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Mastering Uncertainty in Mechanical Engineering.

Bibliographic Details
Main Author: Pelz, Peter F.
Other Authors: Groche, Peter., Pfetsch, Marc E., Schaeffner, Maximilian.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2021.
Edition:1st ed.
Series:Springer Tracts in Mechanical Engineering Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Preface
  • Acknowledgements
  • Contents
  • 1 Introduction
  • 1.1 Motivation
  • 1.2 Holistic Control of Uncertainty over the Phases of the Product Life Cycle
  • 1.3 Components are Represented in Models
  • 1.4 Data and Data Sources
  • 1.5 Component Structures
  • 1.6 Sustainable Systems Design-The Extended Motivation for This Book
  • 1.7 Outlook on the Following Book Structure
  • References
  • 2 Types of Uncertainty
  • 2.1 Data Uncertainty
  • 2.1.1 Introduction
  • 2.1.2 Stochastic Data Uncertainty
  • 2.1.3 Incertitude
  • 2.2 Model Uncertainty
  • 2.2.1 Functional Relations, Scope and Complexity of Mathematical Models
  • 2.2.2 Approaches to Detect, Quantify, and Master Model Uncertainty
  • 2.3 Structural Uncertainty
  • References
  • 3 Our Specific Approach on Mastering Uncertainty
  • 3.1 Beyond Existing Approaches
  • 3.2 Uncertainty Propagation Through Process Chains
  • 3.3 Five Complementary Methods for Mastering Uncertainty in Process Chains
  • 3.4 Time-Variant, Dynamic and Active Processes
  • 3.5 Strategies for Mastering Uncertainty-Robustness, Flexibility, Resilience
  • 3.6 Exemplary Technical System Mastering Uncertainty
  • 3.6.1 Modular Active Spring-Damper System
  • 3.6.2 Active Air Spring
  • 3.6.3 3D Servo Press
  • References
  • 4 Analysis, Quantification and Evaluation of Uncertainty
  • 4.1 Identification of Uncertainty During Modelling of Technical Processes
  • 4.1.1 Analysis of Data Uncertainty Using the Example of Passive and Active Vibration Isolation
  • 4.1.2 Bayesian Inference Based Parameter Calibration for a Mathematical Model of a Load-Bearing Structure
  • 4.1.3 Model-Based Analysis of Uncertainty in Chained Machining Processes
  • 4.2 Data-Induced Conflicts
  • 4.2.1 Dealing with Data-Induced Conflicts in Technical Systems
  • 4.2.2 Data-Induced Conflicts for Wear Detection in Hydraulic Systems.
  • 4.2.3 Fault Detection in a Structural System
  • 4.3 Analysis, Quantification and Evaluation of Model Uncertainty
  • 4.3.1 Detection of Model Uncertainty via Parameter Estimation and Optimum Experimental Design
  • 4.3.2 Detection of Model Uncertainty in Mathematical Models of the 3D Servo Press
  • 4.3.3 Assessment of Model Uncertainty for the Modular Active Spring-Damper System
  • 4.3.4 Model Uncertainty in Hardware-in-the-loop Tests
  • 4.3.5 Identification of Model Uncertainty in the Development of Adsorption Based Hydraulic Accumulators
  • 4.3.6 Uncertainty Scaling-Propagation from a Real Model to a Full-Scale System
  • 4.3.7 Improvement of Surrogate Models Using Observed Data
  • 4.3.8 Uncertainty Quantification with Estimated Distribution of Input Parameters
  • 4.4 Representation and Visualisation of Uncertainty
  • 4.4.1 Ontology-Based Information Model
  • 4.4.2 Visualisation of Geometric Uncertainty in CAD Systems
  • 4.4.3 Digital Twin of Load Carrying Structures for the Mastering of Uncertainty
  • References
  • 5 Methods and Technologies for Mastering Uncertainty
  • 5.1 Technical and Legal Requirements for Mastering Uncertainty
  • 5.1.1 `Just Good Enough' Versus `as Good as It Gets': Negotiating Specifications in a Conflict of Interest of the Stakeholders
  • 5.1.2 Technical Specification
  • 5.1.3 Product Safety Requirements for Innovative Products
  • 5.1.4 Legal Uncertainty and Autonomous Manufacturing Processes
  • 5.1.5 Optimisation Methods and Legal Obligations
  • 5.1.6 Linguistic Analysis of Technical Standards to Identify Uncertain Language Use
  • 5.1.7 From Risk to Uncertainty-New Logics of Project Management
  • 5.2 Product Design Under Uncertainty
  • 5.2.1 The Method of Uncertainty Analysis and Evaluation: UMEA
  • 5.2.2 Mastering Uncertainty in Product Development.
  • 5.2.3 Methodical Uncertainty Consideration in Technical Process Modelling
  • 5.2.4 Conflicting Objectives in the Determination of Process and Component Control
  • 5.2.5 Estimation of Surrogate Models
  • 5.2.6 Density and Quantile Estimation in Simulation Models
  • 5.2.7 Mastering Uncertainty in Customer-Integrated Change Management
  • 5.3 Mastering Propagated Uncertainty in Process Chains
  • 5.3.1 Uncertainty Propagation in a Forming and Machining Process Chain
  • 5.3.2 Closed-Loop Control of Product Stiffness and Geometry
  • 5.3.3 Controlled Partial Post-compaction of Sintered Bevel Gears
  • 5.3.4 Forming Integration of Functional Materials in Load-Bearing Structures and Machine Elements
  • 5.3.5 Process Controlling During the Production of Smart Structures
  • 5.3.6 Process-Integrated Calibration of Smart Structures
  • 5.4 Semi-active and Active Process Manipulation
  • 5.4.1 Control of Press Stiffness
  • 5.4.2 State Control of Combined Roller and Plain Bearings
  • 5.4.3 Development of a Sensor-Integrated Compensation Chuck for Semi-active Control of the Tapping Process
  • 5.4.4 Shock Absorber with Integrated Hydraulic Vibration Absorber to Improve Driving Dynamics
  • 5.4.5 Active Air Spring for Vibration Reduction in Vehicle Chassis
  • 5.4.6 Vibration Attenuation in Beam Truss Structures Via (Semi-)active Piezoelectric Shunt-Damping
  • 5.4.7 Active Buckling Control of Compressively Loaded Beam-Columns and Trusses
  • 5.4.8 Load Redistribution Via Semi-active Guidance Elements in a Kinematic Structure
  • References
  • 6 Strategies for Mastering Uncertainty
  • 6.1 Robustness
  • 6.1.1 Robust Topology Optimisation of Truss Structures
  • 6.1.2 Optimal Actuator Design and Placement
  • 6.1.3 Mathematical Optimisation in Robust Product Design
  • 6.1.4 Quantified Programs
  • 6.1.5 Mastering of Disturbing Influences in Early Phases of Product Development.
  • 6.1.6 Uncertainty-Based Product Design in Robust Design
  • 6.1.7 Non-linear Robust Closed-Loop Control of Presses with Geometric Singularities
  • 6.1.8 Mastering Uncertainty in Tapping and Reaming by Robust Tools and Processes
  • 6.2 Flexibility
  • 6.2.1 Total Flexibility in Forming Technology
  • 6.3 Resilience of Technical Systems
  • 6.3.1 Resilience as a Concept to Master Uncertainty
  • 6.3.2 Mastering Uncertainty in Engineering Design by Adaptive Resilience
  • 6.3.3 Human Factors in Resilient Socio-Technical Systems
  • 6.3.4 Truss Topology Optimisation Under Aspects of Resilience
  • 6.3.5 Optimal Design of Resilient Systems on the Example of Water Supply Systems
  • 6.3.6 Application of Resilience Metrics to the Fluid Dynamic Vibration Absorber in Drop Tests
  • 6.3.7 Concept of a Resilient Process Chain to Control Uncertainty of a Hydraulic Actuator
  • 6.3.8 Experimental Evaluation of Resilience Metrics in a Fluid System
  • References
  • 7 Outlook
  • 7.1 Towards the Complete Picture
  • 7.2 Future of Mastering Uncertainty
  • 7.2.1 Robustness
  • 7.2.2 Flexibility
  • 7.2.3 Resilience
  • 7.3 Final Remarks
  • References
  • 8 Correction to: Mastering Uncertainty in Mechanical Engineering
  • Correction to: P. Pelz et al. (eds.), Mastering Uncertainty in Mechanical Engineering, Springer Tracts in Mechanical Engineering, https://doi.org/10.1007/978-3-030-78354-9
  • Appendix Glossary.

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