000 | 05897nam a22004813i 4500 | ||
---|---|---|---|
001 | EBC28983715 | ||
003 | MiAaPQ | ||
005 | 20240703143952.0 | ||
007 | cr cnu|||||||| | ||
008 | 240628s2020 xx o ||||0 eng d | ||
020 |
_a9780768099294 _q(electronic bk.) |
||
020 | _z9780768094275 | ||
035 | _a(MiAaPQ)EBC28983715 | ||
035 | _a(Au-PeEL)EBL28983715 | ||
035 | _a(OCoLC)1302012831 | ||
040 |
_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ |
||
050 | 4 | _aTL553 .D49 2020 | |
082 | 0 | _a629.13 | |
100 | 1 | _aDibsdale, Charles Edwin. | |
245 | 1 | 0 | _aAerospace Predictive Maintenance. |
250 | _a1st ed. | ||
264 | 1 |
_aWarrendale : _bSAE International, _c2020. |
|
264 | 4 | _c�2020. | |
300 | _a1 online resource (140 pages) | ||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
505 | 0 | _aCover -- CHAPTER 1 An Engineer's Journey -- Who Is This Book Intended For? -- How This Book Is Organized -- Reference -- CHAPTER 2 A History of Maintenance and How Maintenance Is Done Today -- Most Functional Failures in Complex Machinery Are Random -- What Is the Difference between Failure Modes and Failure Mechanisms? -- Intrinsic and Achieved Reliability -- Applied Systems Thinking -- MSG-3 Overview -- Key Take-Away Points -- References -- CHAPTER 3 What Is Predictive Maintenance (PdM) and How Does It Fit into a Maintenance Regime? -- What Are Functions? -- What Are Operating Performance Levels? -- The Major Influences of Failure -- What Is an Operating Context? -- What Is an Operating Environment? -- Who Are Asset Stakeholders? -- A Taxonomy of Maintenance Tasks -- The Taxonomy of Maintenance -- Preventative Maintenance -- Deeper Explanation of PdM -- Levels of Diagnostic Capability -- Diagnostics -- Diagnostic Effectiveness -- Prognostics -- Type 1 Models -- Type 2 Models -- Type 3 Models -- Type 4 Models -- Fallacies and Hype Surrounding PdM -- The 'Real Time' Label of Superior PdM Misunderstanding -- A Data-driven Approach Negates the Need for Engineering Domain Knowledge -- What Is the Difference between Condition Monitoring and Condition-Based Maintenance? -- Immature Systems Are Sold as PdM Systems -- Wasteful Number of Inspections -- How Does PdM Impact Maintenance Planning and Scheduling? -- What Is a Maintenance Schedule? -- What Is a Maintenance Plan? -- Digital Twin -- Key Take-Away Points -- References -- CHAPTER 4 How Does PdM Fit with Integrated Vehicle Health Management (IVHM)? -- What Are Maintenance Credits? -- Key Take-Away Points -- References -- CHAPTER 5 Why Is PdM Generally Better than Traditional Maintenance? (How to Build a Business Case) -- Why Choose On-Condition over Scheduled Discard/Replacement or Restoration?. | |
505 | 8 | _aExceptions to the Rule - When Is Scheduled Replacement Better? -- When Should Median and Mean Measures Be Used? -- Why Is the Use of MTBF Persisted? -- Building the Business Case -- Business Cases Built on Reliability-Availability-Maintainability (RAM) Simulation -- Key Take-Away Points -- References -- CHAPTER 6 How Does PdM Relate to Reliability-Centered Maintenance (RCM)? -- How Can Severity of Failure Be Categorized? -- How Can the Likelihood of Failure Be Categorized? -- The Applicability of Weibull Analysis -- FMEA Storage and Tools for Analysis -- Key Take-Away Points -- References -- CHAPTER 7 What Are the Key Features in a PdM Maturity Model? -- Data , Information and Knowledge -- Data Quality -- The Breakdown of PdM into Functional Blocks -- Sense -- Data Sampling Rates -- Acquire -- Transfer -- Analyze -- Learn -- People and Competencies -- Maturity Model -- Key Take-Away Points -- References -- CHAPTER 8 Specifying Predictive Maintenance -- Assumptions -- Basic Requirements -- Key Take-Away Points -- Reference -- CHAPTER 9 What Are the Disadvantages of PdM and How Should They Be Addressed? -- Daniel Kahneman: Thinking Fast, Thinking Slow -- Nassim Nicholas Taleb: Fooled by Randomness -- The Resnikoff Conundrum -- Key Take-Away Points -- References -- CHAPTER 10 How PdM Will Likely Transform with the Emergence of New Technology -- Big Data and Cloud Services -- The Emergence of the Industrial Internet of Things (IIoT) -- Industry 4.0 -- Nanotechnology -- Configuration Management -- The Advent of the Citizen Data-Scientist -- The Apache Software -- Python -- Other Open-Source Capabilities -- Key Take-Away Points -- References -- CHAPTER 11 A Summary, Future States, and Things to Look For -- How Do You Start Implementing PdM? -- PdM Analogies -- Key Take-Away Points -- CHAPTER 12 An Example PdM Case Study Using Open-Source Development Tools. | |
505 | 8 | _aPlots -- Summary Notes -- Code Notes -- Reference -- Glossary -- Author Bio. | |
520 | _aConsiders Predictive Maintenance (PdM) a subset of Condition Based Maintenance (CBM), and must obey the same underlying rules and pre-requisites that apply to it. Yet, PdM is new because it takes advantage of emerging digital technology in sensing, acquiring data, communicating the data, and processing it. | ||
588 | _aDescription based on publisher supplied metadata and other sources. | ||
590 | _aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. | ||
650 | 0 | _aAeronautics--Safety measures. | |
650 | 0 | _aAvionics--Maintenance and repair. | |
650 | 0 | _aAirplanes--Maintenance and repair. | |
655 | 4 | _aElectronic books. | |
776 | 0 | 8 |
_iPrint version: _aDibsdale, Charles Edwin _tAerospace Predictive Maintenance _dWarrendale : SAE International,c2020 _z9780768094275 |
797 | 2 | _aProQuest (Firm) | |
856 | 4 | 0 |
_uhttps://ebookcentral.proquest.com/lib/kliuc-ebooks/detail.action?docID=28983715 _zClick to View |
942 |
_2lcc _cEBK |
||
999 |
_c337200 _d337200 |