Statistics for Innovation

Statistical Design of “Continuous” Product Innovation

  • Pasquale Erto

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Design for Innovation

    1. Front Matter
      Pages 1-1
    2. Stefano Barone, Alberto Lombardo, Pietro Tarantino
      Pages 3-25
    3. Antonio Lanzotti, Giovanna Matrone, Pietro Tarantino, Amalia Vanacore
      Pages 27-41
    4. Stefano Barone, Antonio Lanzotti
      Pages 43-64
    5. Alessandro Baldi Antognini, Alessandra Giovagnoli, Daniele Romano, Maroussa Zagoraiou
      Pages 65-88
  3. Technological Process Innovation

    1. Front Matter
      Pages 89-89
    2. Paola Pedone, Daniele Romano, Grazia Vicario
      Pages 103-121
    3. Fiorenzo Franceschini, Maurizio Galetto, Domenico Maisano, Luca Mastrogiacomo
      Pages 161-176
    4. Biagio Palumbo, Gaetano De Chiara, Roberto Marrone
      Pages 177-190
  4. Innovation of Lifecycle Management

    1. Front Matter
      Pages 191-191
    2. Maurizio Guida, Gianpaolo Pulcini
      Pages 193-211
    3. Massimiliano Giorgio, Maurizio Guida, Gianpaolo Pulcini
      Pages 213-230
  5. Research and Innovation Management

    1. Front Matter
      Pages 231-231
    2. Pasquale Erto, Giuliana Pallotta
      Pages 233-245
    3. Pasquale Erto, Amalia Vanacore
      Pages 247-260
  6. Back Matter
    Pages 261-264

About this book


The objective of this book is to illustrate statistical methodologies that incorporate physical and numerical experiments and that allow one to schedule and plan technological innovation, similar to any other productive activity. This methodology should be implemented through a structured procedure aimed at reducing the high rate of commercial failure characterizing actual innovation processes. In fact, it is well known that:

i) The rate of commercial failure of a innovative idea is very high (90–94 out of 100 proposals for innovation undergo substantial failure in the EU and in the USA).

ii) Low reliability in the long run and sensitivity to usage conditions are the factors that determine the failure of the innovation.

The definition of an iterative design activity is an objective that can be reached by subdividing the complex innovation process into "short" steps in experimental statistics research. The approach adopted to analyze customer needs and the tools used to reduce unwanted variability form the framework for the statistical design of "continuous" product innovation.

Starting from the observation that product innovation is achieved when a "quality" that is able to satisfy a new customer need is conferred on the product and survives over real operating conditions and time, this book illustrates the operative steps required to perform the whole innovation process iteratively.


Computer experiments Design for Innovation Innovation Quality engineering Reliability Robust design Sage Simulation computer simulation innovation management optimization statistics virtual reality

Editors and affiliations

  • Pasquale Erto
    • 1
  1. 1.Department of Aerospace EngineeringUniversity of Naples “Federico II”Italy

Bibliographic information