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This study aims to demonstrate the application of Lean Six Sigma (LSS) at a stainless steel manufacturer in Türkiye for yield improvement.

A qualitative approach consisting of a single descriptive case study was adopted. Both primary and secondary sources were used. The interviews were conducted with the Six Sigma team. In addition, an in-depth review of the project documents was conducted. The “define, measure, analyze, improve and control (DMAIC)” phases were explained by examining the tables, facts and figures. The company’s downgraded rate owing to defective materials was 0.21%. Root causes were detected in the tension unit, carpet cleaning, coating unit, film surface and cleaning of the rolls. Therefore, improvements were taken accordingly.

The rolled throughput yield was 99.05%, and the defect rate was reduced to 0.08% after implementing LSS, which provided statistically proven results and a direct reflection on customer satisfaction.

To the best of the author’s knowledge, this is the first case study examining the application of LSS to improve the yield of a medium-sized stainless steel company in Türkiye.

Success and business reputation depend upon the quality of products where product quality depends upon the capability of a process, yield value and sigma score, etc. Poor quality of ceiling fan and mass rejection from quality check resulted in an alarming amount of cost for rework. As a result, the fulfillment of the production target was getting difficult day by day. The main purpose of this research is to identify the crucial causes for humming noise of ceiling fans and control it to a tolerable level so that maximum quality can be achieved.

The poor quality of ceiling fans was determined from the Pareto analysis of the define, measure, analyze, improve and control model which was humming noise during running and further actions were undertaken regarding the reduction of the humming noise. Project charter was formed before initiating the measure phase to study the suppliers, inputs, processes, outputs and customers diagram with process parameters and existing noise data were collected from random samples to determine the rolled throughput yield (94.95% existing) and existing sigma score which value of 3.14 and also the poor value (1.05) of process potential index implied that the process condition was below standard (<1.33) and need to be improved badly. Then root causes analysis and relationship diagram was prepared to identify the possible causes and with the design of experiments and correlation analysis, it was clear that the air gap between the stator and rotor was the main culprit behind the humming noise.

The minimum value of air gap was determined from boxplot analysis which was 0.2 mm–0.225 mm and the corresponding mean, the minimum and maximum value of sound level in dB (37.5–40.3 dB) for 0.225 mm air gap with the watt consumption (83 w) from the hypothesis test for the corresponding air gap. Finally, the updated sigma score and process capability analysis were performed with control charts to show the comparison after applying the DMAIC-six sigma methodology. The final sigma score was 5.1 which indicates a significant improvement of the process with the capability of saving US$23,438/year caused by the poor quality of ceiling fans.

Only quantitative values of the causes behind the humming noise were possible to identify. Other trivial many causes elimination might improve the sigma score closer to 6.00. The final sigma score that was achieved from this research was sustainable.

A structural approach with proper data analysis and application of various tools to detect the actual cause behind the humming noise of ceiling fans with numerical value has not been found in any literature. This research study can be a valuable asset for ceiling fan mass producers.

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 improve the yield of a particular model of a car windshield, as the organization faces losses due to poor performance and rejection.

The Six Sigma DMAIC (define, measure, analyze, improve and control) methodology is used to reduce variation and defects in the process. It is a methodology based on data-driven and fact-based analysis to find out the root cause of the problem with the help of statistical analysis. A worst performing model is selected as a case study through the scoping tree. The preprocess, printing, bending and layup process defects are reduced by analyzing the potential causes and hypothesis testing.

This paper describes Six Sigma methodology in a glass manufacturing industry in India for automotive applications. The overall yield of a car windshield achieved 93.57 percent against the historical yield of 88.4 percent, resulting in saving 50 lacs per annum. Due to no rework or repairing in the glass, low first-time yield causes major losses. Process improvement through focused cross-functional team reduces variation in the process. Six Sigma improves profitability and reduces defects in the automotive glass manufacturing process.

This case study is applied in automotive glass manufacturing industries. For service and healthcare industries, a similar type of study can be performed. Further research on the common type of processor industry would be valuable.

The case study can be used as a problem-solving methodology in manufacturing and service industries. The tools and techniques can be used in other manufacturing processes also. This paper is useful for industries, researchers and academics for understanding Six Sigma methodology and its practical implementation.

This case study is an attempt to solve automobile glass manufacturing problems through DMAIC approach. The paper is a real case study showing benefits of Six Sigma implementation in the manufacturing industry and saving an annual cost of 50 lacs due to rejections in the process.

This paper aims to demonstrate how the five phases of design for six sigma approach as defined by define-measure-analyse-design-validate (DMADV) are adopted towards the development of an optoelectronic product to address the unexplored development issues related to micron-scale tolerances of internal diameters in plastic moulded parts. In addition, the structured product development approach is used to address the critical-to-quality (CTQ) characteristics that define the quality of the final product.

In line with DMADV, the presented methodology used various tools at each development stage to address key requirements of critical concern in the project. This included the ideal use of computer-aided design (CAD) simulation tool to identify CTQ parameters, failure mode effect analysis as a predictive tool to identify the major defects, while adopting root-cause-analysis to identify the fundamental causes of the major defects, design of experiment, and statistical analysis using Minitab Software for data-driven decision-making.

The two major defects that hindered the mass production of quality products were eliminated, and the overall development of the product significantly improved. Additionally, a quality control strategy approach was implemented to “lock in” the quality.

The case study presented develops and adopts a structured approach from DMADV with the key focus of addressing a micron-scale tolerance conflict between the design and manufacturing tolerance requirements of an optoelectronic product. The uniqueness of the case study is the adoption and application of CAD simulation at the Define phase of the DMADV process to address the CTQ issue of the product developed.

Continued quest for business improvement in terms of enhanced productivity and cost cuts is the most valued strategic function in an organization. Towards this endeavor, there have been evolutions of many problem-solving techniques like Lean, quality control (QC) tools, Six Sigma, total productive maintenance (TPM), etc. This paper introduces a different problem-solving methodology for quality improvement – prepare, measure, define, establish, control and stabilize (PMDECS) approach of Red Bin Analysis (RBA) – and presents empirical evidence of its effectiveness in eliminating the defectives at source (parts per million [PPM]) and improving the process capability (Cp).

An attempt has been made to compare RBA with the Six Sigma methodology in terms of number of defects, defectives, process capabilities, project duration, etc. Data validation with more than 2000 data points was conducted based on empirical data collected over multiple problem-solving projects conducted in six manufacturing industries of India to compare the effectiveness of both the methods. Finally, fuzzy AHP (analytical hierarchy process) model was proposed to identify the Quality Improvement Index for both the methods to address the manager’s dilemma in selecting an appropriate problem-solving method.

The paper provides empirical insights in establishing that the PMDECS approach of RBA is at par and sometimes better for problem-solving if the problem is not chronic and is at the initial stages, it requires less duration than Six Sigma projects and except casting process and it can yield better results in case of PPM rejection or Cp/Cpk improvement in other processes.

Because of the chosen research approach, the research results may lack generalizability. This research has been specifically conducted in automotive manufacturing industries. Therefore, researchers are encouraged to test the proposed propositions further.

The paper includes implications for the usage of alternative problem-solving methods, like PMDECS approach of RBA.

This paper intends to compare how the results of six sigma projects in manufacturing industries are effective against a different methodology, PMDECS approach of RBA.

Point-of-care testing (POCT) at the Emergency Department (ED) attains better objectives in patient care while aiming to achieve early diagnosis for faster medical decision-making. This study assesses and compares the benefits of POCT in the ED in Germany and Malta, while considering differences in their health systems.

This chapter utilizes multiple case study approach using Six Sigma. The German case study assesses the use of POCT in acute coronary syndrome patients, compared to the central lab setting. The Maltese case study is a pilot study of the use of medical ultrasonography as a POCT to detect abdominal free fluid in post-blunt trauma.

This study provides clear examples of the effectiveness of POCT in life-threatening conditions, as compared to the use of traditional central lab or the medical imaging department. Therapeutic quality in the ED and patient outcomes directly depend upon turnaround time, particularly for life-threatening conditions. Faster turnaround time not only saves lives but reduces morbidity, which in the long-term is a critical cost driver for hospitals.

The application of Six Sigma and the international comparison of POCT as best practice for life-threatening conditions in the ED.

The purpose of this paper is, first, to utilize institutional theory to assess motivation for the adoption of Six Sigma. Second, to examine the role of an organization's innovation implementation climate and the fit between the innovation considered and the values of the organization's members on the implementation of Six Sigma. Third, to study the impact that the adoption and implementation of Six Sigma has on organizational performance.

Methods advocated in case study research were employed in the conduct of seven case studies. The research protocol consisted of identifying organizations in a variety of manufacturing industries, and conducting focused interviews with a minimum of three respondents in each company in order to improve validity.

This paper suggests that institutional theory proves to be an effective means by which to examine the adoption of Six Sigma. In addition, support for innovation implementation model suggested by Klein and Sorra is found. Each of the studied firms reported performance improvements as a result of the adoption and implementation of Six Sigma.

This paper contributes to a better understanding of Six Sigma adoption, implementation, and implementation effectiveness of Six Sigma by exploring how it is applied in different manufacturing contexts.

This paper aims to apply the Six Sigma methodology to improve workflow by eliminating the causes of failure in the medical imaging department of a private Turkish hospital.

Implementation of the design, measure, analyse, improve and control (DMAIC) improvement cycle, workflow chart, fishbone diagrams and Pareto charts were employed, together with rigorous data collection in the department. The identification of root causes of repeat sessions and delays was followed by failure, mode and effect analysis, hazard analysis and decision tree analysis.

The most frequent causes of failure were malfunction of the RIS/PACS system and improper positioning of patients. Subsequent to extensive training of professionals, the sigma level was increased from 3.5 to 4.2.

The data were collected over only four months.

Six Sigma's data measurement and process improvement methodology is the impetus for health care organisations to rethink their workflow and reduce malpractice. It involves measuring, recording and reporting data on a regular basis. This enables the administration to monitor workflow continuously.

The improvements in the workflow under study, made by determining the failures and potential risks associated with radiologic care, will have a positive impact on society in terms of patient safety. Having eliminated repeat examinations, the risk of being exposed to more radiation was also minimised.

This paper supports the need to apply Six Sigma and present an evaluation of the process in an imaging department.

Six Sigma is a business strategy and a systematic methodology, use of which leads to breakthrough in profitability through quantum gains in product/service quality, customer satisfaction and productivity. The concept of implementing Six Sigma processes was pioneered at Motorola in the 1980s and the objective was to reduce the number of defects to as low as 3.4 parts per million opportunities. For the effective implementation of Six Sigma projects in organisations, one must understand the critical success factors that will make the application successful. This paper presents the key ingredients, which are essential for Six Sigma implementation. These ingredients are generated from a pilot survey conducted in the UK manufacturing and service organisations.