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Sigma Ratings is a new entrant to the anti-money laundering (AML) marketplace and seeks to alleviate some of the inherent flaws within the AML regime. This paper aims to examine those flaws and ask whether Sigma may succeed in this bourgeoning marketplace.

This paper is based upon a normative methodology, which takes place after reviewing the relevant literature to examine the potential success for Sigma Ratings.

The paper finds that there is indeed a position for Sigma Ratings in the marketplace, and that it may alleviate key issues within the AML regime.

The paper presents Sigma Ratings to the literature for the first time and positions this against an examination of the role of banks within AML – Sigma’s main demographic.

Six sigma is a way to measure the probability of manufacturing a product or creating a service with zero defects. Presents a case study to illustrate how the concept of zero defects, measured by six sigma, can be applied to customer satisfaction measurement and to examine the impact of customer expectations on the company’s strategies for improving satisfaction. The information presented is based on actual studies conducted for a high‐tech manufacturing company in the USA during 1991 and 1992. The performance and expectations values and some of the attributes have been altered for reasons of confidentiality.

The purpose of the study is to measure the current or baseline institutional performance level of the Government and private engineering colleges in the state of West Bengal.

The study has been conducted on the basis of a survey. The feedback for this survey questionnaire has been considered independently for service providers such as administrators, faculties, other supporting staff as well as students who receive these services and are direct customers. A total of 2,168 persons have been surveyed from the 30 randomly selected colleges out of 70 colleges. The baseline or current performance level of the engineering colleges has been assessed based on the sigma level through quantification of the survey questionnaire consisting of eight enablers. Each enabler contains several questions or drivers. A total of 75 drivers have been arrived at for eight enablers. A seven‐point scale has been designed for each driver ranging from “Unsatisfactory” to “Outstanding”. To identify the weak areas for a college, the vital few drivers that correspond to “Unsatisfactory” performance have been made to take necessary remedial measures for attaining the new benchmark sigma level under the present techno‐economic set‐up.

The overall ratings (sigma levels) of engineering colleges in West Bengal range from 0.11 to 2.7, which is far away from the sigma level (4σ) of an average organization in the USA.

The paper is a purely original work. Instead of going by the popular perception of the Selection, Engineering and Technology, West Bengal, it is much better to categorize the colleges based on the class intervals of baseline sigma levels as demonstrated.

The purpose of this paper is to investigate the application of lean construction practices in the construction industry and develop a practical and applicable framework that incorporates Six Sigma rating into the best practices of lean construction. The objective is to help the industry reduce waste and cost, increase effectiveness, and improve quality.

A generic yet practical framework of lean construction is developed using the guidelines of project lean delivery system developed by the Lean Construction Institute (LCI). Applicable lean techniques and Six Sigma rating are integrated into the developed framework. A cyclical look‐ahead planning and execution approach is used to implement the lean construction techniques. A set of Lean Six Sigma (LSS) performance indicators is defined to measure performance, set target threshold values, and guide improvement actions. A case study of the construction industry in Abu Dhabi (AD) is used to clarify the proposed approach and identify its key practical aspects.

Analysis of wastes in AD construction industry reveals 27 types of construction wastes. These wastes were categorized into the seven types of wastes. Defects (errors and corrections) are found to be the most common type of construction waste in the surveyed companies. This calls for integrating Six Sigma rating into the proposed lean construction framework. The other common types of wastes are overprocessing and delays. Lean project management is focused on assessing a set of key performance indictors (KPIs) at the end of each “look‐ahead” period. First lean practices are employed during the period and Sigma Rating is assessed at the end of the period along with other KPIs. The proposed LSS‐KPIs were able to measure progress and guide improvement.

The credibility of the research findings is dependent on the accuracy and reliability of collected data from construction companies. Implementing lean construction techniques within a look‐ahead period is not expected to achieve significant project gains in terms of quality, speed, and cost without adopting the overall lean construction framework.

The work of construction companies largely contributes to the quality and safety of public and society at large through residential and commercial buildings, transportation, and infrastructure projects. Lean construction practices and Six Sigma rating positively impact these important aspects and often result in reducing waste and costs, improving safety, and saving energy resources in construction projects.

Research significance stems from the focus on increasing the effectiveness of the construction industry. Research contributions include the development of an applicable lean construction framework that integrates lean construction practices with Six Sigma rating. This contributes to the effort of applying Lean Six Sigma (LSS) in the vital field of construction. This research prescribes a systematic approach for implementing the proposed framework within a cyclical look‐ahead period and highlights the practical implications of the proposed approach. Also, the research provides an effective periodic measurement system of project effectiveness based on five LSS key performance indices.

This paper examined employee perceptions of the rewards associated with their participation in a six sigma program. Six sigma is an approach to organizational change that incorporates elements of total quality management, business process reengineering, and employee involvement.

A survey was completed by 215 employees (34 percent response rate). Respondents rated the extent to which they felt their participation in six sigma was “instrumental” for a range of outcomes, as well as valence (desirability) of each outcome (based on the VIE concept of instrumentality). The outcomes were classified into four categories: extrinsic, intrinsic, social, and organizational.

Valence ratings revealed that all 12 outcomes were perceived as desirable. Instrumentality ratings showed that extrinsic outcomes were rated significantly lower than intrinsic, social, and organizational outcomes. Additional analyses revealed significant differences on all four outcome categories between participants and non‐participants in the six sigma program.

The positive valence and instrumentality ratings for participants indicate they believe their participation will lead to valued outcomes for themselves and their organizations. However, employees who choose not to get involved in six sigma do not perceive that their participation would have led to desired outcomes. The results also show that while participants value extrinsic rewards, they do not see six sigma as instrumental in their receipt. These perceptions have important implications for attracting and retaining program participants.

While much has been written about the use of reward systems in supporting a successful six sigma effort, this study empirically examines how employees actually perceive the rewards associated with their participation. It also identifies which types of rewards are most instrumental for participants and non‐participants.

This research aims to enhance the operational excellence and continuous improvement of the retail supply chain in the Saudi Thobe Factory through an integrated approach of Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) with artificial intelligence (AI).

The study identified the tailoring department as the department with maximum defects by using voice of customer and critical to quality tools. An AI-integrated Six Sigma approach was applied to identify and eliminate nonproductive stages, and a new facility layout was designed to enhance productivity and customer satisfaction.

The use of the factor rating method and simulation using Arena software led to an improved sigma level from 1.597 to 2.237, representing an increment of about 40%. Additionally, the defects per million opportunities reduced from 461,538 to 230,769. The study can help production industry management to optimize facility layouts and improve overall production line efficiency.

This study addresses the lack of published research on the use of an integrated approach of Six Sigma DMAIC with AI in the retail and distribution sector of Saudi Arabia, particularly for small and medium-sized enterprises (SMEs). The study demonstrates how this approach may significantly boost SMEs’ performance and provides a basis for future research in this area.

This study provides a practical example of how an integrated approach of Six Sigma DMAIC with AI can be used in the retail and distribution sector of Saudi Arabia to enhance operational excellence and continuous improvement. The study highlights the potential benefits of this approach for SMEs in the region and provides a framework for future research.

The purpose of this paper is to develop a simulation-based value function (VF) that combines multiple key performance indicators (KPIs) into a unified Sigma rating (SR) for system-level performance assessment and improvement.

Simulation is used as a platform for assessing the multiple KPIs at the system level. A simple additive VF is formed to combine the KPIs into a unified SR using the analytical hierarchy process and the entropy method. Value mapping is utilized to resolve the conflict among KPIs and generate a unified value. These methods are integrated into the standard Six Sigma define-measure-analyze-improve-control (DMAIC) process.

Simulation results provided the Six Sigma DMAIC process with system-level performance measurement and analysis based on multiple KPIs. The developed VF successfully generated unified SRs that were used to assess various performance improvement plans.

The accuracy and credibility of the results obtained from using the proposed VF are highly dependent on the availability of pertinent data and the accuracy of the developed simulation model.

The proposed approach provides Six Sigma practitioners and performance mangers with a mechanism to assess and improve the performance of production and service system based on multiple KPIs when conducting Six Sigma studies.

This paper contributes to the previous research by handling multiple KPIs in Six Sigma studies conducted at the system level using simulation and VF. The research also provides guidelines for using the different methods of weights assessment to form the VF within the DMAIC process.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

The aim of this paper is to highlight the application of six sigma, software engineering techniques and simulation to software development with a view to improving the software process and product.

This paper attempts to integrate six sigma and simulation to define, analyse, measure and predict various elements of software development (such as cost, schedule, defects) that influence software quality, thereby helping the software personnel take necessary measures early in the development process to improve the software processes and remove defects. Simulation results provide qualitative and quantitative suggestions on the ways to change the software process to achieve six sigma quality. The integration of six sigma and CMM and the role of knowledge management in software organisations have been taken into account.

Most software organisations operate between 2.3 and 3 sigma level. This paper presents a framework for definition, measurement, and analysis of important elements of the software product and process using six sigma tools and exploits the use of simulation in bringing six sigma improvements. Case studies have been presented to demonstrate the findings.

Application of the techniques presented in this paper would definitely improve software organisations' processes and product.

The adoption of methodologies outlined in this paper in software companies would enable them to attain improvements in terms of cost, schedule and quality.

The integration of simulation with six sigma applied to software development is novel in this paper. This paper will be valuable for quality professionals and management personnel in software organisations.

The purpose of this paper is to provide Lean Six Sigma deployment champions with a structured approach to identify and prioritize parts of their business that are conducive to the Lean Six Sigma methodology.

A five‐step approach to Lean Six Sigma project identification is presented in this paper. The approach utilizes a clustering technique to group similar processes based on seven process characteristics. The clusters formed are then evaluated and prioritized for their compatibility to Lean Six Sigma.

The clustering approach can be applied to any industry segment, including non‐manufacturing, healthcare and financial‐based organizations. A case study is presented in this paper in which the approach is applied to an IT based company. A total of 30 percent of the business processes were found to be Lean Six Sigma conducive.

The current model does not have provision to consider the current performance of a process as an evaluation criterion. This requires the deployment champion to use the model in conjunction with a Balanced Scorecard. Future research will address this limitation.

There is a general lack of a mathematical approach to enable Lean Six Sigma practitioners to identify parts of their business that are conducive to the methodology. This research attempts to bridge this gap in the literature by using an unsupervised learning approach, using a clustering algorithm, to group processes based on seven process characteristics. The cluster evaluation helps the deployment champion identify key areas within the business to focus an LSS deployment.