Sigma Project Research Articles

LEAN SIX SIGMA APPROACH FOR SIMULTANEOUS QUALITY IMPROVEMENT OF COURSES IN HIGHER EDUCATION INSTITUTIONS DURING COVID-19 PANDEMIC

The purpose of this study is to assess whether Lean Six Sigma can improve the quality of teaching-learning processes in higher educational institutions during the Covid-19 pandemic. The integration of e-learning technologies with lean six sigma (LSS). DMAIC stands for five phases of sig sigma project: define, measure, analyze, improve, and control was applied to implement quality assurance in the teaching-learning process. Action research was adopted in 30 courses of a particular engineering programme. The methodology was applied as a course improvement tool, and the challenges encountered during the implementation were also studied. The LSS DMAIC methodology could successfully improve the quality of various courses simultaneously through online mode during the Covid-19 pandemic. The adopted methodology could assist in effectively responding during the present stage of uncertainty and provide stakeholders with guidelines to deal with the post-pandemic era. In terms of practical implications, this study discusses a new approach to improving the quality of the teaching-learning process in higher educational institutions. The LSS DMAIC is applied with the help of online educational and social media platforms for the simultaneous improvement of courses in a particular engineering programme.

A curvilinear assessment of innovation in Six Sigma project teams: the influence of psychological safety and intrinsic motivation

PurposeTo investigate the factors affecting innovation in Six Sigma improvement teams. Based on Activation Theory, this study explores the possibility of an inverted U-shaped association between psychological safety and innovation and examines how intrinsic motivation moderates this relationship.Design/methodology/approachModerated regression analysis is carried out to test the curvilinear relationship, using data collected from 324 members of 102 Six Sigma improvement teams from two European manufacturing firms.FindingsThe findings demonstrate that the beneficial effect of psychological safety reaches an inflection point, after which its relations with innovation cease to be linear and positive; this gives the relationship a curvilinear pattern (inverted U-shaped). Further, intrinsic motivation has a supportive effect in enhancing the beneficial impact of psychological safety on innovation, and in shifting the inflection points to a higher level; this demonstrates their synergetic influence on innovation.Originality/valueThe impact of psychological safety on innovation is examined from the new perspective of a curvilinear relationship. This is one of the first studies to investigate the combined effects of individual (intrinsic motivation) and team-level antecedents (psychological safety) on innovation in Six Sigma teams. The study provides insights into how Six Sigma enhances innovation and offers some valid inputs to the current academic debate on this topic.

Quality Improvement Project Selection Using Fuzzy AHP and TOPSIS to Support Lean Six Sigma at PT ABC

This research aims to improve project quality at PT ABC by integrating the Fuzzy Analytical Hierarchy Process (F-AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within the Lean Six Sigma framework. This method assesses and selects quality improvement projects by considering uncertainty and complexity in decision-making. The Fuzzy AHP approach is used to flexibly assign criteria weights, while TOPSIS is used to rank projects based on performance scores relative to the ideal solution. This research aims to select the most suitable Lean Six Sigma project using the MCDM fuzzy AHP and TOPSIS approaches at PT ABC. There are three alternative quality improvement projects and three assessment criteria. The data processing results using Fuzzy AHP and TOPSIS showed that the most influential criterion was the impact criterion, with a value of 0.665. Overall, the order of influencing criteria is cost (0.260) and time (0.075). Based on a review of all criteria, the project to increase the drive plate production line (A) capacity was ranked first with a value of 0.772. Second place is the project to increase capacity and consolidate rear axle assemblies A and B with a value of 0.5529. Finally, the third is the process innovation and integrated manufacturing project to strengthen the business with a value of 0.4053.

Six sigma project generation and selection: an action research study

PurposeThe purpose of this paper is to test and develop a method for generation and selection of six sigma projects. This is done by testing the use of the generation and selection method for six sigma projects (GSM_SSP) in a Brazilian manufacturing industry with the participation of managers, aiming to gather the user’s perspective and improvement opportunities for the approach itself.Design/methodology/approachThe work adopts the action research (AR) approach once the researchers were busily involved in the training, implementation and use of the GSM_SSP. The intervention was performed in on a series of 15 workshops, with a group of managers, during six months.FindingsThe application of the eight steps of the GSM_SSP approach assisted the company’s management team to generate nine project candidates and also to select three six sigma projects. This study also finds and discusses barriers and lessons learned used to improve the GSM_SSP.Research limitations/implicationsThis study presents an example of how six sigma project generation and selection has been applied to a manufacturing industry by adapting AR to the process using the eight steps of GSM_SSP, demonstrating how the management team was involved. This study should be replicated in different companies because AR is limited in its generalization.Originality/valueTo the best of the authors’ knowledge, this study represents the first use of AR methodology in six sigma project selection. This study contributes a method that can generate and select six sigma projects. In doing so, the research offers a simple approach that can be used by managers. In addition, the steps of the approach before selection were explored.

Optimizing workflow of urgent stroke endovascular intervention: A focused lean six sigma project

IntroductionUrgent endovascular intervention is currently accepted as the primary and critical therapeutic approach to patients whose acute ischemic stroke results from a large arterial occlusion (LAO). In this context, one of the quality metrics most widely applied to the assessment of emergency systems performance is the “door-to-puncture” (D-P) time. We undertook a project to identify the subinterval of the D-P metric causing the most impact on workflow delays and created a narrowly focused project on improving such subinterval. MethodsUsing the DMAIC (i.e., define, measure, analyze, improve and control) approach, we retrospectively reviewed our quality stroke data for calendar year (CY) 2021 (i.e., baseline population), completed a statistical process control assessment, defined the various subintervals of the D-P interval, and completed a Pareto analysis of their duration and their proportional contribution to the D-P interval. We retooled our workflow based on these analyses and analyzed the data resulting from its implementation between May and December 2022 (i.e., outcome population). ResultsThe baseline population included 87 patients (44 men; mean age = 67.2 years). Their D-P process was uncontrolled, and times varied between 35-235 minutes (Mean = 97; SD = 38.40). Their door to angiography arrival (D-AA) subinterval was significantly slower than their arrival to puncture (AA-P) (73.4 v. 23.5 minutes; p < 0.01), accounted for 73% of the average length of the D-P interval. The group page activation to angiography arrival (GP-AA) subinterval accounted for 41.5% of the entire D-AA duration, making it the target of our project. The outcome population originally consisted of 38 patients (15 men; mean age = 70.3 years). Their D-P process was controlled, its times varying between 43-177 minutes (Mean = 85.8; SD = 34.46), but not significantly difference than the baseline population (p = 0.127). Their target subinterval GP-AA varied between 0-37 minutes and was significantly improved from the baseline population (Mean = 13.21 v. 29.68; p < 0.001). ConclusionsIt seems feasible and reasonable to analyze the subinterval components of complex quality metrics such as the D-P time and carry out more focused quality improvement projects. Care must be exercised when interpreting the impact on overall system performance, due to unexpected variations within interdependent subprocesses. The application of a robust and comprehensive LSS continuous quality improvement process in any CSC will have to include individualized focused projects that simultaneously control the different components of overall system performance.

How to Estimate the Sigma Level of the Process

Purpose: This paper proposes a procedure for estimating the sigma level of the process through a confidence interval. Methodology/Approach: The approach is based on a model in which the process has a normal distribution and constant variance, and its mean is shifted to the right or left by 1.5 standard deviations. Findings: The paper explains a method for creating a random sample along with determining the sample size to estimate the “defects per million opportunities” characteristic through a confidence interval. Based on it, the confidence interval for the “sigma level” of the process is determined. Research Limitation/implication: We assume a discrete process in which n pieces of the product are selected. The proposed procedure assumes that the process is in statistical control. Originality/Value of paper: Applying the proposed random sampling and estimation procedure can improve evaluations of process performance, aiding decision-making for Six Sigma projects.

Promoting shared leadership in Lean Six Sigma project teams: toward a three-way interaction model

PurposeShared leadership is an effective mechanism for managing project teams. Its performance-enhancing benefits have been demonstrated in many studies. Nonetheless, there is an obvious silence about how to promote shared leadership in Lean Six Sigma (LSS) project teams. To address this deficit, the purposes of this study are to investigate the influence of shared leadership on LSS project success and to explore how team psychological safety, project task complexity and project task interdependence influence shared leadership.Design/methodology/approachA multi-source, time-lagged survey design with a four-month interval was conducted. To do this, the authors collected data from 71 project teams (comprising 71 project managers and 352 project members) using LSS approaches in the manufacturing and service industries.FindingsThe findings show that shared leadership positively influences LSS project success. The authors also found that team psychological safety fosters the development of shared leadership and, more importantly, these effects are stronger when the tasks are more complex and more interdependent.Practical implicationsThese findings advance our understanding of the factors that enable shared leadership and equip LSS project managers with practical techniques to improve shared leadership for the success of their projects.Originality/valueThis study extends the theory of shared leadership to the context of LSS project management and is among the first, to the best of the authors’ knowledge, to theoretically propose and empirically validate how to promote shared leadership in LSS project teams.

Agile DMAIC cycle: incorporating process mining and support decision

PurposeThe aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.Design/methodology/approachThe approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.FindingsIt was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.Practical implicationsThrough the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.Originality/valueThe authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

Six Sigma Project Prioritization and Selection Using AHP–CODAS Integration: A Case Study in Healthcare Industry

Given the complex nature of Six Sigma project (SSP) prioritization and selection processes, multicriteria decision-making (MCDM) methods may help organizations identify the most effective projects. Considering potential limitations of subjective methods and advantages of MCDM methods, this article proposes a model that integrates analytical hierarchy process (AHP) and combinative distance-based assessment (CODAS) in SSP prioritization and selection process. In the proposed approach, AHP is employed to assign criteria weights, and CODAS is performed to determine priorities of SSPs. CODAS was advanced in term of its threshold function. Differences between Euclidean distances of two alternatives were compared, based on the standard deviation of Euclidean distances of all alternatives to overcome the subjectivity. This is the first study that combines AHP and CODAS methods for SSP selection, and CODAS is used with objective threshold value computation, and developed for the healthcare industry. In this article, ten SSPs were evaluated for four key criteria groups as financial, operational, patient centric, and organizational main criteria groups. In total, 18 subcriteria were considered under these four main criteria groups. This article provides a support for executives who make implementation plans for the potential SSPs.

DMAIC Analysis of Educational Institutes in Pakistan

Pakistan is growing interest in implementing DMAIC in educational institutions to promote both quality and effectiveness. To teach learners about Six Sigma, the education sector is extremely important. Educational institutes don't want to adopt new technologies teaching methods or assessment strategies and fear of the unknown can make people resistant to trying something new or different they did not use proper training for the students and teachers thus, they didn't have any idea regarding the Six Sigma project, hence management wind up the training. Six Sigma and the education sector now have gaps in innovative learning styles, quality management, novel classroom learning methods, and effective teacher behaviour. A popular method of quality improvement Six Sigma is to be applied in a study using the DMAIC (define, measure, analyze, implement and control) criteria.

Employees' preference analysis on lean six sigma program coaching attributes using a conjoint analysis approach

The purpose of this study was to determine the preference of employees for Lean Six Sigma project coaching attributes. Conjoint analysis with an orthogonal design was utilized and six attributes were considered: coaching style, frequency of coaching sessions, duration of coaching sessions, the turn-around time of feedback, documentation review, and mock defense. In addition, 4 different projects were also evaluated: Quick Win project, Yellow Belt project, Green Belt project, and Black Belt project. The results showed that for Quick Win projects, employees consider conducting a mock defense as the highest preference, followed by having a documentation review, and a democratic coaching style. For Yellow Belt projects, employees considered conducting a mock defense as the highest preference, followed by having a documentation review, and a weekly coaching session. For Green Belt projects, employees consider having a documentation review as the highest preference, followed by a transactional coaching style, and conducting a mock defense. Lastly, for Black Belt projects, employees consider having a documentation review as the highest preference, followed by conducting a mock defense, and a 1-week turn-around time for feedback. The results of this study will help companies to implement and to sustain better employee-oriented LSS programs.

Principles for the Europeanisation of Public Administration

Administrative regimes are no longer isolated phenomena: they are constantly confronted with international influences, which shape the internal structure and system of the states. The cooperation between the European Union and the Member States’ administration is today a kind of convergence in principles. This is what the EU expects from the candidate countries and in the neighbourhood policy. The main question of the study is whether the content of the principles used by the EU is cognisable and consistent. The study covers two policy instruments: the SIGMA project, which is a joint EU–OECD collaboration, and the comparative legal activities of the ReNEUAL. These instruments testify two completely different attitudes: one does not explain the principle but holds it accountable, the other seeks the means to understand its content and the reasons for the differences in interpretations. Both programs have undergone internal development, but while SIGMA has moved away from its administrative procedural roots, ReNEUAL has confirmed it. The paper is another argument in favour of the need for administrative research using the tools of comparative law.

Efficiency analysis of Lean Six Sigma projects: insights for selection and prioritisation

The main purpose of this article is to identify the main characteristics of Lean Six Sigma projects executed by efficient companies. To do so, this article explores a large empirical database, with 112,421 projects, executed from 2001 to 2018 in 57 strategic business units from a heavy machinery producer, which is recognised as a worldwide reference in the use of Lean Six Sigma methodology. The research was conducted in two stages, first, the data was analysed with a Network Data Envelopment Analysis (DEA) model, which provided an efficiency ranking formed by the strategic business units. In the second stage, a Classification Tree (CHAID) method was used to identify the common characteristics of the projects accomplished by the most efficient ones. The findings show that these strategic business units are characterised by projects executed in departments closely related to senior management, especially Corporate Governance and Business Strategy. In addition, their projects usually focus on people, innovation, or cost reduction and are structured more frequently with the DMAIC cycle. These findings broaden the understanding of the criteria that should be considered in Lean Six Sigma project selection and prioritisation, by providing new insights (not identified in previous studies) to decision-makers and researchers, from projects associated with the efficient performance of Lean Six Sigma, which can be particularly valuable considering the multiple projects conducted in this initiative, that frequently compete for resources.

Selection of Six Sigma projects based on integrated multi-criteria decision-making methods: the case of the software development industry

Selection of Six Sigma projects based on integrated multi-criteria decision-making methods: the case of the software development industry

Analysis of the Impact of Six Sigma and Risk Management on Iraq's Energy Sector Metrology

Purpose: aims the study to show How to be can to enhance measurement management by incorporating a risk-based approach and the six sigma method into a more thorough assessment of metrological performance. Theoretical framework: Recent literature has recorded good results in analyzing the impact of Six Sigma and risk management on the energy sector (Barrera García et al., 2022) (D'Emilia et al. 2015). However, this research came to validate and emphasize the most comprehensive assessment of metrological performance by integrating Risk management based approach and Six Sigma analysis. Design/methodology/approach: This study was conducted in Iraqi petroleum refining companies. System quality is measured in terms of sigmas, and two indices—one for actualizing metrological risk and another for its management—are assessed. Findings: We find the all dimensions of the six sigma projects implemented facilitate the correction and adaptation of the main tasks aimed at improving the measurement management system. Research, Practical &amp; Social implications: a risk-based approach and the six sigma method are can enhance the measurement management system and collect feedback on its performance. Originality/value: The merge a risk-based approach and the six sigma method its usefulness as a methodological tool for enhancing measurement management has been demonstrated.

EFSA info‐session on Avian Influenza surveillance data in the context of the SIGMA Project

This report describes the content and the outcomes of the info-session held by EFSA in videoconference on 17 November 2022. The info-session aimed at informing the country-representatives on the new Avian influenza (AI) data collection based on the approach developed by the SIGMA project. EFSA is in charge of collating, validating, analysing, and summarising in an annual report the data resulting from the AI surveillance activities in poultry and wild birds carried out by the European Union (EU) Member States (MSs), upon mandate M-2017-0221, received from the European Commission. During the info-session, benefits of the SIGMA approach were shown, and the EFSA data models were presented together with the tools provided by EFSA to support data providers and validators. The goal of the SIGMA project is the increase of standardisation, harmonisation and interoperability of data on animal diseases and domestic animal populations. The SIGMA approach entails the application of the SIGMA animal population data model, designed to collect information at establishment and subunit (farm/house) level, and of the laboratory data model, the latter based on Standard Sample Description version 2 (SSD2), but further tailored to the animal health needs. As a major novelty, countries will be asked to submit poultry population data at subunit level and positive and negative laboratory test results at sample level, both for domestic and wild birds. With this level of detail, EFSA will be able to perform more informative statistical analysis to be included in the annual report on AI. Thanks to the automation of the process (under development) EFSA aims at reducing the time between data submission and report publication, making the scientific outputs more timely and relevant. Moreover, un-aggregated data can be more easily used for other risk assessment purposes by EFSA (e.g., welfare, biosecurity, etc.), avoiding double requests for data submission in the future. EFSA calls for the MSs’ collaboration during the pilot phase in 2023 as a crucial element for the success of the initiative.

Application of six sigma through deep learning in the production of fasteners

PurposeThe purpose of this study was conducted at an enterprise that produces fasteners and is one of the leading companies in the sector in terms of market share. Possible defects in the coating of bolts and nuts either lead to products being scrapped or all of the coating process being repeated from beginning to end. In both cases, the enterprise faces a waste of time and excessive costs. Through this project, the six sigma theory and its means were effectively used to improve the efficiency and quality management of the company. The selection of the six sigma project has also contributed to the creation of various documents to be used for project screening and evaluation of financial results.Design/methodology/approachSix sigma is an optimization strategy that is used to improve the profitability of businesses, avoid waste, scrap and losses, reduce costs and improve the effectiveness of all activities to meet or exceed customers’ needs and expectations. Six sigma’s process improvement model, known as Definition-Measurement-Analysis-Improvement-Control, contributes to the economic and technical achievements of businesses. The normal distribution of a process should be within ±3 sigma of the mean. This represents a scale of 99.7% certainty. However, improving the process through the utilization of the six sigma rule, which accepts normal variabilities of processes twice as strict, will result in an error rate of 3.4 per million instead of 2,700 per million for each product or service.FindingsUsing six sigma practices to reduce the costs associated with low quality and to increase economic added value became a cultural practice. With this, the continuation of six sigma practices throughout the Company was intended. The annual cost reduction achieved with the utilization of six sigma practices can be up to $21,780. When time savings are also considered, a loss reduction of about $30,000 each year can be achieved. The coating thickness efficiency increased from 85% to 95% after the improvements made through the six sigma project. There is a significant increase in the efficiency of coating thickness. In addition, the coating thickness efficiency is also close to the target value of 95%–97%.Originality/valueThe results of the study were optimized with the help of deep learning. The performance of the model created in deep learning was quite close to the actual performance. This result implicates the validity of the improvement work. The results may act as a guide for the use of deep learning in new projects.

How project management principles affect Lean Six Sigma program and projects

Goal: This paper aims to explores and understand which project management principles most contributes to implementing Lean Six Sigma program and projects. Design/Methodology/Approach: Through a systematic literature review, some key works related to the objective were searched in Scopus and Web of Science databases in order to provide metadata that could be further analysed and used as source of information to answer the research questions of this work. Results: The research provides evidence that project alignment with organizational goals plays a significant role in Lean Six Sigma program success, referring the importance of a structured portfolio management. To complement the list of principles, stakeholder’s management and well-defined project scope also contributes to same success metrics. In the other hand, risk management, project schedule and hybrid project management approaches remain unclear in the literature, do not providing sufficient data to validate its relation to success. Limitations of the investigation: As principal limitation could be pointed the project selection by title and abstract analysis and the coding scheme. Both points are not easy to be replicated, but the final sample could retrieve closer results. Practical Implications: For practitioners, this work contributes summarizing in a quantitative form which are the principal principles in project management that could be used to implement or improve Lean Six Sigma project and programs. Originality/ Value: This work brings for academics what were discussed early about the constructs Lean Six Sigma and Project Management and which are the gaps that remains unclear.

Clustering and identifying the Lean Six Sigma projects: higher education institutes

Lean Six Sigma (LSS) is an effective quality improvement program. The deployment of LSS in organisations is done with significant investment as it has many benefits. As to higher education institutes (HEIs), this system has not been applied in the manner it should be. Identifying an appropriate project requires a precise analysis of the data to make all the selected projects in line with the organisation strategy objectives, and with the least uncertainty rate in implementation. Actually, the concern is not merely the application of LSS, but also the successful implementation of the best improving project. In this study, 133 main processes were identified in the determined four zones of the University of Isfahan, and assessed using the five Lean Six Sigma indicators clustered in SPSS Clementine 12.0 S/W based on the viewpoints of the managers and professionals of the zones. 19 out of 133 processes were found critical, with higher priorities in defining the Lean Six Sigma projects. While clustering is an appropriate approach for the identification of higher education institutes, it is not possible through the common methods. Based on the evaluation of the involved managers and professionals, the proposed approach is efficient, practical, and dynamic.

Lean Six Sigma: a clinical treatment for national healthcare system

Lean Six Sigma is a business-driven, multi-faceted approach to process improvement, reduce costs, and increase profit. It helps to improve quality of product and cost saving. Lean Six Sigma is considered to be one of the best quality improvement methodology applied successfully to organisational areas like manufacturing, production, accounting and finance, sales and marketing, information systems, human resource management, etc. Lean Six Sigma is a project driven approach that concentrates on reducing variations, defects and improving the quality of products, processes as well as services. Basically Lean Six Sigma measures 3.4 defects per million of opportunities (DPMO) and it operate on the concept of DMAIC. In the proposed work, guides how DMAIC can be successfully implemented in medical transcription to identify different Lean Six Sigma projects by identifying critical to quality (CTQ).