Software Verification Process Improvement Proposal Using Six Sigma

2007 ◽  
pp. 51-64 ◽  
Author(s):  
Tihana Galinac ◽  
Željka Car
Keyword(s):  
Process Improvement ◽  
Six Sigma ◽  
Software Verification ◽  
Verification Process

Process Improvement of Brake Lever Production Using DMAIC (+)

2011 ◽  
Author(s):  
Chittaranjan Sahay ◽  
Suhash Ghosh ◽  
Pradeep Kumar Bheemarthi
Keyword(s):  
Data Analysis ◽  
Problem Solving ◽  
Process Improvement ◽  
Six Sigma ◽  
Lean Manufacturing ◽  
Cost Effective ◽  
Poor Quality ◽  
Statistical Process ◽  
Automotive Components ◽  
The Cost

This work describes a strategy to reduce the cost associated with poor quality, by reducing the parts per million defects by Defining, Measuring, Analyzing, Implementing and Controlling (DMAIC) the production process. The method uses a combination of principles of Six Sigma applications, Lean Manufacturing and Shanin Strategy. The process has been used in analyzing the manufacturing lines of a brake lever at a Connecticut automotive components manufacturing company for reducing the cost associated with the production of nonconforming parts. The analysis was carried out with the help of the data collected on nonconformance parts and the application of phase change rules from DMAIC (+). Data analysis was carried out on statistical process control softwares, MINITAB and SPC XL 2000. Although, the problem of tight bushing existed on only one line of the brake lever assembly, this problem solving approach has solved the tight bushing problems on all assembly and alternates lines in a time- and cost-effective way.

Credit card account opening excellence using six sigma methodology

2016 ◽  
Vol 7 (3) ◽  
pp. 294-323 ◽  
Author(s):  
Samsul Islam
Keyword(s):  
Process Improvement ◽  
Six Sigma ◽  
Credit Card ◽  
Current Knowledge ◽  
Case Study Methodology ◽  
Content Type ◽  
Study Results ◽  
Six Sigma Methodology ◽  
Six Sigma Approach ◽  
Opening Process

Purpose This study aims to expand the current knowledge of the Six Sigma approach in a period of time when there is little direct evidence of the need to improve the credit card account opening process. This is an important but neglected area of focus in the Six Sigma literature. This study explores the extent to which process improvement practices are extended to the credit card department. Design/methodology/approach A case study methodology is adopted in this study to facilitate an exploration of the implemented Six Sigma approach in the credit card department of a leading commercial bank. The process improvement tool used is the define, measure, analyze, improve and control (DMAIC) cycle. Findings The study’s results confirm that the Six Sigma approach improves the quality of the credit card account opening process. So, the Six Sigma approach can account for a reduced number of keying-in errors, resulting in better data accuracy and improved customer satisfaction. Research limitations/implications The authors, in an attempt to render the study results more feasible for data collection, have chosen to focus on the process of the new accounts unit of the credit card department. Therefore, the authors have not taken into account the other units (e.g. transaction processing) of the same department. Practical implications The results of this study will be useful in persuading bank management to evaluate and implement the Six Sigma approach. Hence, this research will assist bank managers with replies to questions, such as: “What impact will Six Sigma have on process-centric improvement, such as the new accounts opening process of a credit card department?” Originality/value Within the literature on the Six Sigma practice, there is little research that focuses on the implementation of this particular toolset especially for credit card departments. This indicates a gap in the field. A new contribution to bridging that gap comes from the analysis of the results for the Six Sigma concept, which addresses the new accounts opening process.

scholarly journals 24 Challenges in Deductive Software Verification

10.29007/j2cm ◽  
2018 ◽  
Author(s):  
Reiner Hähnle ◽  
Marieke Huisman
Keyword(s):  
Software Verification ◽  
Logical Inference ◽  
Verification Process ◽  
Further Development

Deductive software verification aims at formally verifying that all possible behaviors of a given program satisfy formally defined, complex properties, where the verification process is based on logical inference. We list the most important challenges for the further development of the field.

New Horizons for Shipbuilding Process Improvement

2005 ◽  
Author(s):  
Bahadir Inozu ◽  
M. J. Niccolai ◽  
Clifford A. Whitcomb ◽  
Brian Brian MacClaren ◽  
Ivan Ivan Radovic ◽  
...  
Keyword(s):  
Process Improvement ◽  
Six Sigma ◽  
Lean Six Sigma ◽  
Defense Contractors ◽  
New Era ◽  
Process Improvements ◽  
New Horizons ◽  
Direct Reports ◽  
Design For Six Sigma ◽  
Strategy Design

“In 2004, we start an Initiative --Lean Six Sigma Initiative to achieve our Op Ex Goals. We will be conducting a number of on boarding sessions for Six Sigma with senior leaders in DOD, NAVY, and most importantly Defense Contractors. We will require Six Sigma training for direct reports.” John Young, ASN (RDA) The announcement of NAVSEA’s Lean Six Sigma initiative has ushered in a new era in the ways that naval combatants are designed, built, and operated. As the Navy’s budgetary constraints increase in the coming years, the challenges they face in the 21st century will grow. New levels of process performance are mandated. This paper first highlights the opportunities that the Lean Six Sigma roadmap brings to shipbuilding process improvement and then details the efforts to adopt Lean Six Sigma and align it with the continuous improvement initiative at NGSS. Aspects of management strategy, Design for Six Sigma, replicating process improvements as part of integrating Lean Six Sigma with Knowledge Management are discussed.

Data-driven quality improvement approach to reducing waste in manufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rose Clancy ◽  
Dominic O'Sullivan ◽  
Ken Bruton
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Quality Management ◽  
Process Improvement ◽  
Six Sigma ◽  
Data Driven ◽  
Manufacturing Processes ◽  
Management Performance ◽  
Chain Management ◽  
Content Type

PurposeData-driven quality management systems, brought about by the implementation of digitisation and digital technologies, is an integral part of improving supply chain management performance. The purpose of this study is to determine a methodology to aid the implementation of digital technologies and digitisation of the supply chain to enable data-driven quality management and the reduction of waste from manufacturing processes.Design/methodology/approachMethodologies from both the quality management and data science disciplines were implemented together to test their effectiveness in digitalising a manufacturing process to improve supply chain management performance. The hybrid digitisation approach to process improvement (HyDAPI) methodology was developed using findings from the industrial use case.FindingsUpon assessment of the existing methodologies, Six Sigma and CRISP-DM were found to be the most suitable process improvement and data mining methodologies, respectively. The case study revealed gaps in the implementation of both the Six Sigma and CRISP-DM methodologies in relation to digitisation of the manufacturing process.Practical implicationsValuable practical learnings borne out of the implementation of these methodologies were used to develop the HyDAPI methodology. This methodology offers a pragmatic step by step approach for industrial practitioners to digitally transform their traditional manufacturing processes to enable data-driven quality management and improved supply chain management performance.Originality/valueThis study proposes the HyDAPI methodology that utilises key elements of the Six Sigma DMAIC and the CRISP-DM methodologies along with additions proposed by the author, to aid with the digitisation of manufacturing processes leading to data-driven quality management of operations within the supply chain.

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