Research Papers related to Lean Six Sigma and Operational Excellence

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Jiju Antony : Professor of Quality Management, Heriot Watt University

ILSSI Director for Research and Education Services is :

Professor of Quality Management and LSS Master Black Belt.

Professor Jiju Antony,  Heriot Watt University, Edinburgh, UK

Professor Antony is a Fellow of the Royal Statistical Society (UK), Fellow of the Chartered Quality Institute (CQI), Fellow of the Institute of Operations Management (FIOM), Fellow of the American Society of Quality (FASQ), Fellow of the International Lean Six Sigma Institute (ILSSI).  He has recently been elected to the International Academy of Quality.

Leadership characteristics for Lean Six Sigma

Alessandro Laureani & Jiju Antony

In this paper, we explore the relation between Leadership and Lean Six Sigmadeployment in organisations: as leadership has been identified as a critical success factor for Lean Six Sigma deployment in organisations, this paper sets out to determine the characteristics of leadership that are more conducive to a successful implementation.

Critical failure factors of Lean Six Sigma

Saja Albliwi
Jiju Antony
Sarina Abdul Halim Lim
Ton van der Wiele

There are 34 common failure factors of LSS cited in this paper. There are some common factors for failure, such as a lack of top management commitment and involvement, lack of communication, lack of training and education, limited resources and others. Many gaps and limitations are discussed in this paper and need to be explored in future research.

link to this document:

Enhancing Robust Design with the Aid of TRIZ and Axiomatic Design

Matthew Hu
Ford Motor Company
Kai Yang
Wayne State University
Shin Taguchi
American Supplier Institute
Shin Taguchi Quality ILSSI DFSS Shin Taguchi Kai Yang DFSS Design ILSSI Quality Kai Yang This paper describes how to use the framework of Axiomatic Design to identify a proper system output response and bridge the gap between the conceptual design and the parameter design to facilitate the upfront robustness thinking.  It could be, for instance, be a design review process to investigate how a design concept may be optimized to desensitize the side effects of noise factors. It is shown that using bottom-up approach based on axiomatic design bridges the gap between conceptual design and parameter design. By applying these methods the engineer gains deeper insight of design concept structure and the physical effects of the corresponding design parameters. Keywords: Axiomatic Design; Robust Design; Basic Function; Ideal Function; S-Field Analysis; Mode of Action. Design Parameter Diagram DFSS ILSSI Quallity Taguchi

Six Sigma to distinguish patterns
in COVID-19 approaches

Willem Salentijn
School of Business and Economics, Vrije Universiteit Amsterdam,
Amsterdam, The Netherlands
Jiju Antony
Quality Management, Heriot Watt University, Edinburgh, UK and
Edinburgh Business School, Heriot Watt University, Edinburgh, UK, and
Jacqueline Douglas
Liverpool Business School, LJMU, Liverpool, UK Willem Salentijn Master Black Belt / Agile Coach / Beste Trainer van Nederland ILSSI Master Black Belt / Agile Coach / Beste Trainer van Nederland Jiju Antony ILSSI Professor of Quality Management, Heriot-Watt DOE Design of Experiments Jiju Antony ILSSI Professor of Quality Management, Heriot-Watt DOE Design of Experiments Abstract
Purpose – COVID-19 has changed life as we know. Data are scarce and necessary for making decisions on
fighting COVID-19. The purpose of this paper is to apply Six Sigma techniques on the current COVID-19
pandemic to distinguish between special cause and common cause variation. In the DMAIC structure, different
approaches applied in three countries are compared.
Design/methodology/approach – For three countries the mortality is compared to the population to
distinguish between special cause variation and common cause variation. This variation and the patterns in it
are assessed to the countries’ different approaches to COVID-19.
Findings – In the DMAIC problem-solving approach, patterns in the data are distinguished. The special cause
variation is assessed to the special causes and approaches. The moment on which measures were taken has
been essential, as well as policies on testing and distancing.
Research limitations/implications – Cross-national data comparisons are a challenge as countries have
different moments on which they register data on their population. Furthermore, different intervals are taken,
varying from registering weekly to registering yearly. For the research, three countries with similar data
registration and different approaches in fighting COVID-19 were taken.
Originality/value – This is the first study with Master Black Belts from different countries on the application
of Six Sigma techniques and the DMAIC from the viewpoint of special cause variation on COVID-19.
Keywords COVID-19, Corona, Six sigma, DMAIC, Attribute charts, Pandemic
Paper type Research paper Covid19 Six Sigma Study Analysis

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