Sigma Project Research Articles

A Lean Six Sigma (LSS) Project Management Improvement Model

Current economic crisis raises the constant demand for profitable solutions that allow organizations to gain competitive advantage. For this reason, more and more companies search for management methodologies that allow them to improve their products and/or service characteristics, perfect their processes, decrease costs, improve the capital's profitability and costumers’ satisfaction. This have been attempted through Lean Management and Six Sigma integrated approaches in their managerial and production processes in which, Lean focus mainly on the waste elimination, using simple and visual techniques whenever possible and Six Sigma on the control and processes variability reduction, using statistical tools for this purpose.The present article proposes a Lean Six Sigma (LSS) project management improvement model supported by the DMAIC cycle and integrating an enlarged and adapted set of statistical tools, given the nature of the project management main variables and the involved processes. The proposed model was tested in a Portuguese telecommunication company context which project management processes system are based on Project Management Institute (PMI) standards. The model allowed identifying company's main project management problems and associated causes and the selection of the causes to be first attended. The proposed model also permitted to systematically address the actions and solutions to be implemented in order to keep, in the long run, the continuous improvement of the project management processes in the organization.

Reduction in Repair rate of Welding Processes by Determination & Controlling of Critical KPIVs

Six Sigma is being Implemented all over the World as a successful Quality Improvement Methodology. Many Companies are now days are using Six Sigma as an Approach towards zero defects. This article provides a practical case study regarding the implementation of Six Sigma Project in a Welding Facility and discusses the Statistical Analysis performed for bringing the welding processes in the desired sigma Limits. DMAIC was chosen as potential Six Sigma methodology with the help of findings of this Methodology, Six Sigma Team First Identified the critical Factors affecting the Process Yield and then certain Improvement Measures were taken to improve the Capability of Individual welding Processes and also of Overall Welding Facility. Cost of Quality was also measured to Validate the Improvement results achieved after Conducting the Six Sigma Project.

Identifying the role of human resource management in increasing performance and implementation of six sigma projects using fuzzy cognitive maps

Article history: Received December 10, 2013 Received in revised format 12 March 2013 Accepted April 14 2014 Available online April 16 2014 Six Sigma is known as the best quality management system, which has been applied in different places with distinct tasks. Any implementation of Six Sigma project normally can succeed only when human resource management is applied within the organization, properly. In this paper, we illustrate the intense of relationships between the human resources management indices and Six Sigma project implementation indices for some selected Iranian manufacturing firms. By using the fuzzy cognitive maps (FCM), we are able to show the strength of relationships among various indices. This study helps quality and human resource managers learn how to manage the critical indices to achieve their determined goals and to increase Six Sigma project performance throw human resource management perspective. © 2014 Growing Science Ltd. All rights reserved.

Generic Lean Six Sigma project definitions for the construction industry

Fuelled by an increased level of competitiveness in the construction industry, construction companies must continuously improve their processes to ensure high-quality and reliable products at low cost. The purpose of this paper is to support in defining Lean Six Sigma (LSS) projects in this industry. On the basis of our sample of LSS projects, we structured and analysed generic project definitions elements. We identified seven generic project definition templates. The templates include critical-to-quality (CTQ) flowdown models and operational definitions of each CTQ. With these templates, practitioners with local knowledge of their business are able to effectively define improvement projects. This paper presents the concepts of an effective project definition

Six Sigma in small- and medium-sized enterprises: a Black Belt project in the Swedish steel industry

Many big companies around the world have solid Six Sigma infrastructures and it is easy to find in literature successful case studies. Conversely, small and medium–sized enterprises (SMEs) generally suffer lower attention in the literature. This happens because SMEs have only recently approached the methodology; they have weaker connection with the academia; or they do not rigorously pursue the frameworks. This paper is based on a Six Sigma project in a Swedish medium–sized company that produces steel tubes mainly for hydraulic applications. The project focused on the improvement of warehouse activities related to cutting processes. This Black Belt project was part of a Six Sigma education at the Chalmers University of Technology in Gothenburg. The case study offers the opportunity to discuss general and specific issues that a SME faces in the implementation of the Six Sigma methodology and it contributes to connect academic debate to practical experience in industry.

Glaciological observations in 2012 and 2013 at SIGMA-A site, Northwest Greenland（北西グリーンランド , SIGMA-Aサイトにおける 2012年, 2013年の雪氷調査）

Glaciological observations were conducted in 2012 and 2013 at the SIGMA‑A site on the northwest Greenland ice sheet (78°03�06�N 67°37�42�W 1490 m a.s.l. as part of the Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic (SIGMA project. The meteorological conditions during the two observations were quite different. The meteorological condition during the 2012 observation period was warm and heavy rainfall occurred during the observation period thus the snow was very wet. In contrast the meteorological condition during the observation period in 2013 was cold with a blowing snow event thus the snow was quite dry. The glaciological observations in 2012 consisted of 1 snow‑stake measurements 2 snow pit observations 3 grain size observations for validation of satellite‑derived snow products 4 snow specific surface area measurements using a near‑infrared camera 5 snow sampling for chemical analyses and 6 drilling of firn cores with a hand auger. The glaciological observations in 2013 consisted of 1 snow‑stake measurements 2 snow pit observations and 3 snow sampling for chemical analyses.

Lean six sigma application in reducing nonproductive time in operation theaters

Background: Non Productive Time OT causes potential loss or deferment of revenue for the hospital and internal customer dissatisfaction. The quality tool Lean Six Sigma may help to reduce the non-productive time. Aim: To use elements of a six sigma model to reduce non-productive time in Gastro Intestine Surgery OT. It focuses on the reduction of NPT between Patient In time and Induction Begin time, Induction End time and Incision In time, Patient Out time and OT Readiness Time. Method: In a five phase study using DMAIC (Define. Measure, Analyze, Implement & Control) model, business case, value analysis, brain storming, FMEA (Failure Mode & Effect Analysis), RPN (Risk Priority Number) calculation identified causes and solutions. In six sigma analysis process sigma, target sigma and achieved sigma was calculated. Results: The null hypothesis of no difference in old and new Non Productive Time between Patient In time and Induction Begin time, between Induction End time and Incision and between Patient Out Time and OT Readiness Time was rejected using 2test since the p-value was below 0.05 at 95% confidence level. The process sigma was at 0.91, 0.96 and 0.67 which got improved to 2.55, 2.22 and 3.28 which was better than target Six sigma. Overall bottom line improvement was 4.8CR for the study period by bringing efficiency in the system. Conclusion: The six sigma project in OT resulted in reducing NPTs, helping to take more cases, patient discharge becoming more systematic, and reducing chaos regarding scheduling OT cases.

Applying a Hybrid MCDM Model for Six Sigma Project Selection

Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS) is a type of multiple criteria decision making (MCDM) problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL) technique, analytic network process (ANP), and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map.

Simultaneous quantification of epistemic and aleatory uncertainty in GMPEs using Gaussian process regression

This paper presents a Bayesian non-parametric method based on Gaussian Process (GP) regression to derive ground-motion models for peak-ground parameters and response spectral ordinates. Due to its non-parametric nature there is no need to specify any fixed functional form as in parametric regression models. A GP defines a distribution over functions, which implicitly expresses the uncertainty over the underlying data generating process. An advantage of GP regression is that it is possible to capture the whole uncertainty involved in ground-motion modeling, both in terms of aleatory variability as well as epistemic uncertainty associated with the underlying functional form and data coverage. The distribution over functions is updated in a Bayesian way by computing the posterior distribution of the GP after observing ground-motion data, which in turn can be used to make predictions. The proposed GP regression models is evaluated on a subset of the RESORCE data base for the SIGMA project. The experiments show that GP models have a better generalization error than a simple parametric regression model. A visual assessment of different scenarios demonstrates that the inferred GP models are physically plausible.

Successful Implementation of Six Sigma to Schedule Student Staffing for Circulation Service Desks

In fall of 2011 the University at Buffalo Libraries circulation department undertook Six Sigma training for the purpose of overhauling its student scheduling process. The department was able to mitigate significant staffing budgetary reductions and resource reallocations and to overcome the unique challenges of scheduling student labor for a significant portion of service desk hours. This article discusses why the Six Sigma project was undertaken as well as the Six Sigma process steps and the measurement and formalization a of significant procedural change to the circulation department's student scheduling process that resulted in a highly successful outcome.

Going Forward: A Lean Way to Design

That's not what I meant. Generally speaking, this phrase does not mean the end of the world, and the affected parties can quickly come to terms and remedy the misunderstanding. In the world of design, how- ever, such a phrase can imply disaster for the designer and client, if not resolved early enough in the process of a building project. And in the history of design, this phrase is probably heard more often than many designers are willing to admit.As with many areas where inspiration evolves organically with the passing of time, the world of design and build is undergoing a renaissance. New tools and approaches, including patient-centered design, computer simulation and itera- tive data-driven design are being applied in the healthcare setting, and this issue of HERD is dedicated to examining them. In each of these thought-provoking articles, we challenge conventional approaches to design-and conventional wis- dom-and offer new techniques that promise to create more effective environ- ments in which to practice and receive care.The idea that conventional wisdom must be challenged in the world of design grew from the very successful application of Lean and Six Sigma principles in hospital operations, dating back over a decade. In 1999, nobody in healthcare had heard of these methods, and it might not be unusual to hear in the halls of the hospital is Sigma and why is she sick? Today, two separate studies, one by the American College of Healthcare Executives and the other by the Ameri- can Society for Quality, indicate that over 40% of hospitals have applied Lean and Six Sigma to improve quality and reduce costs.My own experience with these methods has been consistent with industry. In 2000, I earned a Blackbelt in Six Sigma and went about helping hospitals to realize their full potential in operational, workflow and quality changes. Unfor- tunately, even the smallest amount of data can be intoxicating to managers, who are often quick to conclude that they understand the root cause of performance problems. Executives were absolutely convinced they knew how to improve pro- cesses and many initiated performance improvement efforts with a solution in mind. The industry became replete with examples of performance improvement efforts that actually had a deleterious effect because they were based on flawed data. It would take another several years before the industry realized that for data-driven design to work, it must demand accurate data, patience, and the ability to surrender to the process of discovery before rushing to solutions.Fortunately, such patience has paid off. In a study conducted by Creative Health- care including over 150 projects conducted by 10 healthcare systems over the past 10 years, Six Sigma projects were shown to yield an average return on invest- ment (ROI) of 7:1. With this compelling evidence to embolden us, it's time to take these methods as far as they can go.How does one begin the process of undertaking a Lean or Six Sigma journey in an environment where such concepts are potentially new and unproven? A research paper offered by Maartje van Reedt Dortland et al. in this issue of HERD discusses the findings from an exploratory survey with options for con- struction that facilitate understanding of the contemporary view of available options, while another research paper by Vanessa Okken et al. …

Applications of Lean Six Sigma in an Irish hospital

Purpose – The purpose of this paper is to present a case study of the implementation of Lean Six Sigma techniques through a series of student projects carried out in a hospital setting. Design/methodology/approach – The five projects were carried out by teams of Masters' students taking a module on operations and quality management. The students were all staff members of the hospital. The study analysed each of the five projects under a number of headings: setting and context, approach, key success factors, benefits and lessons learnt. The projects were then examined to identify patterns among the projects. Findings – All student projects adopted a single foundation methodology as the basis for the project, but supported this with additional techniques from the Lean Six Sigma stable. The primary methodology was Lean in the case of three projects, Six Sigma in the case of one project and mistake proofing in the case of the final project. The most commonly used supporting techniques were process mapping, seven wastes, 5S and logic tree/root cause which were each used in two of the five projects. Other techniques used were control charts, checklists and theory of constraints, which were each used by one project team. Support from top management and regular communication with stakeholders were identified as key factors for success by three of the five project teams. All of the projects, although implemented during a time period of less than three months, and by relatively novice users of Lean Six Sigma techniques, yielded practical benefit to the hospital. Research limitations/implications – This paper examines a number of Lean Six Sigma projects carried out in an Irish hospital. Students were tasked to examine and improve the efficiency and effectiveness of a clinical or/and an administrative process within the hospital. Arguably, a single module on a Master's program in healthcare leadership and organisational change is insufficient to bring about large-scale process change in a single hospital in particular, or to the Irish healthcare sector in general, but it is a start, and as these projects demonstrate it provides a set of tools, techniques and effective methods for instigating process change. Practical implications – Lean Six Sigma offer a variety of methodologies and techniques for use on a process improvement project. It is vital that the project team select for use those techniques which are most appropriate to the particular context of the project. Adoption of an overall methodology (philosophy) supported by specific techniques, proved to be an effective approach. Originality/value – This paper provides useful information for practitioners who are introducing the Lean Six Sigma approach into a hospital setting. The study demonstrates that relatively novice users of Lean Six Sigma can provide value to the organisation in a relatively short period of time. The paper also demonstrates that Lean Six Sigma can be used and provide benefit in a variety of settings within a hospital.

Lean Six Sigma and Leadership

“These are not ‘bottom-up’ programs: The CEO must own it.” Jack Welch.When organizations decide to implement a Lean Six Sigma (or “Six Sigma”) initiative, there are several fundamentals required for a successful rollout. Leadership is paramount. From executive level support to assigning champions and choosing the right projects, leadership is critical for a successful Six Sigma implementation. The aspects of leadership is unique to Six Sigma include symbolic actions such as employees going through Green Belt training, or devoting five hours per week to involvement in Six Sigma projects with the responsible Black Belt present, or being the Champion of a major project, or putting Six Sigma as the first topic on every meeting’s agenda. Leadership training can help each executive determine what symbolic actions are congruent with his or her style. Symbolic actions often become part of the organization’s myths, which can have a powerful effect. In a broader context, coaching the executive team to recognize and improve leadership quality is the first step in the process of developing effective leaders. In this paper I will examine leader’s six personal qualities and their decisions that will lead to significantly better results for Six Sigma and other improvement initiatives: 1. Good Communicator; 2. Forward-looking, Proactive Visionary; 3. Good Motivator/Inspirational; 4. High Moral Standards; 5. Competent in the Business; 6. Imaginative and Creative.Organizations pursue process improvements such as Six Sigma for different reasons, and being clear about what to expect from the effort is crucial for any leader to be able to make the decisions about how to implement it. If the C-suites truly want the benefits of organizational transformation, then they need a method to measure themselves. The concept is that the C-suites, of course, need to lead by “walking the talk.”

Evaluating Management Consultants for Six Sigma Projects

This paper aims at evaluating the performance of management consultants for Six Sigma projects in service and manufacturing industries. An activity model is proposed for implementing Six Sigma projects. Four inputs (consultant fee, time spent, top management supported, and degree of difficulty) and two outputs (perceived satisfaction and financial performance) from a survey study by firms in Taiwan are used to estimate efficiency using data envelopment analysis. Four hypotheses: type of industry, company size, primary business activity and type of consultant are identified by soft systems methodology. We use a truncated regression model to investigate the relationship between efficiency scores and the variable of interest. Results support the larger organizations with more efficient implementations and the local management consultants with more efficient implementations. However, primary business activity and the type of industry are not significantly related to the efficiency of the Six Sigma project implementation.

Fast Initial Response Control Charts For Accounting Activities

Although Six Sigma was developed to improve processes in a manufacturing environment, its use has expanded to many other areas including accounting and finance. We propose that control charts, originally used as tools for monitoring short-run manufacturing processes, can be effectively used in the Control Stage of Six Sigma projects designed to improve accounting processes with sparse data. We describe four of these control charts: (1) pre-control charts; (2) Shewhart control charts with dramatically reduced average run lengths (ARLs); (3) Cumulative Sum (CUSUM) control charts with fast initial response (FIR) enhancements; and (4) Exponentially Weighted Moving Averages (EWMA) control charts with FIR enhancements. We provide examples of FIR enhancements to CUSUM and EWMA control charts that can result in quicker detection of small shifts in the mean of accounting data.

Investigating the Influence of Six Sigma Implementation in Khorasan Steel Plant in Year 2011

The purpose of this empirical research is to investigate the influence of implementation Six Sigma project in commodity management unit in Khorasan steel plant in year 2011 to explore the main reasons of the defects in determining the purchase orders amount and inventory control to generate the improvement in the processes and also the profitability through decreasing the defects in the purchase orders amount and inventory control. The researchers regarding the requirement of an assessment in commodity management unit after establishing management information system, decided to scrutinize the unit and tried for implementing Six Sigma quality improvement project and applying five stages of Six Sigma (DMAIC) and its techniques such as Project Prism, SIPOC Chart, Failure Mode and Effect Analysis (FMEA), Workflow Chart, Fishbone Chart or Cause and Effect Analysis, Histogram, Process Capability ratio (CPK) and using tools like Minitab and Sigma Calculator, examining the Sigma level for finding the reasons of the defects in determining the purchase orders amount and inventory control. Finally, the critical points that have significant effects on decreasing the deviation in the process were found and solutions for improving the process and decreasing the defects for commodity management unit of khorasan steel plant were provided.

The Process to Estimate Economical Benefits of Six Sigma Projects

This paper seeks to define the process for the continuous evaluation of the financial benefits during Six Sigma project life time. The financial criteria are critical success factors of a Six Sigma project. The process has been developed as part of the six sigma project monitoring in order to estimate proper allocation of the resources taking in account the expected project benefits as well as evaluationof real achievements. The evaluation of the finacial benefits based on the quality costs is not sufficient in the real life and has to be accomplished with key financial performance indicators of the business to visualize the results. The evaluation based on the savings seems to be too difficult especially for green belts. The early involvement of the finance department in the project definition as well as ongoing evaluation is key. The defined process has been applied to real business enviroment.

Improving laboratory data entry quality using Six Sigma

The Uganda Makerere University provides clinical laboratory support to over 70 clients in Uganda. With increased volume, manual data entry errors have steadily increased, prompting laboratory managers to employ the Six Sigma method to evaluate and reduce their problems. The purpose of this paper is to describe how laboratory data entry quality was improved by using Six Sigma. The Six Sigma Quality Improvement (QI) project team followed a sequence of steps, starting with defining project goals, measuring data entry errors to assess current performance, analyzing data and determining data-entry error root causes. Finally the team implemented changes and control measures to address the root causes and to maintain improvements. Establishing the Six Sigma project required considerable resources and maintaining the gains requires additional personnel time and dedicated resources. After initiating the Six Sigma project, there was a 60.5 percent reduction in data entry errors from 423 errors a month (i.e. 4.34 Six Sigma) in the first month, down to an average 166 errors/month (i.e. 4.65 Six Sigma) over 12 months. The team estimated the average cost of identifying and fixing a data entry error to be $16.25 per error. Thus, reducing errors by an average of 257 errors per month over one year has saved the laboratory an estimated $50,115 a year. The Six Sigma QI project provides a replicable framework for Ugandan laboratory staff and other resource-limited organizations to promote quality environment. Laboratory staff can deliver excellent care at a lower cost, by applying QI principles. This innovative QI method of reducing data entry errors in medical laboratories may improve the clinical workflow processes and make cost savings across the health care continuum.

Translating 10 Lessons From Lean Six Sigma Project in Paper-Based Training Site to Electronic Health Record–Based Primary Care Practice

Lean Six Sigma is a well-proven methodology to enhance the performance of any business, including health care. The strategy focuses on cutting out waste and variation from the processes to improve the value and efficiency of work. This article walks through the journey of "green belt" training using a Lean Six Sigma approach and the implementation of a process improvement project that focused on wait time for patients to be examined in an urban academic primary care clinic without requiring added resources. Experiences of the training and the project at an urban paper-based satellite clinic have informed the planning efforts of a data and performance team, including implementing a 15-minute nurse "pre-visit" at primary care sites of an accountable care organization.

Measuring efficiency of lean six sigma project implementation using data envelopment analysis at Nasa

Purpose: This study aims to review the implementation of the Lean Six Sigma project methodology in the Johnson Space Center (JSC) business environment of National Aeronautics and Space Administration (NASA) with an objective of evaluating performance of individual projects and to develop recommendation for strategies to improve operational efficiencies based on Data Envelopment Analysis (DEA). Design/methodology/approach: In this study, authors propose the Lean Six Sigma project performance evaluation model (LSS-PPEM) based on Data DEA where Critical Success Factors (CSFs) and Total Team Hours serve as inputs while Process Sigma and Cost avoidance are used as outputs. The CSFs are factors that critically affect the performance of LSS at JSC. Six of those are identified by the Black Belts through Analytical Hierarchical Process, and the values of those are decided by project leaders and Green Belts through survey. Eighteen LSS projects are evaluated, and their results are analyzed. Findings and Originality/value: Eventually, four out of the six CSFs are adopted for this study based upon Pearson correlation analysis, and those four include Project execution and follow up of results; Top management’s commitment and participation; The use of data analysis with easily obtainable data; Attention given to both long and short term targets. Using data between the years 2009 and 2011, seven of the eighteen projects are found to be efficient. The benchmark analysis and slack analysis are conducted to provide further recommendation for JSC managers. Three out of those seven efficient projects are most frequently used as an efficient peer. Practical implications: Traditionally, DEA has been considered as a data-driven approach. In this study, authors incorporate the survey-based CSFs into the DEA frame. Since many organizations may have different CSFs, the framework presented in this study can be easily applied to other organizations. Originality/value: This study provides a DEA-based framework and case study of LSS project evaluation in the government sector, which is very unique application to author’s best knowledge. The framework is unique in terms of its input factor selection and quantification procedures.