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1 – 4 of 4Elisa Gonzalez Santacruz, David Romero, Julieta Noguez and Thorsten Wuest
This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework…
Abstract
Purpose
This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”
Design/methodology/approach
The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.
Findings
This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.
Originality/value
This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.
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Panagiotis Tsarouhas and Niki Sidiropoulou
In a packaging olives manufacturing system, the drained weight of the product plays a decisive role in customer’s satisfaction as well as in financial saving for the organization…
Abstract
Purpose
In a packaging olives manufacturing system, the drained weight of the product plays a decisive role in customer’s satisfaction as well as in financial saving for the organization. The purpose of this study is to minimize the variation of the drained weight of olives in the production system to avoid the negative consequences.
Design/methodology/approach
The research develops a practical implementation step-by-step of Six Sigma define, measure, analyze, improve and control (DMAIC) in reducing the variation of the drained weight of olives.
Findings
Data analysis was used at various phases of the project to identify the root causes of rejection and rework. As a result of the necessary interventions and actions to optimize the manufacturing process, the standard deviation of drained weight was significantly reduced by 51.02%, with a 99.97% decrease in the number of parts per million defectives. Thus, the yield of the production process was improved by 8.24%. The estimated annual savings from this project were US$ 228,000 resulting from reduced rejection and rework.
Practical implications
This research may be used in packaging olives production systems as a tool for managers and engineers planning to increase productivity and efficiency while also improving product quality. The study also provided the organization with helpful actions that will be used to guide future Six Sigma operations management on the system. Thus, practical guidelines and solutions are provided.
Originality/value
In this project, for the first time, the Six Sigma methodology has been applied to solve a real-world problem in the packaging olives manufacturing system and to show that the DMAIC approach may assist to improve the efficiency of their operations and hence contribute to their quest toward continuous improvement.
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The purpose of this study is to propose the implementation of Lean Six Sigma (LSS) framework in supply chain by providing an actual case study of how to reduce the logistics cost.
Abstract
Purpose
The purpose of this study is to propose the implementation of Lean Six Sigma (LSS) framework in supply chain by providing an actual case study of how to reduce the logistics cost.
Design/methodology/approach
In this paper, it is shown how LSS approach, basic tools and Define, Measure, Analyze, Improve and Control methodology can significantly improve a company by enhancing the supply chain and reducing the logistics expenditures.
Findings
Root causes to the main problem of this study were analyzed to identify appropriate solutions. After the implementation of solutions, the company’s product quality and internal communication were improved. Correspondingly, the percentage of customer orders that have to be transported by road instead of maritime reduced to 5% from 13% and the percentage of the road transportation cost paid unnecessarily by the company decreased to 1% from 5%.
Practical implications
This case study provides a roadmap and step-by-step implementation of LSS framework for especially companies in plastics industry.
Originality/value
To the best of the author’s knowledge, this paper is the first example of a LSS case study conducted in Turkey to improve the supply chain of a company by targeting primarily a reduction on logistics costs.
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This study examines the research landscape of Lean Six-Sigma (LSS) applications in hospitals for the period of the last decade (2011–2020) to derive answers to the research…
Abstract
Purpose
This study examines the research landscape of Lean Six-Sigma (LSS) applications in hospitals for the period of the last decade (2011–2020) to derive answers to the research questions RQ 1: What are the current publication trends for the application of LSS in hospitals concerning document type, Journal (Source), active authors and country-wise publications and their comparison in the two most reputed scientific databases, i.e. Scopus and Web of Science (WoS), RQ2: What are the clusters based on the authors and keywords? RQ3: What are the research trends and author's productivity in LSS applications in Hospitals? RQ4: What are the future research areas?
Design/methodology/approach
This article compares these two databases (Scopus and WoS) based on publication pattern, document type, active authors and co-citation analysis. This article analyzes the core sources, author's productivity, globally cited articles, word growth analysis, thematic map and world collaboration map on the WoS and Scopus dataset. The software used are Vosviewer, Biblioshiny (R Package for Bibliometric) and M.S. Excel.
Findings
The application of LSS in hospitals is a niche theme. In the WoS database International Journal of Lean Six-Sigma and in Scopus database International Journal of Health Care Quality Assurance are the most relevant sources publishing research articles in this field. The USA has the highest scientific production in this field. Among the authors, Antony J is the most active author in this area, with the highest contribution over the years.
Originality/value
This study fills the literature gap by mapping the field of LSS in hospitals.
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