John Wiley & Sons End-to-end Data Analytics for Product Development Cover An interactive guide to the statistical tools used to solve problems during product and process inno.. Product #: 978-1-119-48369-4 Regular price: $74.67 $74.67 Auf Lager

End-to-end Data Analytics for Product Development

A Practical Guide for Fast Consumer Goods Companies, Chemical Industry and Processing Tools Manufacturers

Giancristofaro, Rosa Arboretti / De Dominicis, Mattia / Jones, Chris / Salmaso, Luigi

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1. Auflage März 2020
312 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-119-48369-4
John Wiley & Sons

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An interactive guide to the statistical tools used to solve problems during product and process innovation

End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction.

The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors - noted experts in the field - explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book:

* Presents a guide to innovation feasibility and formulation and process development

* Contains the statistical tools used to solve challenges faced during product innovation and feasibility

* Offers information on stability studies which are common especially in chemical or pharmaceutical fields

* Includes a companion website which contains videos summarizing main concepts

Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.

Preface

About the companion Website

Chapter 1 Basic Statistical Background 1

1.1 Introduction 1

Chapter 2 The Screening Phase 15

2.1 Introduction 15

2.2 Case Study: Air Freshener Project 16

2.2.1 Plan of the Screening Experiment 16

2.2.2 Plan of the Statistical Analyses 24

Chapter 3 Product Development and Optimization 37

3.1 Introduction 37

3.2 Case Study for Single Sample Experiments: Throat Care Project 39

3.2.1 Comparing the Mean to a Specified Value 39

3.2.2 Comparing a Proportion to a Specified Value 44

3.3 Case Study for Two-Sample Experiments: Condom Project 48

3.3.1 Comparing Variability between Two Groups 48

3.3.2 Comparing Means between Two Groups 54

3.3.3 Comparing Two Proportions 56

3.4 Case Study for Paired Data: Fragrance Project 62

3.5 Case Study: Stain Removal Project 70

3.5.1 Plan of the General Factorial Experiment 70

3.5.2 Plan of the Statistical Analyses 74

Chapter 4 Other Topics in Product Development and Optimization. Response Surface and Mixture Designs 91

4.1 Introduction 91

4.2 Case Study for Response Surface Designs: Polymer Project 93

4.2.1 Plan of the Experimental Design 93

4.2.2 Plan of the Statistical Analyses 101

4.3 Case Study for Mixture Designs: Mix Up Project 112

4.3.1 Plan of the Experimental Design 112

4.3.2 Plan of the Statistical Analyses 136

Chapter 5 Product Validation 145

5.1 Introduction 145

5.2 Case Study: Gord Project 147

5.2.1 Evaluation of the Relationship among Quantitative Variables 147

5.3 Case Study: Shelf Life Project (Fixed Batch Factor) 166

5.4 Case Study: Shelf Life Project (Random Batch Factor) 170

Chapter 6 Consumer Voice 175

6.1 Introduction 175

6.2 Case Study: Top Two Box Project 177

6.3 Case Study: DOE-Top Score Project 193

6.3.1 Plan of the Factorial Design 193

6.3.2 Plan of the Statistical Analyses 194

6.4 Final Remarks 198

References
ROSA ARBORETTI is Associate Professor of Statistics at the Department of Civil, Environmental and Architectural Engineering at the University of Padova, Italy.

MATTIA DE DOMINICIS is a former R&D Vice-President in Household and Personal Care at Reckitt Benckiser in Venice, Italy.

CHRIS JONES is Vice President of R&D in Hygiene Home at Reckitt Benckiser in Montvale, USA.

LUIGI SALMASO is Full Professor of Statistics and Deputy Chair of the Department of Management and Engineering at the University of Padova, Italy.