Design for Maintainability

ISBN-13: 9781119578512 / Angielski / Twarda / 2021 / 400 str.

Louis J. Gullo; Jack Dixon

Spis treści

Series Editor's Foreword by Dr Andre Kleyner xixPreface xxiAcknowledgments xxiiiIntroduction: What You Will Learn xxv1 Design for Maintainability Paradigms 1Louis J. Gullo and Jack Dixon1.1 Why Design for Maintainability? 11.1.1 What is a System? 11.1.2 What is Maintainability? 11.1.3 What is Testability? 21.2 Maintainability Factors for Design Consideration 21.2.1 Part Standardization 31.2.2 Structure Modularization 31.2.3 Kit Packaging 31.2.4 Part Interchangeability 31.2.5 Human Accessibility 41.2.6 Fault Detection 41.2.7 Fault Isolation 41.2.8 Part Identification 51.3 Reflections on the Current State of the Art 51.4 Paradigms for Design for Maintainability 61.4.1 Maintainability is Inversely Proportional to Reliability 71.4.2 Maintainability is Directly Proportional to Testability and Prognostics and Health Monitoring 71.4.3 Strive for Ambiguity Groups No Greater Than 3 71.4.4 Migrate from Scheduled Maintenance to Condition-based Maintenance 81.4.5 Consider the Human as the Maintainer 81.4.6 Modularity Speeds Repairs 81.4.7 Maintainability Predicts Downtime During Repairs 81.4.8 Understand the Maintenance Requirements 91.4.9 Support Maintainability with Data 91.5 Summary 10References 112 History of Maintainability 13Louis J. Gullo2.1 Introduction 132.2 Ancient History 132.3 The Difference Between Maintainability and Maintenance Engineering 142.4 Early Maintainability References 152.4.1 The First Maintainability Standards 152.4.2 Introduction to MIL-STD-470 162.5 Original Maintainability Program Roadmap 172.5.1 Task 1: The Maintainability Program Plan 172.5.2 Task 2: Maintainability Analysis 172.5.3 Task 3: Maintenance Inputs 182.5.4 Task 4: Maintainability Design Criteria 182.5.5 Task 5: Maintainability Trade Studies 192.5.6 Task 6: Maintainability Predictions 192.5.7 Task 7: Vendor Controls 192.5.8 Task 8: Integration 192.5.9 Task 9: Maintainability Design Reviews 202.5.10 Task 10: Maintainability Data System 212.5.11 Task 11: Maintainability Demonstration 212.5.12 Task 12: Maintainability Status Reports 212.6 Maintainability Evolution Over the Time Period 1966 to 1978 212.7 Improvements During the Period 1978 to 1997 222.8 Introduction of Testability 232.9 Introduction of Artificial Intelligence 242.10 Introduction to MIL-HDBK-470A 242.11 Summary 26References 263 Maintainability Program Planning and Management 29David E. Franck, CPL and Anne Meixner, PhD3.1 Introduction 293.2 System/Product Life Cycle 293.3 Opportunities to Influence Design 333.3.1 Engineering Design 333.3.2 Design Activities 333.3.3 Design Reviews 363.4 Maintainability Program Planning 373.4.1 Typical Maintainability Engineering Tasks 383.4.2 Typical Maintainability Program Plan Outline 383.5 Interfaces with Other Functions 423.6 Managing Vendor/Subcontractor Maintainability Efforts 443.7 Change Management 453.8 Cost-effectiveness 473.9 Maintenance and Life Cycle Cost (LCC) 503.10 Warranties 523.11 Summary 53References 54Suggestions for Additional Reading 544 Maintenance Concept 55David E. Franck, CPL4.1 Introduction 554.2 Developing the Maintenance Concept 574.2.1 Maintainability Requirements 604.2.2 Categories of Maintenance 614.2.2.1 Scheduled Maintenance 614.2.2.2 Unscheduled Maintenance 634.3 Levels of Maintenance 694.4 Logistic Support 704.4.1 Design Interface 714.4.2 Design Considerations for Improved Logistics Support 714.4.2.1 Tools 714.4.2.2 Skills 724.4.2.3 Test/Support Equipment - Common and Special 724.4.2.4 Training 724.4.2.5 Facilities 734.4.2.6 Reliability 734.4.2.7 Spares Provisioning 754.4.2.8 Backshop Support 754.5 Summary 76References 77Suggestions for Additional Reading 775 Maintainability Requirements and Design Criteria 79Louis J. Gullo and Jack Dixon5.1 Introduction 795.2 Maintainability Requirements 795.2.1 Different Maintainability Requirements for Different Markets 815.3 The Systems Engineering Approach 815.3.1 Requirements Analysis 825.3.1.1 Types of Requirements 825.3.1.2 Good Requirements 835.3.2 System Design Evaluation 845.3.3 Maintainability in the Systems Engineering Process 845.4 Developing Maintainability Requirements 845.4.1 Defining Quantitative Maintainability Requirements 855.4.2 Quantitative Preventive Maintainability Requirements 875.4.3 Quantitative Corrective Maintainability Requirements 885.4.4 Defining Qualitative Maintainability Requirements 905.5 Maintainability Design Goals 905.6 Maintainability Guidelines 915.7 Maintainability Design Criteria 915.8 Maintainability Design Checklists 935.9 Design Criteria that Provide or Improve Maintainability 945.10 Conclusions 95References 95Suggestions for Additional Reading 96Additional Sources of Checklists 966 Maintainability Analysis and Modeling 97James Kovacevic6.1 Introduction 976.2 Functional Analysis 986.2.1 Constructing a Functional Block Diagram 996.2.2 Using a Functional Block Diagram 1006.3 Maintainability Analysis 1006.3.1 Objectives of Maintainability Analyses 1016.3.2 Typical Products of Maintainability Analyses 1016.4 Commonly Used Maintainability Analyses 1016.4.1 Equipment Downtime Analysis 1026.4.2 Maintainability Design Evaluation 1026.4.3 Testability Analysis 1026.4.4 Human Factors Analysis 1026.4.5 Maintainability Allocations 1036.4.5.1 Failure Rate Complexity Method 1046.4.5.2 Variation of the Failure Rate Complexity Method 1046.4.5.3 Statistically-based Allocation Method 1046.4.5.4 Equal Distribution Method 1066.4.6 Maintainability Design Trade Study 1066.4.7 Maintainability Models and Modeling 1086.4.7.1 Poisson Distribution in Maintainability Models 1086.4.8 Failure Modes, Effects, and Criticality Analysis - Maintenance Actions (FMECA-MA) 1106.4.9 Maintenance Activities Block Diagrams 1106.4.10 Maintainability Prediction 1126.4.11 Maintenance Task Analysis (MTA) 1126.4.12 Level of Repair Analysis (LORA) 1136.4.12.1 Performing a Level of Repair Analysis 1146.4.12.2 Managing LORA Data 1166.4.12.3 Level of Repair Analysis Outcomes 1176.5 Summary 117References 117Suggestion for Additional Reading 1187 Maintainability Predictions and Task Analysis 119Louis J. Gullo and James Kovacevic7.1 Introduction 1197.2 Maintainability Prediction Standard 1197.3 Maintainability Prediction Techniques 1207.3.1 Maintainability Prediction Procedure I 1217.3.1.1 Preparation Activities 1217.3.1.2 Failure Verification Activities 1217.3.1.3 Failure Location Activities 1227.3.1.4 Part Procurement Activities 1227.3.1.5 Repair Activities 1227.3.1.6 Final Test Activities 1237.3.1.7 Probability Distributions 1237.3.2 Maintainability Prediction Procedure II 1237.3.2.1 Use of Maintainability Predictions for Corrective Maintenance 1237.3.2.2 Use of Maintainability Predictions for Preventive Maintenance 1247.3.2.3 Use of Maintainability Predictions for Active Maintenance 1247.3.3 Maintainability Prediction Procedure III 1247.3.4 Maintainability Prediction Procedure IV 1257.3.5 Maintainability Prediction Procedure V 1277.4 Maintainability Prediction Results 1277.5 Bayesian Methodologies 1297.5.1 Definition of Bayesian Terms 1307.5.2 Bayesian Example 1307.6 Maintenance Task Analysis 1307.6.1 Maintenance Task Analysis Process andWorksheets 1327.6.2 Completing a Maintenance Task Analysis Sheet 1347.6.3 Personnel and Skill Data Entry 1347.6.4 Spare Parts, Supply Chain, and Inventory Management Data Entry 1357.6.5 Test and Support Equipment Data Entry 1377.6.6 Facility Requirements Data Entry 1377.6.7 Maintenance Manuals 1387.6.8 Maintenance Plan 1387.7 Summary 139References 1398 Design for Machine Learning 141Louis J. Gullo8.1 Introduction 1418.2 Artificial Intelligence in Maintenance 1428.3 Model-based Reasoning 1448.3.1 Diagnosis 1458.3.2 Health Monitoring 1458.3.3 Prognostics 1458.4 Machine Learning Process 1458.4.1 Supervised and Unsupervised Learning 1478.4.2 Deep Learning 1488.4.3 Function Approximations 1498.4.4 Pattern Determination 1508.4.5 Machine Learning Classifiers 1508.4.6 Feature Selection and Extraction 1518.5 Anomaly Detection 1528.5.1 Known and Unknown Anomalies 1528.6 Value-added Benefits of ML 1538.7 Digital Prescriptive Maintenance (DPM) 1548.8 Future Opportunities 1548.9 Summary 155References 1559 Condition-based Maintenance and Design for Reduced Staffing 157Louis J. Gullo and James Kovacevic9.1 Introduction 1579.2 What is Condition-based Maintenance? 1589.2.1 Types of Condition-based Maintenance 1589.3 Condition-based Maintenance vs. Time-based Maintenance 1599.3.1 Time-based Maintenance 1599.3.2 Types of Time-based Maintenance 1599.3.3 Calculating Time-based Maintenance Intervals 1609.3.4 The P-F Curve 1609.3.5 Calculating Condition-based Maintenance Intervals 1629.4 Reduced Staffing Through CBM and Efficient TBM 1639.5 Integrated System Health Management 1649.6 Prognostics and CBM+ 1659.6.1 Essential Elements of CBM+ 1709.7 Digital Prescriptive Maintenance 1709.8 Reliability-centered Maintenance 1729.8.1 History of RCM 1729.8.2 What is RCM? 1739.8.3 Why RCM? 1749.8.4 What we Learned from RCM 1749.8.4.1 Failure Curves 1759.8.5 Applying RCM in Your Organization 1779.8.5.1 InnerWorkings of RCM 1779.9 Conclusion 180References 181Suggestion for Additional Reading 18110 Safety and Human Factors Considerations in Maintainable Design 183Jack Dixon10.1 Introduction 18310.2 Safety in Maintainable Design 18310.2.1 Safety and its Relationship to Maintainability 18410.2.2 Safety Design Criteria 18410.2.3 Overview of System Safety Engineering 18710.2.4 Risk Assessment and Risk Management 18710.2.4.1 Probability 18810.2.4.2 Consequences 18810.2.4.3 Risk Evaluation 18910.2.5 System Safety Analysis 19010.2.5.1 Operating and Support Hazard Analysis 19110.2.5.2 Health Hazard Analysis 19310.3 Human Factors in Maintainable Design 19510.3.1 Human Factors Engineering and its Relationship to Maintainability 19510.3.2 Human Systems Integration 19610.3.3 Human Factors Design Criteria 19610.3.4 Human Factors Engineering Analysis 19810.3.5 Maintainability Anthropometric Analysis 19910.4 Conclusion 205References 206Suggestion for Additional Reading 20611 Design for Software Maintainability 207Louis J. Gullo11.1 Introduction 20711.2 What is Software Maintainability? 20811.3 Relevant Standards 20811.4 Impact of Maintainability on Software Design 20911.5 How to Design Software that is Fault-tolerant and Requires Zero Maintenance 21011.6 How to Design Software that is Self-aware of its Need for Maintenance 21211.7 How to Develop Maintainable Software that was Not Designed for Maintainability at the Start 21311.8 Software Field Support and Maintenance 21411.8.1 Software Maintenance Process Implementation 21411.8.2 Software Problem Identification and Software Modification Analysis 21511.8.3 Software Modification Implementation 21511.8.4 Software Maintenance Review and Acceptance 21511.8.5 Software Migration 21511.8.6 Software Retirement 21511.8.7 Software Maintenance Maturity Model 21611.9 Software Changes and Configuration Management 21611.10 Software Testing 21711.11 Summary 218References 21812 Maintainability Testing and Demonstration 221David E. Franck, CPL12.1 Introduction 22112.2 When to Test 22212.3 Forms of Testing 22412.3.1 Process Reviews 22512.3.2 Modeling or Simulation 22512.3.3 Analysis of the Design 22712.3.4 In-process Testing 22712.3.5 Formal Design Reviews 22812.3.6 Maintainability Demonstration (M-Demo) 22812.3.6.1 M-Demo Test Plan 22912.3.6.2 M-Demo Maintenance Task Sample Selection 23012.3.6.3 M-Demo Test Report 23312.3.6.4 AN/UGC-144 M-Demo Example 23412.3.7 Operational Maintainability Testing 23612.4 Data Collection 23612.5 Summary 241References 242Suggestions for Additional Reading 24313 Design for Test and Testability 245Anne Meixner and Louis J. Gullo13.1 Introduction 24513.2 What is Testability? 24513.3 DfT Considerations for Electronic Test at All Levels 24713.3.1 What is Electronic Test? 24713.3.2 Test Coverage and Effectiveness 24813.3.3 Accessibility Design Criteria Related to Testability 24913.4 DfT at System or Product Level 25013.4.1 Power-On Self-Test and On-Line Testing 25113.5 DfT at Electronic Circuit Board Level 25113.6 DfT at Electronic Component Level 25313.6.1 System in Package/Multi-chip Package Test and DfT Techniques 25313.6.2 VLSI and DfT Techniques 25513.6.3 Logic Test and Design For Test 25513.6.4 Memory Test and Design for Test 25613.6.5 Analog and Mixed-Signal Test and DfT 25913.6.6 Design and Test Tradeoffs 26013.7 Leveraging DfT for Maintainability and Sustainment 26113.7.1 Built-In-Test/Built-In Self-Test 26113.8 BITE and External Support Equipment 26213.9 Summary 262References 262Suggestions for Additional Reading 26314 Reliability Analyses 265Jack Dixon14.1 Introduction 26514.2 Reliability Analysis and Modeling 26614.3 Reliability Block Diagrams 26614.4 Reliability Allocation 26814.5 Reliability Mathematical Model 26914.6 Reliability Prediction 26914.7 Fault Tree Analysis 27014.7.1 What is a Fault Tree? 27014.7.2 Gates and Events 27114.7.3 Definitions 27114.7.4 Methodology 27114.7.5 Cut Sets 27314.7.6 Quantitative Analysis of Fault Trees 27614.7.7 Advantages and Disadvantages 27614.8 Failure Modes, Effects, and Criticality Analysis 27614.9 Complementary Reliability Analyses and Models 27914.10 Conclusions 279References 280Suggestions for Additional Reading 28015 Design for Availability 281James Kovacevic15.1 Introduction 28115.2 What is Availability? 28115.3 Concepts of Availability 28315.3.1 Elements of Availability 28515.3.1.1 Time-related Elements 28615.3.1.2 Mean Metrics 28715.4 Types of Availability 28915.4.1 Inherent Availability 28915.4.2 Achieved Availability 29015.4.3 Operational Availability 29115.4.3.1 Ao Method 1 29115.4.3.2 Ao Method 2 29215.4.3.3 Ao Method 3 29215.4.3.4 Ao Method 4 29315.5 Availability Prediction 29415.5.1 Data for Availability Prediction 29515.5.2 Calculating Availability 29615.5.3 Steps to Availability Prediction 29815.5.3.1 Define the Problem 29915.5.3.2 Define the System 29915.5.3.3 Collect the Data 29915.5.3.4 Build the Model 29915.5.3.5 Verify the Model 29915.5.3.6 Design the Simulation 29915.5.3.7 Run the Simulation 30015.5.3.8 Document and Use the Results 30015.6 Conclusion 300References 30116 Design for Supportability 303James Kovacevic16.1 Introduction 30316.2 Elements of Supportability 30416.2.1 Product Support Management 30516.2.2 Design Interface 30616.2.3 Sustaining Engineering 30716.2.4 Supply Support 30816.2.5 Maintenance Planning and Management 30916.2.6 Packaging, Handling, Storage, and Transportation (PHS&T) 31116.2.7 Technical Data 31216.2.8 Support Equipment 31516.2.9 Training and Training Support 31516.2.10 Manpower and Personnel 31616.2.11 Facilities and Infrastructure 31716.2.12 Computer Resources 31816.3 Supportability Program Planning 31916.3.1 Supportability Analysis 31916.4 Supportability Tasks and the ILS Plan 32116.5 Summary 322References 322Suggestion for Additional Reading 32217 Special Topics 323Jack Dixon17.1 Introduction 32317.2 Reducing Active Maintenance Time with Single Minute Exchange of Dies (SMED) 32317.2.1 Incorporating Lean Methods into PM Optimization 32517.2.1.1 UnderstandingWaste 32517.2.1.2 Apply Lean Techniques to EliminateWaste 32617.2.1.3 Continually Improve the PM Routine 32917.2.2 Summary 33017.3 How to use Big Data to Enable Predictive Maintenance 33017.3.1 Industry Use 33117.3.2 Predicting the Future 33217.3.3 Summary 33317.4 Self-correcting Circuits and Self-healing Materials for Improved Maintainability, Reliability, and Safety 33417.4.1 Self-correcting Circuits 33417.4.2 Self-healing Materials 33517.4.3 Summary 33617.5 Conclusion and Challenge 337References 337Suggestions for Additional Reading 338Appendix A System Maintainability Design Verification Checklist 339A.1 Introduction 339A.2 Checklist Structure 339Index 353

O autorze

Louis J. Gullo, Electrical Engineer with over 35 years of leadership and hands-on experience in electronic systems, advanced technology research, reliability requirements, and engineering hardware and software development. Louis is retired from the US Army and Raytheon, an IEEE Senior Member, IEEE Reliability Society Standards Committee chair, currently employed at Northrop Grumman Corporation (NGC), Roy, UT. He is the co-editor/author of Design for Reliability and Design for Safety, both from Wiley.Jack Dixon is a Systems Engineering Consultant and President of JAMAR International, Inc. He has worked in the defense industry for over forty years doing system safety, human factors engineering, logistics support, systems engineering, program management, and business development. He is a contributing author of Design for Reliability and the co-author Design for Safety, both from Wiley.