Page 1 of 30
Journal for Studies in Management and Planning
Available at http://internationaljournalofresearch.org/index.php/JSMaP
e-ISSN: 2395-0463
Volume 01 Issue 03
April 2015
Available online: http://internationaljournalofresearch.org/ P a g e | 615
The Quality Improvement and Quality of
Products in Organization
Karmjeet Kaur ; Narinder Kumar Sharma
College: - University College Of Computer Applications
Email Id: - karmsidhu82@gmail.com
ABSTRACT
Many quality improvement (QI) programs
including six sigma, design for six sigma, and
kaizen require collection and analysis of data
to solve quality problems. Due to advances in
data collection systems and analysis tools,
data mining (DM) has widely been applied
for QI in manufacturing. Although a few
review papers have recently been published to
discuss DM applications in manufacturing,
these only cover a small portion of the
applications for specific QI problems (quality
tasks). In this study, an extensive review
covering the literature from 1997 to 2007 and
several analyses on selected quality tasks are
provided on DM applications in the
manufacturing industry. The quality tasks
considered are; product/process quality
description, predicting quality, classification
of quality, and parameter optimization. The
review provides a comprehensive analysis of
the literature from various points of view:
data handling practices, DM applications for
each quality task and for each manufacturing
industry, patterns in the use of DM methods,
application results, and software used in the
applications are analyzed. Several summary
tables and figures are also provided along
with the discussion of the analyses and
results. Finally, conclusions and future
research directions are presented.
Highlights: - Review, data mining
applications, manufacturing, 1997–07,
selected quality problems, and typically
small, separately stored quality and
production data. Increasing use of DM,
especially in metal, computer and electronics
industries, Common use of artificial neural
networks for prediction and design
optimization General purpose software
preferred over specialized DM software.
Page 2 of 30
Journal for Studies in Management and Planning
Available at http://internationaljournalofresearch.org/index.php/JSMaP
e-ISSN: 2395-0463
Volume 01 Issue 03
April 2015
Available online: http://internationaljournalofresearch.org/ P a g e | 616
Keywords: - Knowledge discovery in
databases; Data mining; Quality
improvement; Six sigma; Design for six
sigma; Quality description; Prediction;
Classification; Parameter optimization; Data
mining software; Manufacturing
1. INTRODUCTION
Quality management ensures that an
organization, product or service is consistent.
It has four main components: quality
planning, quality control, quality assurance
and quality improvement. Quality
management is focused not only on product
and service quality, but also the means to
achieve it. Quality management therefore uses
quality assurance and control of processes as
well as products to achieve more consistent
quality.
There are many methods for quality
improvement. These cover product
improvement, process improvement and
people based improvement. In the following
list are methods of quality management and
techniques that incorporate and drive quality
improvement:
Figure 1.1 the PDCA Cycle
ISO 9004:2008 — guidelines for
performance improvement.
ISO 15504-4: 2005 — information
technology — process assessment —
Guidance on use for process
improvement and process capability
determination.
QFD — quality function deployment,
also known as the house of quality
approach.
Kaizen — 改善, Japanese for change
for the better; the common English
term is continuous improvement.
Zero Defect Program — created by
NEC Corporation of Japan, based
upon statistical process control and
one of the inputs for the inventors of
Six Sigma.
http://upload.wikimedia.org/wikipedia/commons/thumb/7/7a/PDCA_Cycle.svg/1024px-PDCA_Cycle.svg.png
Page 3 of 30
Journal for Studies in Management and Planning
Available at http://internationaljournalofresearch.org/index.php/JSMaP
e-ISSN: 2395-0463
Volume 01 Issue 03
April 2015
Available online: http://internationaljournalofresearch.org/ P a g e | 617
Six Sigma — 6σ, Six Sigma combines
established methods such as statistical
process control, design of experiments
and failure mode and effects analysis
(FMEA) in an overall framework.
PDCA — plan, do, check, act cycle
for quality control purposes. (Six
Sigma's DMAIC method (define,
measure, analyze, improve, control)
may be viewed as a particular
implementation of this.)
Quality circle — a group (people
oriented) approach to improvement.
Taguchi methods — statistical
oriented methods including quality
robustness, quality loss function, and
target specifications.
The Toyota Production System — reworked
in the west into lean manufacturing.
Kansei engineering — an approach
that focuses on capturing customer
emotional feedback about products to
drive improvement.
TQM — total quality management is a
management strategy aimed at
embedding awareness of quality in all
organizational processes. First
promoted in Japan with the Deming
prize which was adopted and adapted
in USA as the Malcolm Baldrige
National Quality Award and in Europe
as the European Foundation for
Quality Management award (each
with their own variations).
TRIZ — meaning "theory of inventive
problem solving"
BPR — business process
reengineering, a management
approach aiming at optimizing the
workflows and processes within an
organization.
OQRM — Object-oriented Quality
and Risk Management, a model for
quality and risk management.
Proponents of each approach have sought to
improve them as well as apply them for small,
medium and large gains. Simple one is
Process Approach, which forms the basis of
ISO 9001:2008 Quality Management System
standards, duly driven from the 'Eight
principles of Quality management', process
approach being one of them. Thareja writes
about the mechanism and benefits: "The
process (proficiency) may be limited in
words, but not in its applicability. While it
fulfills the criteria of all-round gains: in terms
of the competencies augmented by the
