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Face the process yield rate improvements of motherboard, although general enterprises finish deployment goal of each functions by overall quality managements, through quality improvement methods, industry engineering methods, plan‐do‐check‐act (PDCA) methods and other improvement solutions, but it is only can be improved partially and unable to enhance the yield rate of product to the target. It only can takes one step ahead to enhance the process yield rate of motherboard with six sigma (6 σ) overall DMAIC process and tactics. This research aimed to use six sigma quality improvement tactics by DMAIC systematic procedure and tactics, and find the key factors that effect to the process yield rate of surface mount technology. It also identified the keys input and process and output index to satisfy customer requirements and internal process index. The results showed that the major effective factors by fishbone and process failure modes and effects analysis (PFMEA). If the index of input and output that can be quantified, the optimum parameter can be found through design of experiment to ensure that the process is stable. If the factor of input and output that cannot be quantified, we found out the effective countermeasure by Mind_Mapping, make sure whole processes can be controlled stably, to reach the high product quality and enhance the customer satisfaction.

This paper aims to bring together the concepts of Six Sigma into the process of training design and training transfer.

The concepts of the paper are supported with an actual example of their application to practice. The industrial example shows where the inclusion of the concepts of Six Sigma can make positive contributions to the design and transfer of training processes.

The application of the concepts to training design and transfer showed a positive contribution through a more structured process. Including the concepts of Six Sigma within the process of training design and transfer will provide the organization with additional support and structure to improve the overall success of the training design process, and improve the impact and effectiveness of the training itself.

The single example of application may limit the successfulness of the overall concept to training design overall. Based on the successful application in one industrial training setting, the impression that the concepts will adequately translate to additional applications is favorable.

The success of the application shown in this paper suggests that further success is likely in other similar industrial applications. Expanding the application to other job training design processes should improve the overall process of training design in other areas and industries.

Training design and transfer are critical components to all areas of an organization that conducts any type of training. Application of these and other improvement methods and tools will improve the overall performance of the training process and the effectiveness of the training.

The purpose of this paper is to describe the historical approach to concurrent engineering (CE) which has resulted in product line management (PLM) and then evaluates the theoretical models that have been proposed for design for Six Sigma (DFSS) in order to determine which model is able to provide the most consistent approach with historical development of PLM.

The approach begins with an overview of the approach taken by the Union of Japanese Scientists and Engineers (JUSE) in the development of a coherent quality methodology for structured analysis and problem solving – the Deming Wheel of plan‐do‐check‐act (PDCA) which has become the standard model in Japanese total quality management to define a logical decomposition in process management. In Japan, PDCA is the single logical model which has been broadly accepted as the construct for understanding how to develop both strategic and operational quality methods. The second step in the approach is to examine a similar American development of the model for statistical problem solving that is applied in the Six Sigma method for statistical problem solving: define‐measure‐analyze‐improve‐control (DMAIC). Next, the paper examines the historical sequence in the way the product development process has developed over the past forty years, with emphasis on its military origins (especially CE) and which resulted in the generic model for PLM. The final part of this paper examines the models that have been proposed to implement DFSS over the past ten years and evaluate their logical congruence with the engineering community's design process.

Problems in alignment with the engineering design process were identified with all of the DFSS models and with the non‐structured or “heuristic” approach to developing a coherent body of knowledge related to DFSS.

This paper provides a challenge to the quality community as well as to the academic community. The paper points out the need for rigorous examination of logical models that are proposed for guiding the thinking of practitioners in the use of quality methods for both the engineering of products and business systems. An expose of lack of rationality in the way an approach to DFSS has been investigated calls for more responsibility in the management of the development of this body of knowledge.

Six Sigma is a well-established powerful business strategy for achieving operational excellence (OPEX). However, previous studies have suggested that the Six Sigma may negatively impact organizational creativity and innovation. The C-K theory is one of the most widely used technique for design reasoning which promotes the creativity and innovation. The purpose of this paper is to integrate the Six Sigma methodology and C-K theory for enhancing innovative capacity of Six Sigma for achieving OPEX.

The paper proposes an integration methodology of C-K theory and Six Sigma using the extant literature. Also, a case study is conducted based on the proposed integration model.

The paper suggests a step-by-step integration methodology for integrating Six Sigma with C-K theory for both (DMAIC and DMADV). The methodology when applied to a live case in mining logistics the results are very encouraging. The solution was cost effective and also technically superior compared to previous solutions.

The paper proposes a step-by-step methodology for the integration of Six Sigma with C-K tools. The methodology is practically applied in a live case. Organizations can use findings from this paper to implement an integration model of Six Sigma with C-K theory.

This is the first paper that proposes an integration methodology of Six Sigma with C-K theory to enhance the innovation capability to achieve the OPEX.

This paper is one of seven in this volume that aims to elaborate different approaches to quality improvement in education. It delineates a methodology called Six Sigma.

The paper presents the origins, theoretical foundations, core principles and a case study demonstrating an application of Six Sigma in a school-community partnership in Milwaukee, Wisconsin.

The core principles underlying the approach are decreasing variability or unreliability in organizational work processes, eliminate waste or activity that does not add value to desired outcomes, identify defects and decrease their incidence, reduce the cost of work processes, and improve beneficiary/client satisfaction levels. The steps in this statistics-dependent method are design, measure, analyze, improve and control.

Few theoretical treatments and demonstration cases are currently available on commonly used models of quality improvement that might have potential value in improving education systems internationally. This paper fills this gap by elucidating one promising approach. The paper also derives value as it permits a comparison of the Six Sigma approach with other quality improvement approaches treated in this volume.

The purpose of this paper is to develop a consistent and crystallized exposition of Six‐Sigma's methodology for improvement projects, which could serve as a basis for subsequent scientific research of the method.

The paper shows that reformulation of imprecise and unscientific formulations of knowledge is called rational reconstruction. Starting from accounts given in the Six‐Sigma literature, a descriptive reconstruction of the main elements of the Six‐Sigma method is made: its business context, strategy, tools and techniques, and concepts and classifications.

The paper finds that, although, on the face of it, it may seem that accounts given in literature diverge, analysis shows that variations are superficial rather than essential. The analyses result in precisely formulated accounts of Six‐Sigma's method (DMAIC phases, steps, and tools), its business context, and its terminology. Essential anomalies are discussed. Six‐Sigma's claims of being data‐driven and focused on customers and bottom line results appear to be substantiated by its method.

In this paper the presented reconstruction has a purely descriptive impetus: it structures accounts that the Six‐Sigma literature itself provides, without critical evaluation against theoretical frameworks beyond the Six‐Sigma literature. As such, it provides a basis that is suitable for subsequent scientific research.

The paper sees that loose and inaccurate expositions of Six‐Sigma's project methodology are supplemented with a precise formulation.

Among a tide of accounts of Six‐Sigma's DMAIC method, this paper provides an account that meets scientific standards of precision and consistency. It allows a substantiation of commonly made claims about Six‐Sigma, i.e. Six‐Sigma is a quantitative, data‐driven approach focused on cause‐and‐effect relations, and offering new solutions instead of standard cures.

The selection of right projects in a Six Sigma program is a major concern for early success and long‐term acceptance within any organization. One of the ever‐increasing challenges is to define and select right measure for improvement and appropriate problem definition. Many projects encounter the problem of no linkage with business objectives or customer needs, too large or high‐level project scope along with unclear problem and goal statement. Improperly, chosen metrics lead to sub‐optimal behavior and can lead people away from the organization's goal instead of joining them. This paper aims to propose a project selection methodology for different situations.

This research develops a model for project identification; ensuring well‐defined projects are selected having large impact on customer satisfaction or bottom line. The model is described for the situations: availability of performance data, balanced business score card implemented and no data is available.

A “top‐down approach” model is developed for project selection, since top management support for Six Sigma initiatives is absolutely critical to see tangible, significant results. The authors suggest establishing the linkage with data (either reactive or survey), otherwise through prioritization tool for project selection. Finally, factors influencing successful Six Sigma projects include management commitment; project selection and control skill, irrespective of whether this is a define, measure, analyze, improve and control or define, measure, analyze, design and validate/verify project.

This approach will help the organizations to select the specific project from multivariate organizational and customer needs. Three different methods for project selection are explained with examples and reasons for selection. Merits and demerits of each method are also highlighted.

Numerous attempts at installing Six Sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. Research has highlighted that a considerable number of corporate Six Sigma initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of CSFs on Six Sigma accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. The analysis focused on 260 completed questionnaires, and statistical methods including SEM, EFA, and CFA were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of Six Sigma (SS): (1) Competence of Belt System employees; (2) Project management skills; (3) Organizational economic capability; and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of Six Sigma’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their Six Sigma practices.

The investigation’s originality lies in its contribution to assessing critical success factors in Six Sigma deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.

The academic literature and research lines exploring the effect of quality improvement methods on environmental performance still remain in early stages. The purpose of this paper is therefore to investigate, through a systematic review of the existing academic literature, the environmental (green) impact of using quality and operations improvement methods such as Lean, Six Sigma and Lean Six Sigma. This includes the impact on energy saving and the usage of natural resources.

This study follows a systematic literature review approach through which it analyses research papers published in top 16 operations and quality management journals. No specific time frame was established, but a set of keywords were used to short-list the articles. A sample of 70 articles was finally short-listed and analysed to provide a discussion on environmental concerns related to Lean, Six Sigma and Lean Six Sigma.

The comprehensive review of short-listed articles indicates that both Lean and Six Sigma can be considered effective methods to support the conservation of resources, combat global warming and saving energy. Various scholars provide evidence of this, and as such, organisations should not only consider these methods to manage quality and improve operational performance but also meet environmental regulations. A set of research questions that demands further investigation has also been proposed based on the findings of this research.

This study is limited to a sample of 70 articles collected from top 16 operations and quality management journals. The search of journals is also limited to a set of key words (“Lean”, “Green”, “Six Sigma”, “environment”, “sustainable” and “sustainability”) used to short-list the sample size.

The study shows that organisations can consider the adoption of Lean, Six Sigma and Lean Six Sigma to meet environmental regulations, save costs and also meet quality management standards. This will contribute in helping organisations to formulate more effective and inclusive strategies which do not only consider the quality and operational dimensions but also the environmental dimension.

Literature exploring the environmental/green impact of quality management methods commonly used in industry is limited. There is also a lack of studies aiming to investigate the green impact of Lean and Six Sigma in top operations and quality management journals. The study focusing on investigating the green impact of Lean, Six Sigma and Lean Six Sigma methods altogether is also a research first of its kind.

This study aims to concentrate on quality improvement in plain yogurt production process at company A through adjusting the factors affecting the acidity of the yogurt and determining the optimal level of these factors.

Six Sigma-based framework using define-measure-analyze-improve-control (DMAIC) methodology is adopted through the application of design of experiments tool to focus on customer’s requirements to improve the quality characteristic of plain yogurt production process in dairy products manufacturing company (company A) in Iran.

The results showed that incubation time and fat percentage were significant factors on pH values of yogurt and the optimum settings for these factors were defined as 12 h for the incubation time and 1.5 per cent for the fat percentage.

This study focused solely on the plain yogurt production process in dairy products manufacturing company.

Simplicity of Six Sigma plays a leading role for enabling any dairy manufacturer to determine the problem and minimize its cause through a systematic approach.

Six Sigma has been considered to be a systematic, powerful technique to continuously improve the processes and develop the new products by using effective analytical and statistical tools and methods. This paper presents a Six Sigma-based framework using DMAIC methodology to improve the quality characteristic of plain yogurt production process in dairy products manufacturing company.

This study contributes to show a potential area in which Six Sigma DMAIC approach can promote to improve the quality of yogurt production process. This case can prompt managers of the company to apply Six Sigma method to address complicated problems in other processes, where causes particularly are not clear.