Problem solving for new engineers : what every engineering manager wants you to know / [electronic resource]
Melisa Buie.
- Boca Raton, FL : CRC Press, 2017.
- 1 online resource.
Cover; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; Foreword ; Breakthroughs I want you to know about ; In the real world ; Filling the gap ; Author ; Chapter 1: The Great Universal Cook-Off ; 1.1 Discover for Yourself ; 1.2 Creating a Context for Discovery ; 1.3 Requirements for Experimental Discovery ; 1.4 Requisite Warning Label ; 1.4.1 Understanding Variation ; 1.4.2 Demystifying Causation and Correlation ; 1.4.3 Unraveling Complex Interactions ; 1.5 Book Organization ; 1.6 Key Takeaways ; References ; Chapter 2: Eureka! And Other Myths of Discovery. 2.1 Fairy Tales 2.2 Lightning Bolts ; 2.3 Geniuses ; 2.4 Key Takeaways ; References ; Chapter 3: Experimenting with Storytelling ; 3.1 The Secrets of Science ; 3.2 The Language of Science ; 3.3 Storytelling with Data ; 3.4 Storytelling with Graphics ; 3.4.1 Experimental Sketch ; 3.4.2 Process Flow Charts ; 3.4.3 Input-Process-Output Diagram ; 3.4.4 Infographics ; 3.5 Communicating Experimental Results ; 3.5.1 Components of Graphs ; 3.5.2 Introduction and Examples of Useful Graphical Tools ; 3.5.2.1 Pie Charts ; 3.5.2.2 Histogram ; 3.5.2.3 X-Y Scatter Plots ; 3.5.2.4 Time Series Data. 3.5.2.5 Tables: When and Why 3.6 Importance of Conclusions ; 3.7 Key Takeaways ; References ; Chapter 4: Introducing Variation ; 4.1 Data Chaos ; 4.2 Data Basics ; 4.2.1 Significant Digits ; 4.2.2 Measurement Scales and Units ; 4.3 Variables ; 4.4 Measurement = Signal + Uncertainty ; 4.5 An Uncertain Truth ; 4.5.1 Strengthening the Signal ; 4.5.2 Reducing Uncertainty ; 4.6 Key Takeaways ; References ; Chapter 5: Oops! Unintentional Variation ; 5.1 History of Mistakes ; 5.2 Unintentionally Introducing Variation ; 5.3 Insurance Policy for Data Integrity ; 5.3.1 Checklists: A Safety Net. 5.3.2 Standard Operating Procedures 5.3.3 Input-Process-Output Diagrams ; 5.4 Dynamic Measurements ; 5.5 Bad Data ; 5.6 Role of Intuition and Bias ; 5.6.1 Intuition and Hunches ; 5.6.2 Paradigms ; 5.6.3 Bias and Priming ; 5.7 Key Takeaways ; References ; Chapter 6: What, There Is No Truth? ; 6.1 Measurement Evolution ; 6.2 Problems ; 6.3 Definitions ; 6.4 Measurement System ; 6.5 Standards and Calibration ; 6.6 Measurement Matching ; 6.7 Analysis Methods ; 6.7.1 Setup ; 6.7.2 Average and Range Method ; 6.7.3 Average and Range Method Analysis ; 6.7.4 Analysis of Variance Method. 6.7.5 Measurement System Problems 6.8 A Global Concern ; 6.9 Key Takeaways ; References ; Chapter 7: It's Random, and That's Normal ; 7.1 Patterns ; 7.2 Simple Statistics ; 7.3 It's Normal ; 7.4 It's Normal, so what? ; 7.5 Dark Side of the Mean ; 7.6 Key Takeaways ; References ; Chapter 8: Experimenting 101 ; 8.1 Torturing Nature ; 8.2 Processing, a Deeper Look ; 8.3 The Simplest Experimental Model ; 8.4 The Fun Begins ... ; 8.5 Key Takeaways ; References ; Chapter 9: Experimenting 201 ; 9.1 Complex Problems ; 9.2 Establishing the Experimental Process Space ; 9.3 Selecting a Design.
"This book brings a fresh new approach to practical problem solving in engineering. It covers the critical concepts and ideas that engineers must understand to solve engineering problems. When engineers graduate, they enter the work force with only one part of what's needed to effectively solve problems -- Problem solving requires not just subject matter expertise but an additional knowledge of strategy. With the combination of both knowledge of subject matter and knowledge of strategy, engineering problems can be attacked efficiently. The book focuses on developing a strategy for minimizing, eliminating, and finally controlling variation such that the intentional variation is truly is representative of the variables of interest."--Provided by publisher.