The quality loss function, introduced by Japanese engineer,
statistician and scientist Dr. Genichi Taguchi in the 1980s, is
still one of the most interesting topics in applied industrial
statistics and quality engineering and management, which presented
a paradigm shift in quality loss and product, process and/or system
quality conception. Taguchi emphasized a proactive approach toward
quality in terms of embedding quality requirements into the design
of product, process and/or system, which highly influenced today's
quality approaches such as the aquality-by-design' concept strongly
demanded in the era of the fourth industrial revolution that we are
currently facing. This book contributes to a further development,
extension and application of the Taguchi's quality loss concept,
aiming to overcome limitations of the traditional quadratic quality
loss function and to address complex demands and circumstances in a
dynamic and globalized contemporary industrial sector. It presents
essential issues and heterogeneous complementary aspects of the
quality loss function, including the theoretical background and
advances as well as different application studies. The opening
chapter is dedicated to the quality loss functions used in quality
engineering, presenting an in-depth theoretical background of the
traditional loss function, the bounded loss function concept, i.e.
the reflected normal loss function, and the family of inverted loss
functions, and proposing the recently developed loss function
types. The second chapter is focused on the Taguchi's and inverted
quality loss functions, univariate and multivariate types, and
their advances and implications in tackling real, heterogeneous
industrial problems in statistical quality and process control. The
third chapter considers an application of the quality loss and
quality cost concepts at a system level, by introducing the quality
policy model of an organization, developed and implemented in a
middle-sized manufacturing company in the automotive industry. The
fourth chapter deals with the comparison and alignment of the
Taguchi's orthogonal arrays and the traditional full factorial
approach for experimental design, including also the method for
analysis of experimental results, depicted by two use cases from
different industrial sectors. The last chapter proposes an advanced
quality loss-based method for discrete process parameter
optimization that tackles processes characterized by multiple
correlated responses. The benefits of its implementation are
illustrated on heterogeneous process optimization problems, and
comparison with several frequently used optimization methods
clearly demonstrates its superiority, effectiveness and
applicability in real industrial conditions. Therefore, this book
offers a unique combination of two aspects relevant for scientists
and statisticians, and engineers and managers, respectively: (i)
strong scientific background on the quality loss function, its
modifications and extensions, and novel, advanced developments;
(ii) hands on approach for application of the quality loss
function-based methods designed for product, process and/or system
quality improvement in different stages, from the experimental
design, via analysis of experimental results and process parameter
optimization, toward an organizational quality policy
implementation.
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