SU-E-I-35: Using Six-Sigma Methodology for Practice Quality Improvement Projects

2013 ◽  
Vol 40 (6Part5) ◽  
pp. 133-133 ◽  
Author(s):  
R Paden
Keyword(s):  
Quality Improvement ◽  
Six Sigma ◽  
Six Sigma Methodology

Modern methods of the quality improvement and their application in managing of changes in a company

2018 ◽  
Vol 4 (10) ◽  
pp. 64-72
Author(s):  
Pavol Gejdos
Keyword(s):  
Quality Improvement ◽  
Six Sigma ◽  
Business Processes ◽  
Relevant Information ◽  
Correct Choice ◽  
Sigma Level ◽  
Continuous Quality ◽  
Modern Methods ◽  
Six Sigma Methodology ◽  
A Company

This article deals about the application of the Six Sigma methodology by using modern methods in various stages of the DMAIC improvement model. The change management of business processes in terms of quality is determined by the correct choice of methods and tools for reducing discrepancies and non-productive costs. The evaluation of selected processes of furniture production through defects per million opportunities, efficiency, capability and sigma level before the change and after the change in the quality process provides relevant information for ensuring continuous quality improvement. Implementation of assessing changes in the process is a source of information for continuous improvement of process performance. Keywords: Processes, quality improvement, Six Sigma, DMAIC, changes in processes.

Applying quality improvement methodologies to decrease the time-to-activation of new clinical trials at an NCI-designated comprehensive cancer center.

2019 ◽  
Vol 37 (27_suppl) ◽  
pp. 296-296
Author(s):  
Timothy J Brown ◽  
Erin Fenske Williams ◽  
Patrice Griffith ◽  
Asal Shoushtari Rahimi ◽  
Rhonda Oilepo ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Quality Improvement ◽  
Six Sigma ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Process Map ◽  
Decision Points ◽  
Improvement Methodologies ◽  
Six Sigma Methodology ◽  
Pass Through

296 Background: Initiating a new clinical trial is burdensome and complex. The time to activate a clinical trial can directly affect the ability to provide innovative, state-of-the-art care to patients. We sought to understand the process of activating an oncology clinical trial at a matrix National Cancer Institute-designated, comprehensive cancer center. Methods: A multidisciplinary team of stakeholders within the cancer center, university, and affiliate hospitals held a retreat to map out the process of activating a clinical trial from packet receipt to enrollment of the first patient. We applied classical QI and Six Sigma methodology to determine bottlenecks and redundancies in activating a clinical trial. During this process, particular attention was paid to time to pass through each step and perceived barriers and bottlenecks were identified through group discussions. The time to activation was measured from the day the trial packet was received until the time when the trial was open for enrollment. Results: The process map identified 66 steps with 12 decision points to activate a new clinical trial. The following two steps were instituted first: 1) allow parallel scientific committee and institutional review board (IRB) review and 2) allow the clinical research coordination committee to review protocols for feasibility and university interest separate from the IRB approval process. These changes resulted in a mean time-to-activation change from 194 days at baseline to 135 days after these changes were implemented. The committee continues to track the activation time and this frame work is used to identify additional improvement steps. Conclusions: By applying quality improvement methodologies and Six Sigma principles, we were able to redesign redundant aspects of the process of activating a clinical trial at a matrix comprehensive cancer center. This was associated with a reduction of time to activation of trials. More importantly, the process map provides a framework to maintain these gains and implement further changes.

A DMAIC Six Sigma approach to quality improvement in the anodising stage of the amplifier production process

2018 ◽  
Vol 35 (9) ◽  
pp. 1868-1880 ◽  
Author(s):  
Pallavi Sharma ◽  
Suresh Chander Malik ◽  
Anshu Gupta ◽  
P.C. Jha
Keyword(s):  
Quality Improvement ◽  
Production Process ◽  
Six Sigma ◽  
Shop Floor ◽  
Manufacturing Firm ◽  
Content Type ◽  
Root Cause ◽  
Six Sigma Methodology ◽  
Six Sigma Approach ◽  
Current Reality

Purpose The purpose of this paper is to study the anodising process of a portable amplifier production process to identify and eliminate the sources of variations, in order to improve the process productivity. Design/methodology/approach The study employs the define-measure-analyse-improve-control (DMAIC) Six Sigma methodology. Within the DMAIC framework various tools of quality management such as SIPOC analysis, cause and effect diagram, current reality tree, etc., are used in different stages. Findings High rejection rate was found to be the main problem leading to lower productivity of the process. Four types of defects were identified as main cause of rejections in the baseline process. Pareto analysis resulted in detection of the top defects, which were then analysed in details to find the root cause of the problem. Further study resulted in finding improvement measures that were discussed with the management before implementation. The process is sampled again to check the improvements, and control measures were established. Practical implications The study provides a framework for implementation of DMAIC Six Sigma methodology for a manufacturing firm. The results presented are based on the data collected from the shop floor. Results and findings of the study were implemented for quality improvement of the process. Originality/value The study is based on an original research conducted with the objective of quality improvement in the anodising process of the production process. Besides presenting an approach to DMAIC Six Sigma methodology, an application of the current reality tree tool for root cause analysis is presented, a tool used limitedly in the Six Sigma studies. The tool finds its uniqueness in its ability to address problems relating multiple factors than isolated factors.

Six Sigma Methodology and Postoperative Information Reporting: A Multidisciplinary Quality Improvement Study With Interrupted Time-Series Regression

2019 ◽  
Vol 76 (4) ◽  
pp. 1048-1067
Author(s):  
Aalap C. Shah ◽  
Andrew R. Herstein ◽  
Katherine T. Flynn-O'Brien ◽  
Daniel C. Oh ◽  
Anna H. Xue ◽  
...  
Keyword(s):  
Time Series ◽  
Quality Improvement ◽  
Six Sigma ◽  
Interrupted Time Series ◽  
Time Series Regression ◽  
Information Reporting ◽  
Six Sigma Methodology

scholarly journals Histology Slide Quality Improvement Project Utilizing DMAIC principle of Six Sigma Quality Improvement Methodology

2021 ◽  
Vol 156 (Supplement_1) ◽  
pp. S111-S112
Author(s):  
Y Wang ◽  
A Loboda ◽  
M Chitsaz ◽  
S Ganesan
Keyword(s):  
Quality Improvement ◽  
Six Sigma ◽  
Business Processes ◽  
Endometrial Biopsy ◽  
Improvement Project ◽  
Histology Slide ◽  
Six Sigma Methodology ◽  
And Control

Abstract Introduction/Objective DMAIC (an acronym for Define, Measure, Analyze, Improve and Control) refers to a data- driven improvement cycle used for improving, optimizing, and stabilizing business processes and designs. Our goal was to utilize DMAIC principle of six sigma quality to improve histology slide quality. Methods/Case Report We “defined” the problem as suboptimal quality in endometrial biopsy slides (defects). Utilizing the DMAIC principle and adhering to a strict timeline, the defects found during baseline slide quality review were “measured” by linking the defects to specific histology competencies, which were addressed systematically for process improvement (PI). After PI, a follow up review (“improve” and “control” phases) was carried out to identify measurable outcomes as a testament to quality. Results (if a Case Study enter NA) During the problem “measurement” phase, the defects found in the baseline review of 175 slides were linked to four specific histology competencies (fixation, embedding, cutting, and staining). Processing was excluded as it is completely automated and standardized. Our analysis showed that 83.3 % of defects were linked to embedding (“tissue too dispersed”). As embedding competency depends on the size and nature of the tissue (e.g. mucus and blood admixed with tissue), grossing competency was also addressed along with embedding at the respective workstations. Recommendations were offered to the grosser, embedder, and cutter to reduce variables during the “improvement” phase. Follow up review was done on 196 slides. The number of defective slides decreased and the defects that linked to “tissue too dispersed” had an overall improvement of 91.3%. Once the PI is proven to be effective, in service to histotechnology personnel biannually were also offered during “control” phase. Conclusion We have demonstrated successful methods for improving histology slide quality utilizing DMAIC principle of quality improvement by six sigma methodology DMAIC principle can be creatively adapted in laboratory practice management to enhance quality.

scholarly journals Reduction in Rejection Rate of Soy Sauce Packaging via Six Sigma

2021 ◽  
Vol 22 (1) ◽  
pp. 57-70
Author(s):  
Ronald Sukwadi ◽  
Leonardus Harijanto ◽  
M.M. Wahyuni Inderawati ◽  
Po Tsang B. Huang
Keyword(s):  
Quality Improvement ◽  
Six Sigma ◽  
Rejection Rate ◽  
Soy Sauce ◽  
Control Plan ◽  
Maintenance Schedule ◽  
Sigma Level ◽  
Fishbone Diagram ◽  
Cutting Error ◽  
Six Sigma Methodology

The Six Sigma methodology is the most powerful quality improvement technique. This research deals with applying the Six Sigma methodology in reducing the rejection rate of soy sauce packaging in food production. The DMAIC methodology of Six Sigma provides a step-by-step quality improvement methodology in which statistical techniques are applied. The leakage and cutting error problems were identified in the Define phase. The extent of the problem was measured in the Measure phase. The current DPMO value was 5,794.39, or sigma level at 4.0245. The root cause of the problem and the improvement priority were identified in the Analyze phase by applying the fishbone diagram and FMEA. The design of new Standard Operating Procedures (SOPs) and preventive maintenance schedule were used in the Improve phase to increase the sigma level by 50-60 percent and decrease DPMO by 99 percent for the upcoming four months implementation. Furthermore, a control plan was provided in the Control phase to monitor and sustain the achieved improvements.

scholarly journals SIX SIGMA METHODOLOGY IN TELECOM SECTOR FOR QUALITY IMPROVEMENT

2013 ◽  
pp. 84-88
Author(s):  
MADHAV KHANDELWAL ◽  
NEHA KHANDELWAL
Keyword(s):  
Quality Improvement ◽  
Six Sigma ◽  
Process Management ◽  
Sustainable Business ◽  
Design For Six Sigma ◽  
Lean Enterprise ◽  
Competitive Industry ◽  
Six Sigma Methodology ◽  
Telecom Sector ◽  
Insight Into

This paper presents tools of Six Sigma for Telecom Industries; these can achieve powerful operational improvements that produce sustainable business benefits. Six Sigma Qualtec’s dedicated Six Sigma for Telecom practice is specifically designed to help traditional and modern telecommunications providers, become more efficient in their operating procedures. By learning and implementing improvements such as Voice of the Customer (VOC), Six Sigma, Business Process Management Design for Six Sigma and Lean Enterprise principles, those companies will be able to dramatically improve the way they do business thus attracting and keeping customers in this hyper-competitive industry. This paper maps some of the changes in the telecom markets that resulted from competitive entry and gives an insight into the dynamics of competitive markets in relation to quality improvement. Additionally, the presentation seeks to demonstrate that in the quest for the particular competitive outcome via independent and transparent regulation.

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