ô K ( 3 = l Kô ô ô ô T = ( ( ( ( ( ( ( ( ( K M M M M K K ä K ( 3 = l Kä ä ä ä D l Tó l ó Db b f f = = ad y y y i j j l l jl Compleity Prioritizatio Data Sources 6 Debate Demig: Zero Defects are best Ay attempt to reduce variatio ad its impact will have a positive retur $0K $00K $00K $300K $400K $500K $600K Desired variatio Cost for Reductio Cost for Rewor Net cost Jura: Need to balace the cost of variatio agaist the cost of etra precisio Compleity Prioritizatio Data Sources
9 Problem defiitio Compleity Prioritizatio Data Sources Quality is Free, but Quality requires a ivestmet of resources ad there are limited resources i a compay. 7 Why is prioritizatio o-trivial? Compleity Prioritizatio Data Sources Variatio is assessed at the system The user sees the paper jam ot the roller diameter Variatio is cotrolled at the feature level There are t eough resources to cotrol every dimesio or process Importat thig is to fid the critical few 8 9
10 Data sources Compleity Prioritizatio Data Sources Kowledge of the system is scattered throughout the orgaizatio Process capability data is available but ot used Cost data is scattered 9 Process capability data Compleity Prioritizatio Data Sources Measuremets tae o eistig products i productio Surrogate data used to predict variatio i future products 90% of all compaies we iterviewed had capability data 0% of them used the data durig desig 0 0
11 Process Capability Databases Dimesioal measuremets tae from part Dimesioal target values oted Process parameters etered ito PCDB Data values etered ito PCDB The Purpose of PCDBs Maufacturig improvemet Process cotrol/diagostics Historical referece Maufacturability aalysis Desig improvemet Part redesig New part desig Maufacturability aalysis PCDB creatio Maufacturig process results are measured, etered ito PCDB Process target values are documeted Data Materi may be orgaized Dateby: al Machi Proces e s Operat Featur or The Problem Missig Data i PCDBs Hiders Desig Missig data is caused by No data collectio from process Occurrece OR New process: o precedet Tolerace query for process X NO DATA µ =? σ =? mi =? ma =? Missig data results i Ureliable predictio of process capabilities Less efficiet desig processes ad maufacturig plas Project Goal Develop methods to reliably predict values for missig data Mea Variace Tolerace
12 Variatio Ris Maagemet Defiitio Systematic idetificatio, assessmet ad mitigatio of variatio ris through the desig process to most effectively reduce the impact of variatio give limited resources Assumptio Variatio will always cause degradatio i quality. Desig/maufacturig/quality eped resources to reduce the magitude ad/or impact of variatio Problem is where do you put resources to most effectively reduce the cost of variatio. 3 Ris Two parts to ris Chace of failure (P) Cost of failure (C) Mea cost of variatio C*P Chace of Failure low high Cost of Failure low high Miimal ris?? High Ris 4
13 VRM Stages Idetificatio Idetify variatio sesitive system requiremets Idetify system, sub-system, feature ad process characteristics that may cotribute to the system variatio Assessmet Quatify the probability of variatio (P) Quatify the cost of variatio (C) Mitigatio Select mitigatio strategy based o costs, schedule ad strategic impact Eecute the strategy 5 Variatio Sesitive Customer Requiremets What requiremets are liely to be sesitive to variatio? Eamples Steps ad gaps Flaes i pritig Ueve i depositio What are the toleraces/latitudes Idetificatio Assessmet Mitigatio 6 3
14 Two methods of Assessmet Aggregated Usig a models of variatio to tae process capability ad flow it up to chec quality RSS, VSA Desegregated Usig models of variatio to allocate variatio dow the tree Tolerace allocatio Used i cojuctio Idetificatio Assessmet Mitigatio 7 Assessmet Three parts to assessmet Sesitivity to variatio Process variatio Cost of system variatio Ris System Variatio Cost of Variatio Sesitivity Process Variatio 8 4
15 Failure rate LL i y i m i UL i UL U L P C p = failure = pdf ( y) 6σ LL µ LL UL C p = mi, 3σ 3σ Idetificatio Assessmet Mitigatio µ 9 Relatioship betwee Tolerace ad s For a Cp =.33 (ormal accept levels) UL LL.33 = 6σ UL LL = 8σ Idetificatio Assessmet Mitigatio 30 5
16 Cost of Variatio: Taguchi Loss fuctio $ Prob. Deviatio from Mea L = (y m) Cost of adefectiveproduct = (Tolerace) A = Ä ó L = meavalue of (y m) mea = (b ó ) Idetificatio Assessmet Mitigatio 3 Variatio ris mitigatio strategies Desig Chage Desig Quality cotrol Ispect Chage Process Advaced maufacturig Moitor process Improve Process Factory Idetificatio Assessmet Mitigatio Variatio reductio 3 6
17 Mitigatio durig desig Desig chage Chage the geometry, features, parts to mae the product less sesitive to variatio Robust desig Process chage Specify a more precise process to reduce variatio Idetificatio Assessmet Mitigatio 33 Mitigatio durig productio Variatio Reductio Focused efforts to reduce variatio i processes Stadard operatios, maiteace schedules, etc.. Statistical Process cotrol Ogoig cotrol to prevet process degradatio Ispectio Each part is looed at idividually If it fails ispectio it is either scrapped or rewored. Idetificatio Assessmet Mitigatio 34 7
18 Compariso of strategies Yield Improvemet Recurrig Costs Norecurrig Costs High- Medium High - Medium Strategic Impact Desig Chage High Noe - Low High Process High-Medium Medium - High Chage Low Variatio Medium Low Medium Medium reductio Process Medium-low Medium - Low Medium Moitorig Low Ispectio Low Low Low Low Idetificatio Assessmet Mitigatio 35 How to select Resource availability Cost of effort Beefit of effort Calculated by baselie without cotrol cost with cotrol 36 8
19 Documetatio system Documetatio of variatio riss Several commo idustry methods IPPD data sheets Tailored databases Keys o drawigs Weaess No commo approach to documetatio No commercial systems Every team ivets a ew system 37 Summary Most compaies address variatio late i the desig process deped o SPC/ispectio rather tha desig chages prioritize efforts based o qualitative assessmets Barriers Lac of good models usable i the early stages of desig Lac of good documetatio systems Lac of good process capability databases 38 9
STRATEGIC. alliances & Services
STRATEGIC alliaces & Services Chesterto is a leadig iteratioal maufacturer of idustrial fluid sealig systems, advaced polymer composites, cleaers, lubricats ad idustrial speciality products. Sice 1884
More informationDesigning a learning system
CS 75 Itro to Machie Learig Lecture Desigig a learig system Milos Hauskrecht milos@pitt.edu 539 Seott Square, -5 people.cs.pitt.edu/~milos/courses/cs75/ Admiistrivia No homework assigmet this week Please
More informationService Oriented Enterprise Architecture and Service Oriented Enterprise
Approved for Public Release Distributio Ulimited Case Number: 09-2786 The 23 rd Ope Group Eterprise Practitioers Coferece Service Orieted Eterprise ad Service Orieted Eterprise Ya Zhao, PhD Pricipal, MITRE
More informationImproving Template Based Spike Detection
Improvig Template Based Spike Detectio Kirk Smith, Member - IEEE Portlad State Uiversity petra@ee.pdx.edu Abstract Template matchig algorithms like SSE, Covolutio ad Maximum Likelihood are well kow for
More informationChapter 3 MATHEMATICAL MODELING OF TOLERANCE ALLOCATION AND OVERVIEW OF EVOLUTIONARY ALGORITHMS
28 Chapter 3 MATHEMATICAL MODELING OF TOLERANCE ALLOCATION AND OVERVIEW OF EVOLUTIONARY ALGORITHMS Tolerace sythesis deals with the allocatio of tolerace values to various dimesios of idividual compoets
More informationOracle Balanced Scorecard
Oracle Balaced Scorecard User Guide Release 4.5 July 2001 Part No. A90873-01 Oracle Balaced Scorecard User Guide, Release 4.5 Part No. A90873-01 Copyright 1999, 2000, 2001, Oracle Corporatio. All rights
More information1 Enterprise Modeler
1 Eterprise Modeler Itroductio I BaaERP, a Busiess Cotrol Model ad a Eterprise Structure Model for multi-site cofiguratios are itroduced. Eterprise Structure Model Busiess Cotrol Models Busiess Fuctio
More informationMorgan Kaufmann Publishers 26 February, COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 5
Morga Kaufma Publishers 26 February, 28 COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 5 Set-Associative Cache Architecture Performace Summary Whe CPU performace icreases:
More informationn Learn how resiliency strategies reduce risk n Discover automation strategies to reduce risk
Chapter Objectives Lear how resiliecy strategies reduce risk Discover automatio strategies to reduce risk Chapter #16: Architecture ad Desig Resiliecy ad Automatio Strategies 2 Automatio/Scriptig Resiliet
More informationDesigning a learning system
CS 75 Machie Learig Lecture Desigig a learig system Milos Hauskrecht milos@cs.pitt.edu 539 Seott Square, x-5 people.cs.pitt.edu/~milos/courses/cs75/ Admiistrivia No homework assigmet this week Please try
More informationData Analysis. Concepts and Techniques. Chapter 2. Chapter 2: Getting to Know Your Data. Data Objects and Attribute Types
Data Aalysis Cocepts ad Techiques Chapter 2 1 Chapter 2: Gettig to Kow Your Data Data Objects ad Attribute Types Basic Statistical Descriptios of Data Data Visualizatio Measurig Data Similarity ad Dissimilarity
More informationIMP: Superposer Integrated Morphometrics Package Superposition Tool
IMP: Superposer Itegrated Morphometrics Package Superpositio Tool Programmig by: David Lieber ( 03) Caisius College 200 Mai St. Buffalo, NY 4208 Cocept by: H. David Sheets, Dept. of Physics, Caisius College
More informationEMPIRICAL ANALYSIS OF FAULT PREDICATION TECHNIQUES FOR IMPROVING SOFTWARE PROCESS CONTROL
Iteratioal Joural of Iformatio Techology ad Kowledge Maagemet July-December 2012, Volume 5, No. 2, pp. 371-375 EMPIRICAL ANALYSIS OF FAULT PREDICATION TECHNIQUES FOR IMPROVING SOFTWARE PROCESS CONTROL
More informationGE FUNDAMENTALS OF COMPUTING AND PROGRAMMING UNIT III
GE2112 - FUNDAMENTALS OF COMPUTING AND PROGRAMMING UNIT III PROBLEM SOLVING AND OFFICE APPLICATION SOFTWARE Plaig the Computer Program Purpose Algorithm Flow Charts Pseudocode -Applicatio Software Packages-
More informationEuclidean Distance Based Feature Selection for Fault Detection Prediction Model in Semiconductor Manufacturing Process
Vol.133 (Iformatio Techology ad Computer Sciece 016), pp.85-89 http://dx.doi.org/10.1457/astl.016. Euclidea Distace Based Feature Selectio for Fault Detectio Predictio Model i Semicoductor Maufacturig
More informationFuzzy Membership Function Optimization for System Identification Using an Extended Kalman Filter
Fuzzy Membership Fuctio Optimizatio for System Idetificatio Usig a Eteded Kalma Filter Srikira Kosaam ad Da Simo Clevelad State Uiversity NAFIPS Coferece Jue 4, 2006 Embedded Cotrol Systems Research Lab
More informationSAMPLE VERSUS POPULATION. Population - consists of all possible measurements that can be made on a particular item or procedure.
SAMPLE VERSUS POPULATION Populatio - cosists of all possible measuremets that ca be made o a particular item or procedure. Ofte a populatio has a ifiite umber of data elemets Geerally expese to determie
More informationOnes Assignment Method for Solving Traveling Salesman Problem
Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:
More informationBACHMANN-LANDAU NOTATIONS. Lecturer: Dr. Jomar F. Rabajante IMSP, UPLB MATH 174: Numerical Analysis I 1 st Sem AY
BACHMANN-LANDAU NOTATIONS Lecturer: Dr. Jomar F. Rabajate IMSP, UPLB MATH 174: Numerical Aalysis I 1 st Sem AY 018-019 RANKING OF FUNCTIONS Name Big-Oh Eamples Costat O(1 10 Logarithmic O(log log, log(
More informationA New Morphological 3D Shape Decomposition: Grayscale Interframe Interpolation Method
A ew Morphological 3D Shape Decompositio: Grayscale Iterframe Iterpolatio Method D.. Vizireau Politehica Uiversity Bucharest, Romaia ae@comm.pub.ro R. M. Udrea Politehica Uiversity Bucharest, Romaia mihea@comm.pub.ro
More informationCapability Analysis (Variable Data)
Capability Aalysis (Variable Data) Revised: 0/0/07 Summary... Data Iput... 3 Capability Plot... 5 Aalysis Summary... 6 Aalysis Optios... 8 Capability Idices... Prefereces... 6 Tests for Normality... 7
More informationEE 435. Lecture 26. Data Converters. Architectures. Characterization
EE 435 Lecture 26 Data Coverters Architectures Characterizatio . Review from last lecture. Data Coverters Types: A/D (Aalog to Digital) Coverts Aalog Iput to a Digital Output D/A (Digital to Aalog) Coverts
More informationOperating System Concepts. Operating System Concepts
Chapter 4: Mass-Storage Systems Logical Disk Structure Logical Disk Structure Disk Schedulig Disk Maagemet RAID Structure Disk drives are addressed as large -dimesioal arrays of logical blocks, where the
More informationAppendix D. Controller Implementation
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Appedix D Cotroller Implemetatio Cotroller Implemetatios Combiatioal logic (sigle-cycle); Fiite state machie (multi-cycle, pipelied);
More informationA SYSTEMATIC APPROACH FOR COST OPTIMAL TOLERANCE DESIGN
INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED 07 8-31 AUGUST 007, CITE DES SCIENCES ET DE L'INDUSTRIE, PARIS, FRANCE A SYSTEMATIC APPROACH FOR COST OPTIMAL TOLERANCE DESIGN Sotiria Ch. Dimitrellou,
More informationEvaluation scheme for Tracking in AMI
A M I C o m m u i c a t i o A U G M E N T E D M U L T I - P A R T Y I N T E R A C T I O N http://www.amiproject.org/ Evaluatio scheme for Trackig i AMI S. Schreiber a D. Gatica-Perez b AMI WP4 Trackig:
More informationDescriptive Statistics Summary Lists
Chapter 209 Descriptive Statistics Summary Lists Itroductio This procedure is used to summarize cotiuous data. Large volumes of such data may be easily summarized i statistical lists of meas, couts, stadard
More informationCustomer Portal Quick Reference User Guide
Customer Portal Quick Referece User Guide Overview This user guide is iteded for FM Approvals customers usig the Approval Iformatio Maagemet (AIM) customer portal to track their active projects. AIM is
More informationMobile terminal 3D image reconstruction program development based on Android Lin Qinhua
Iteratioal Coferece o Automatio, Mechaical Cotrol ad Computatioal Egieerig (AMCCE 05) Mobile termial 3D image recostructio program developmet based o Adroid Li Qihua Sichua Iformatio Techology College
More informationSURVEYING INSTRUMENTS SDR33 SOKKIA ELECTR ONIC FIELD BOOKS NOW EVEN MORE RUGGED PERFORMANCE. from The World Leader in Data Collection
SURVEYING INSTRUMENTS TM SOKKIA SDR33 ELECTR ONIC FIELD BOOKS ELECTRONIC NOW EVEN MORE RUGGED PERFORMANCE from The World Leader i Data Collectio PUT RUGGED, DEPENDABLE POWER IN THE PALM OF YOUR HAND You
More informationData Warehousing. Paper
Data Warehousig Paper 28-25 Implemetig a fiacial balace scorecard o top of SAP R/3, usig CFO Visio as iterface. Ida Carapelle & Sophie De Baets, SOLID Parters, Brussels, Belgium (EUROPE) ABSTRACT Fiacial
More informationICS Regent. Communications Modules. Module Operation. RS-232, RS-422 and RS-485 (T3150A) PD-6002
ICS Reget Commuicatios Modules RS-232, RS-422 ad RS-485 (T3150A) Issue 1, March, 06 Commuicatios modules provide a serial commuicatios iterface betwee the cotroller ad exteral equipmet. Commuicatios modules
More informationPython Programming: An Introduction to Computer Science
Pytho Programmig: A Itroductio to Computer Sciece Chapter 6 Defiig Fuctios Pytho Programmig, 2/e 1 Objectives To uderstad why programmers divide programs up ito sets of cooperatig fuctios. To be able to
More informationComputer Architecture
Computer Architecture Overview Prof. Tie-Fu Che Dept. of Computer Sciece Natioal Chug Cheg Uiv Sprig 2002 Overview- Computer Architecture Course Focus Uderstadig the desig techiques, machie structures,
More informationCopyright 2016 Ramez Elmasri and Shamkant B. Navathe
Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe CHAPTER 18 Strategies for Query Processig Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe Itroductio DBMS techiques to process a query Scaer idetifies
More informationStructuring Redundancy for Fault Tolerance. CSE 598D: Fault Tolerant Software
Structurig Redudacy for Fault Tolerace CSE 598D: Fault Tolerat Software What do we wat to achieve? Versios Damage Assessmet Versio 1 Error Detectio Iputs Versio 2 Voter Outputs State Restoratio Cotiued
More informationImage Segmentation EEE 508
Image Segmetatio Objective: to determie (etract) object boudaries. It is a process of partitioig a image ito distict regios by groupig together eighborig piels based o some predefied similarity criterio.
More informationCOSC 1P03. Ch 7 Recursion. Introduction to Data Structures 8.1
COSC 1P03 Ch 7 Recursio Itroductio to Data Structures 8.1 COSC 1P03 Recursio Recursio I Mathematics factorial Fiboacci umbers defie ifiite set with fiite defiitio I Computer Sciece sytax rules fiite defiitio,
More informationInnovative. Pharma-Tech Process Services is a high-energy, schedule-driven, technical service provider. Our innovative consulting services cover
Iovative S o l u t i o s Pharma-Tech Process Services is a high-eergy, schedule-drive, techical service provider. Our iovative cosultig services cover Commissioig, Validatio ad Costructio Period Services
More information2016 LEARNING SYSTEM FOR CSCP CERTIFICATION EXAM PREPARATION. learncscp.com
2016 LEARNING SYSTEM FOR CSCP CERTIFICATION EXAM PREPARATION APICS CSCP Learig System users cosistetly surpass the average CSCP exam pass rate. learcscp.com 2016_APICS_A4_Brochure_parter.idd 1 WHY SEEK
More informationLecture 1: Introduction
Lecture 1: Itroductio g Class orgaizatio Istructor cotact Course objectives ad outcomes Lectures outlie Laboratory outlie Gradig system Tetative schedule g Lab schedule g Itelliget sesor systems (ISS)
More informationSession Initiated Protocol (SIP) and Message-based Load Balancing (MBLB)
F5 White Paper Sessio Iitiated Protocol (SIP) ad Message-based Load Balacig (MBLB) The ability to provide ew ad creative methods of commuicatios has esured a SIP presece i almost every orgaizatio. The
More informationAn Algorithm to Solve Multi-Objective Assignment. Problem Using Interactive Fuzzy. Goal Programming Approach
It. J. Cotemp. Math. Scieces, Vol. 6, 0, o. 34, 65-66 A Algorm to Solve Multi-Objective Assigmet Problem Usig Iteractive Fuzzy Goal Programmig Approach P. K. De ad Bharti Yadav Departmet of Mathematics
More informationNormal Distributions
Normal Distributios Stacey Hacock Look at these three differet data sets Each histogram is overlaid with a curve : A B C A) Weights (g) of ewly bor lab rat pups B) Mea aual temperatures ( F ) i A Arbor,
More informationLearning to Shoot a Goal Lecture 8: Learning Models and Skills
Learig to Shoot a Goal Lecture 8: Learig Models ad Skills How do we acquire skill at shootig goals? CS 344R/393R: Robotics Bejami Kuipers Learig to Shoot a Goal The robot eeds to shoot the ball i the goal.
More informationPerformance Plus Software Parameter Definitions
Performace Plus+ Software Parameter Defiitios/ Performace Plus Software Parameter Defiitios Chapma Techical Note-TG-5 paramete.doc ev-0-03 Performace Plus+ Software Parameter Defiitios/2 Backgroud ad Defiitios
More informationRecursion. Recursion. Mathematical induction: example. Recursion. The sum of the first n odd numbers is n 2 : Informal proof: Principle:
Recursio Recursio Jordi Cortadella Departmet of Computer Sciece Priciple: Reduce a complex problem ito a simpler istace of the same problem Recursio Itroductio to Programmig Dept. CS, UPC 2 Mathematical
More informationUNIT 4 Section 8 Estimating Population Parameters using Confidence Intervals
UNIT 4 Sectio 8 Estimatig Populatio Parameters usig Cofidece Itervals To make ifereces about a populatio that caot be surveyed etirely, sample statistics ca be take from a SRS of the populatio ad used
More informationEFFECT OF QUERY FORMATION ON WEB SEARCH ENGINE RESULTS
Iteratioal Joural o Natural Laguage Computig (IJNLC) Vol. 2, No., February 203 EFFECT OF QUERY FORMATION ON WEB SEARCH ENGINE RESULTS Raj Kishor Bisht ad Ila Pat Bisht 2 Departmet of Computer Sciece &
More informationECE4050 Data Structures and Algorithms. Lecture 6: Searching
ECE4050 Data Structures ad Algorithms Lecture 6: Searchig 1 Search Give: Distict keys k 1, k 2,, k ad collectio L of records of the form (k 1, I 1 ), (k 2, I 2 ),, (k, I ) where I j is the iformatio associated
More informationSD vs. SD + One of the most important uses of sample statistics is to estimate the corresponding population parameters.
SD vs. SD + Oe of the most importat uses of sample statistics is to estimate the correspodig populatio parameters. The mea of a represetative sample is a good estimate of the mea of the populatio that
More informationWhat are Information Systems?
Iformatio Systems Cocepts What are Iformatio Systems? Roma Kotchakov Birkbeck, Uiversity of Lodo Based o Chapter 1 of Beett, McRobb ad Farmer: Object Orieted Systems Aalysis ad Desig Usig UML, (4th Editio),
More informationTruVu 360 User Community. SpectroCare. Enterprise Fluid Intelligence for Predictive Maintenance. TruVu 360 Product Information
TruVu 360 User Commuity Cotiuous educatio is importat for a successful o-site lubricat program. With ever growig articles, videos, ad structured learig modules, TruVu 360 user commuity is a digital commuity
More informationChapter 1. Introduction to Computers and C++ Programming. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 1 Itroductio to Computers ad C++ Programmig Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 1.1 Computer Systems 1.2 Programmig ad Problem Solvig 1.3 Itroductio to C++ 1.4 Testig
More informationA MODIFIED APPROACH FOR ESTIMATING PROCESS CAPABILITY INDICES USING IMPROVED ESTIMATORS
Pak. J. Statist. 017 Vol. 33(), 411-418 A MODIFIED APPROACH FOR ESTIMATING PROCESS CAPABILITY INDICES USING IMPROVED ESTIMATORS Seem Şaha Vahaplar 1 ad Özlem Ege Oruç Departmet of Statistics, Dokuz Eylül
More informationΤεχνολογία Λογισμικού
ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών Τεχνολογία Λογισμικού, 7ο/9ο εξάμηνο 2018-2019 Τεχνολογία Λογισμικού Ν.Παπασπύρου, Αν.Καθ. ΣΗΜΜΥ, ickie@softlab.tua,gr
More informationBAAN IVc/BaanERP. Conversion Guide Oracle7 to Oracle8
BAAN IVc/BaaERP A publicatio of: Baa Developmet B.V. P.O.Box 143 3770 AC Bareveld The Netherlads Prited i the Netherlads Baa Developmet B.V. 1999. All rights reserved. The iformatio i this documet is subject
More informationBaan Finance Financial Statements
Baa Fiace Fiacial Statemets Module Procedure UP041A US Documetiformatio Documet Documet code : UP041A US Documet group : User Documetatio Documet title : Fiacial Statemets Applicatio/Package : Baa Fiace
More informationCMSC Computer Architecture Lecture 12: Virtual Memory. Prof. Yanjing Li University of Chicago
CMSC 22200 Computer Architecture Lecture 12: Virtual Memory Prof. Yajig Li Uiversity of Chicago A System with Physical Memory Oly Examples: most Cray machies early PCs Memory early all embedded systems
More informationIdentification of the Swiss Z24 Highway Bridge by Frequency Domain Decomposition Brincker, Rune; Andersen, P.
Aalborg Uiversitet Idetificatio of the Swiss Z24 Highway Bridge by Frequecy Domai Decompositio Bricker, Rue; Aderse, P. Published i: Proceedigs of IMAC 2 Publicatio date: 22 Documet Versio Publisher's
More informationOutline n Introduction n Background o Distributed DBMS Architecture
Outlie Itroductio Backgroud o Distributed DBMS Architecture Datalogical Architecture Implemetatio Alteratives Compoet Architecture o Distributed DBMS Architecture o Distributed Desig o Sematic Data Cotrol
More informationAdministrative UNSUPERVISED LEARNING. Unsupervised learning. Supervised learning 11/25/13. Final project. No office hours today
Admiistrative Fial project No office hours today UNSUPERVISED LEARNING David Kauchak CS 451 Fall 2013 Supervised learig Usupervised learig label label 1 label 3 model/ predictor label 4 label 5 Supervised
More informationAPPLICATION NOTE PACE1750AE BUILT-IN FUNCTIONS
APPLICATION NOTE PACE175AE BUILT-IN UNCTIONS About This Note This applicatio brief is iteded to explai ad demostrate the use of the special fuctios that are built ito the PACE175AE processor. These powerful
More information. Written in factored form it is easy to see that the roots are 2, 2, i,
CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or
More informationChapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 9 Poiters ad Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 9.1 Poiters 9.2 Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Slide 9-3
More informationCA Top Secret r14 for z/os
PRODUCT SHEET: CA TOP SECRET FOR z/os CA Top Secret r14 for z/os CA Top Secret for z/os (CA Top Secret) provides iovative ad comprehesive security for your busiess trasactio eviromets icludig z/os, Maiframe
More informationContinuity Logic Frontline Live
September 2015 Cotiuity Logic Frotlie Live Iovatig User Experiece for Busiess Cotiuity SOLUTIONPERSPECTIVE Goverace, Risk Maagemet & Compliace Isight Cotiuity Logic Frotlie Live Iovatio i User Experiece
More informationCORD Test Project in Okinawa Open Laboratory
CORD Test Project i Okiawa Ope Laboratory Fukumasa Morifuji NTT Commuicatios Trasform your busiess, trasced expectatios with our techologically advaced solutios. Ageda VxF platform i NTT Commuicatios Expectatio
More informationEmpirical Validate C&K Suite for Predict Fault-Proneness of Object-Oriented Classes Developed Using Fuzzy Logic.
Empirical Validate C&K Suite for Predict Fault-Proeess of Object-Orieted Classes Developed Usig Fuzzy Logic. Mohammad Amro 1, Moataz Ahmed 1, Kaaa Faisal 2 1 Iformatio ad Computer Sciece Departmet, Kig
More informationCopyright 2016 Ramez Elmasri and Shamkant B. Navathe
Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe CHAPTER 22 Database Recovery Techiques Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe Itroductio Recovery algorithms Recovery cocepts Write-ahead
More informationCSC165H1 Worksheet: Tutorial 8 Algorithm analysis (SOLUTIONS)
CSC165H1, Witer 018 Learig Objectives By the ed of this worksheet, you will: Aalyse the ruig time of fuctios cotaiig ested loops. 1. Nested loop variatios. Each of the followig fuctios takes as iput a
More informationThe identification of key quality characteristics based on FAHP
Iteratioal Joural of Research i Egieerig ad Sciece (IJRES ISSN (Olie: 2320-9364, ISSN (Prit: 2320-9356 Volume 3 Issue 6 ǁ Jue 2015 ǁ PP.01-07 The idetificatio of ey quality characteristics based o FAHP
More information6.854J / J Advanced Algorithms Fall 2008
MIT OpeCourseWare http://ocw.mit.edu 6.854J / 18.415J Advaced Algorithms Fall 2008 For iformatio about citig these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 18.415/6.854 Advaced Algorithms
More informationNumerical Methods Lecture 6 - Curve Fitting Techniques
Numerical Methods Lecture 6 - Curve Fittig Techiques Topics motivatio iterpolatio liear regressio higher order polyomial form expoetial form Curve fittig - motivatio For root fidig, we used a give fuctio
More informationLaser marking systems. Technology, Innovation and Environment
Laser markig systems Techology, Iovatio ad Eviromet 3 chiques atur CI-Laser Nature Iovatio Compay Mark your territory... Compay Profile page 3 Materials page 12 Fields of Applicatio page 14 OEM-Laser Markers
More informationDETECTION OF LANDSLIDE BLOCK BOUNDARIES BY MEANS OF AN AFFINE COORDINATE TRANSFORMATION
Proceedigs, 11 th FIG Symposium o Deformatio Measuremets, Satorii, Greece, 2003. DETECTION OF LANDSLIDE BLOCK BOUNDARIES BY MEANS OF AN AFFINE COORDINATE TRANSFORMATION Michaela Haberler, Heribert Kahme
More informationPowerView. Model AP9215. User s Manual
PowerView Model AP9215 User s Maual Thak You! Thak you for selectig the America Power Coversio PowerView. It has bee desiged for may years of reliable, maiteace-free service i combiatio with your America
More informationModel Based Design: develpment of Electronic Systems
Model Based Desig: develpmet of Electroic Systems Stuttgart 16 Jue 2004 Ageda Model Based Desig: purposes ad process Model Based Desig: vehicle developmet process Tools Fuctioal Requiremets: Structure
More informationBig-O Analysis. Asymptotics
Big-O Aalysis 1 Defiitio: Suppose that f() ad g() are oegative fuctios of. The we say that f() is O(g()) provided that there are costats C > 0 ad N > 0 such that for all > N, f() Cg(). Big-O expresses
More informationDiego Nehab. n A Transformation For Extracting New Descriptors of Shape. n Locus of points equidistant from contour
Diego Nehab A Trasformatio For Extractig New Descriptors of Shape Locus of poits equidistat from cotour Medial Axis Symmetric Axis Skeleto Shock Graph Shaked 96 1 Shape matchig Aimatio Dimesio reductio
More informationThe power of multi-objective calibration: Two case studies with SWAT
The power of multi-objective calibratio: Two case studies with SWAT Sader Huisma Thorste Pohlert, Lutz Breuer & Has-Georg Frede Justus-Liebig-Uiversität Gieße, Germay Istitut für Ladschaftsökologie ud
More informationNON-LINEAR MODELLING OF A GEOTHERMAL STEAM PIPE
14thNew Zealad Workshop 1992 NON-LNEAR MODELLNG OF A GEOTHERMAL STEAM PPE Y. Huag ad D. H. Freesto Geothermal stitute, Uiversity of Aucklad SUMMARY Recet work o developig a o-liear model for a geothermal
More informationFloristic Quality Assessment (FQA) Calculator for Colorado User s Guide
Floristic Quality Assessmet (FQA) Calculator for Colorado User s Guide Created by the Colorado atural Heritage Program Last Updated April 2012 The FQA Calculator was created by Michelle Fik ad Joaa Lemly
More informationIsn t It Time You Got Faster, Quicker?
Is t It Time You Got Faster, Quicker? AltiVec Techology At-a-Glace OVERVIEW Motorola s advaced AltiVec techology is desiged to eable host processors compatible with the PowerPC istructio-set architecture
More informationAir Force Data Reference Architecture and Platform
Headquarters U.S. Air Force Air Force Data Referece Architecture ad Platform Ms. Jackie Murray 11 Oct 2018 1 AF Data Challeges Large umber of legacy systems with umerous poit-to-poit iterfaces that are
More informationvbonline Pro Condition Monitoring System
vbolie Pro Coditio Moitorig System Product Datasheet Betly Nevada* Asset Coditio Moitorig Descriptio The vbolie Pro Coditio Moitorig System uses sophisticated sigal processig algorithms together with machiery
More informationDefinition and Application of a Process Flexibility Index
David Kazmer David Hatch Liag Zhu Christoph Roser Deepak Kapoor Departmet of Mech. & Id. Egieerig, Uiversity of Massachusetts Amherst, Amherst, MA 01003 Defiitio ad Applicatio of a Process Flexibility
More informationLecture Notes 6 Introduction to algorithm analysis CSS 501 Data Structures and Object-Oriented Programming
Lecture Notes 6 Itroductio to algorithm aalysis CSS 501 Data Structures ad Object-Orieted Programmig Readig for this lecture: Carrao, Chapter 10 To be covered i this lecture: Itroductio to algorithm aalysis
More informationΤεχνολογία Λογισμικού
ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών Τεχνολογία Λογισμικού, 7ο/9ο εξάμηνο 2018-2019 Τεχνολογία Λογισμικού Ν.Παπασπύρου, Αν.Καθ. ΣΗΜΜΥ, ickie@softlab.tua,gr
More informationvbonline Pro Condition Monitoring System Product Datasheet Bently Nevada* Asset Condition Monitoring
GE Measuremet & Cotrol vbolie Pro Coditio Moitorig System Product Datasheet Betly Nevada* Asset Coditio Moitorig Descriptio The vbolie Pro Coditio Moitorig System uses sophisticated sigal processig algorithms
More informationGoals of the Lecture Object Constraint Language
Goals of the Lecture Object Costrait Laguage Object-Orieted Aalysis ad Desig - Fall 1998 Preset the Object Costrait Laguage Ð As best as possible, with the limited iformatio available from UML i a Nutshell
More information% Sun Logo for. X3T10/95-229, Revision 0. April 18, 1998
Su Microsystems, Ic. 2550 Garcia Aveue Moutai View, CA 94045 415 960-1300 X3T10/95-229, Revisio 0 April 18, 1998 % Su Logo for Joh Lohmeyer Chairperso, X3T10 Symbios Logic Ic. 1635 Aeroplaza Drive Colorado
More informationOverview Chapter 12 A display model
Overview Chapter 12 A display model Why graphics? A graphics model Examples Bjare Stroustrup www.stroustrup.com/programmig 3 Why bother with graphics ad GUI? Why bother with graphics ad GUI? It s very
More informationMANAGED! PREPARE TO BE FEATURES HANDHELD USER DISPLAYS. Specifications MEASUREMENT STABILIZATION INDICATOR
FEATURES Trasfers data easily betwee Hadheld & PC via USB cable. Stores up to 3000 temperatures ad 300 meu items. Sets Max / Mi temperature limit idicators. Stores custom meus for easy recall. Exports
More informationTELETERM M2 Series Programmable RTU s
Model C6xC ad C6xC Teleterm MR Radio RTU s DATASHEET Cofigurable Iputs ad Outputs 868MHz or 900MHz radio port 0/00 Etheret port o C6Cx ISaGRAF 6 Programmable microsd Card Loggig Low power operatio Two
More informationDimension Reduction and Manifold Learning. Xin Zhang
Dimesio Reductio ad Maifold Learig Xi Zhag eeizhag@scut.edu.c Cotet Motivatio of maifold learig Pricipal compoet aalysis ad its etesio Maifold learig Global oliear maifold learig (IsoMap) Local oliear
More informationBaan Tools User Management
Baa Tools User Maagemet Module Procedure UP008A US Documetiformatio Documet Documet code : UP008A US Documet group : User Documetatio Documet title : User Maagemet Applicatio/Package : Baa Tools Editio
More informationAnalysis of Documents Clustering Using Sampled Agglomerative Technique
Aalysis of Documets Clusterig Usig Sampled Agglomerative Techique Omar H. Karam, Ahmed M. Hamad, ad Sheri M. Moussa Abstract I this paper a clusterig algorithm for documets is proposed that adapts a samplig-based
More informationOne advantage that SONAR has over any other music-sequencing product I ve worked
*gajedra* D:/Thomso_Learig_Projects/Garrigus_163132/z_productio/z_3B2_3D_files/Garrigus_163132_ch17.3d, 14/11/08/16:26:39, 16:26, page: 647 17 CAL 101 Oe advatage that SONAR has over ay other music-sequecig
More informationMindmapping: A General Purpose (Test) Planning Tool
W8 Test Strategy, Plaig, Metrics Wedesday, May 2d, 2018 1:45 PM Midmappig: A Geeral Purpose (Test) Plaig Tool Preseted by: Bob Gale Zeergy Techologies Brought to you by: 350 Corporate Way, Suite 400, Orage
More information