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This research paper aims to develop and validate an enhanced business process improvement methodology (EBPIM) by integrating the DMAIC (define, measure, analyze, improve and control) and the comprehensive business process management (CBPM) methodologies.

A systematic literature review and analysis were conducted to prove the novelty of the research approach and identify the similarities, differences, strengths and weaknesses of the DMAIC and the CBPM methodologies. The EBPIM was proposed based on the analysis results. Then, a focus group approach was used to evaluate and validate the methodology.

The EBPIM consists of nine activities: preparation, selection, description, quantification, modeling, enactment, improvement opportunities selection, analysis and improvement and monitoring. The proposed methodology adopted the systematic and structured process of the DMAIC methodology by having one tollgate between every two activities to check the progress and authorize the team to go to the next activity. At the same time, it has the ability of the CBPM methodology to enhance the interaction between human activities and business process management systems (BPMS).

The EBPIM was evaluated and validated by a focus group of academic professors. However, the main limitation of the proposed methodology is that it is still theoretical and needs to be empirically tested. Therefore, future work will focus on testing the EBPIM in different industries and organization sizes.

From the theoretical perspective, the proposed methodology adds value to the knowledge in the scope of business processes improvement methodologies (BPIMs) by integrating the DMAIC and the CBPM methodologies. It takes advantage of and combines the strengths of the DMAIC and CBPM methodologies. From the practical perspective, the proposed methodology presents a valuable tool that can facilitate the organization’s mission to improve the areas that need improvement using a systematic improvement methodology that will effectively enhance organizational performance (OP).

The BPIMs literature analysis proved that most of the reviewed methodologies could not support all phases of the business process improvement (BPI) activities. It was concluded that integrating the DMAIC and the CBPM methodologies is a novel approach. The proposed methodology will enhance the efficiency of both methodologies, fill the gaps that may exist in both of them and lead to better results in terms of BPI.

Problem solving and continuous process improvement are key elements to achieve business excellence. Many problem solving and process improvement methodologies have been proposed and adopted by organisations, with DMAIC being the most widely used. The purpose of this paper is to present an empirical application of a modified version of DMAIC which enabled a world-class organisation to achieve an optimum reduction in the lead time of its aerospace engine assembly process.

The paper reviews the most commonly used problem solving and process improvement methodologies and specifically, DMAIC, its variations and limitations. Based on this, it presents define, measure, analyse, improve, review, control (DMAIRC). Finally, DMAIRC is empirically applied through a case study, in a world-class manufacturing organisation.

The results obtained from the case study indicate that DMAIRC is an effective alternative to achieve the maximum improvement potential of a process. In particular, DMAIRC helped the organisation studied to achieve a 30 percent reduction in the lead time of its engine assembly process.

The novel problem solving and process improvement methodology presented in this paper can be used by organisations to undertake a more effective improvement project by assuring that the maximum potential of their improvement initiatives and processes is achieved.

This paper aims to investigate the sources of variation in aluminum profiles hot extrusion process for the purpose of process capability improvement at National Aluminum and Profiles Company (NAPCO) in Palestine. The critical-to-quality characteristics (CTQ) have been determined as base variables to measure the process capability.

The DMAIC (Define, Measure, Analyze, Improve, and Control) Lean Six Sigma (LSS) approach has been adopted to conduct this study. More specifically, historical data analysis and PARETO charts have been employed. The defects' root causes have been determined using the cause-and-effect diagram and decision matrix. A course of suggested actions has been established to help in improving extrusion process capability. Minitab-18 software was used for conducting inferential statistical analysis. A case study considering a geometry CTQ of D3 dimension of bottom sash aluminum profiles 4,332 was selected for analysis.

The results indicated a reduction in DPMO from 89,649 to 15,659, sigma level was improved from 2.84 to 3.65, process yield was improved from 91.04% to 98.43% and cost was reduced from U$75,972 to U$13,250.9 (i.e. a saving of U$62,721). Studying and improving the sigma level of the extrusion process would yield fewer defective products and consequently fewer customer complaints. A validation process which has been conducted during the year 2019 showed a consistent improvement that aligns with the first stage of improvement made on October 1, 2018.

This study focuses on only one critical quality characteristic (CTQ), namely, a geometry CTQ of D3 dimension of bottom sash aluminum profiles 4,332 produced by NAPCO was selected for analysis.

This study would be useful for researchers and practitioners to improve the process capability in aluminum profiles manufacturing industries in general and hot extrusion processes in particular.

Many previous studies on applying LSS-DMAIC methodology have been conducted in aluminum industries in developed countries. According to the literature, it is highly recommended to have more case studies of applying LSS-DMAIC in different industries in developing countries. NAPCO is the only aluminum manufacturing plant in Palestine that hotly extrudes and coats aluminum profiles. Hence, the present study is the first of its kind in NAPCO and in Palestine. Projecting the assessment of the impact of process improvement opportunities and capability analyses into monetary measures are also innovative.

Competitive pressures force companies to seek solutions to eliminate wastes while improving product quality. Lean Six Sigma (LSS) has been considered one of the most effective approaches for business transformation. This article aims to present an empirical case study where LSS and Define, Measure–Analyze–Improve–Control (DMAIC) methodologies are applied to reduce defects in a car parts manufacturer.

The study follows the DMAIC methodology. Design of experiments and hypothesis testing were applied in a single case study.

The main defects and the main factors that cause defective parts were indicated for die-casting and machining processes. Solutions implemented reduced the defect incidence from a chronically high level to an acceptable one. The sigma level rose from 3.4 s to 4 s sustainably.

The study is limited to a single case study, without intention of generalizing the results to other types of industries.

This paper can be a useful guide of how to use DMAIC Six Sigma approach to defect reduction and can be applied in many sectors.

This study offers the knowledge on how to apply the Six Sigma DMAIC methodology, reducing the dependence on specialization courses.

This study describes in detail the process used in a structured improvement exercise including sigma-level calculation, factorial experiments and hypothesis tests – a set of techniques still poorly combined in the literature.

In this era of globalisation, as competition intensifies, providing quality products and services has become a competitive advantage and a need to ensure survival. The Six Sigma's problem-solving methodology DMAIC has been one of the several techniques used by organisations to improve the quality of their products and services. This paper aims to demonstrate the empirical application of Six Sigma and DMAIC to reduce product defects within a rubber gloves manufacturing organisation.

The paper follows the DMAIC methodology to systematically investigate the root cause of defects and provide a solution to reduce/eliminate them. In particular, the design of experiments, hypothesis testing and two-way analysis of variance techniques were combined to statistically determine whether two key process variables, oven's temperature and conveyor's speed, had an impact on the number of defects produced, as well as to define their optimum values needed to reduce/eliminate the defects.

The analysis from employing Six Sigma and DMAIC indicated that the oven's temperature and conveyor's speed influenced the amount of defective gloves produced. After optimising these two process variables, a reduction of about 50 per cent in the “leaking” gloves defect was achieved, which helped the organisation studied to reduce its defects per million opportunities from 195,095 to 83,750 and thus improve its sigma level from 2.4 to 2.9.

This paper can be used as a guiding reference for managers and engineers to undertake specific process improvement projects, in their organisations, similar to the one presented in this paper.

This study presents an industrial case which demonstrates how the application of Six Sigma and DMAIC can help manufacturing organisations to achieve quality improvements in their processes and thus contribute to their search for process excellence.

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.

The purpose of this paper is to develop and validate an extended Define-Measure-Analyze-Improve-Control (DMAIC) based framework through a case study of an Indian fasteners manufacturing organization.

Research methodology is established on the development of the existing DMAIC framework through an extensive literature review of 25 LSS/DMAIC based frameworks and discussions held with practitioners. This paper also depicts a case study of Indian manufacturing organization for validation of the developed framework.

The study proposed an extended DMAIC based framework for effective implementation of Lean Six Sigma (LSS) methodology. Furthermore, this framework has been implemented successfully in the Indian manufacturing organization and showed encouraging results. The in-house rejections of Nut Cylinder Head (NCH) were brought down to 966 from 2910 PPM and sigma level was improved by 0.40. The case organization has achieved significant improvements in the process capability, customer satisfaction, and cost savings of US$ 0.25 million in one financial year. Intangible benefits like improvements in employee's morale, communication, housekeeping and decision-making capabilities were also observed significantly.

The proposed DMAIC based framework has been implemented successfully in the Indian case organization, and the results will enable the policymakers, specifically practitioners, to strategically leverage the resources for successful implementation of the LSS in healthcare, aerospace, service sectors etc.

This research develops a DMAIC based framework which can be used to implement LSS effectively in different industries. Moreover, the pre (initial/introduction) and post (validation/verification) implementation phase provides the top management, an edge to think strategically into broader improvement areas.

The purpose of this study is to adopt a supply chain performance measurement (SCPM) framework as proposed by (Dweiri and Khan 2012) to model a novel SCPM index (SCPMI) system to measure and improve supply chain performance (SCP).

The adopted SCPM framework developed by Dweiri and Khan (2012) is used to model a generic SCPMI framework aided by analytic hierarchy process (AHP) method and inputs from industrial experts. To exemplify the applicability and efficiency of the generic SCPMI system, an automobile assembling company from an emerging economy was used. This SCMPI system is used to measure, improve and measure post-improvement SCP guided by DMAIC (define, measure, analyze, improve and control) methodology.

The study’s initial measurement results showed an average SCP of the case company over a four-month period as 82 per cent. DMAIC methodology was used to identify inherent problems and proposed improvements. The post-improvement SCP measurement saw an improvement from an average of 82 to 83.82 per cent over the four-month period.

The proposed generic SCPMI framework aided by AHP-DMAIC has been successfully implemented in a case company. After implementation, managers and decision-makers saw an improvement in their SCP. The proposed SCPMI system and results can be useful for benchmarking by manufacturing organizations for continuous SCP improvement.

An original SCPMI framework proposed is general in nature and can be applied in any organization.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.