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Since works-in-process (WIPs) are highly vulnerable to defects because of the variety and complexity of manufacturing processes, the purpose of this paper is to describe how to utilize existing analytics techniques to reduce defects, improve production processes, and reduce the cost of operations.

Three alternatives for diagnosing causes of defects and variations in the production process are presented in order to answer the following research question: “What are the most important factors to be included in prognostic analysis to prevent defects?”

The key findings for the proposed alternatives help explain the characteristics of defects that have a great impact on manufacturing yield and the quality of products. Consequently, any corrective action and preventive maintenance addressing the common causes of defects and variations in the process can be regularly evaluated and monitored.

Although the focus of this study is on improving shop-floor operations by reducing defects, further experimentation with business analytics in other areas such as machine utilization and maintenance, process control, and safety evaluation remains to be done.

This study has been validated with several scenarios in a manufacturing company, and the results demonstrate the practical validity of the approach, which is equally applicable to other manufacturing sub-sectors.

This study is different from the others by providing alternatives for diagnosing the root causes of defects. Control charts, costs of defects, and clustering-based defect prediction scores are utilized to reduce defects. Additionally, the key contribution of this study is to demonstrate different methods for understanding WIP behaviors and identifying any irregularities in the production process.

The purpose of this paper is to present a case of fatigue damaging of the attacking roller of the WRC class car. Fatigue fractures are a very essential source of cognitive and usable information about the cause of damage of various engineering components. Microfractography allows extending considerations about the main mechanism of initiation and growth of fatigue cracks. The presented research procedure allowed establishing the root cause analysis of the premature fatigue failure of the pinion shaft.

The specimen for metallographic investigation was extracted from failures pinion shaft. According to the light microscopy and scanning electron microscopy (SEM) study, the detailed observations of microstructure were performed. Fracture surface of pinion shaft and teeth were examined using SEM. The presence of the extraordinary mechanical notch was found as a potential failure root cause.

The potential cause of premature failure pinion shaft assembly has been found. The microstructural causes were excluded due to correctly performed heat treatment. The main reason of failure was improper mechanical machining of the pinion shaft due to large mechanical notch.

A detailed metallographic expertise route is presented. The usefulness of fractographic analysis is confirmed in case of the failure analysis of premature pinion shaft. The root cause was found and the concluding remarks are included in this paper.

Outsourcing logistical activities have become a widely used approach for firms to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages. Lean six sigma (LSS) has been accepted globally across sectors as a management strategy for achieving process excellence. The purpose of this paper is to feature the application of LSS for improving the supplier selection process (SSP) of outsourced logistics services in a multinational health-care company.

This study is based on an action research case study conducted on the SSP of the freight and distribution department in a multinational health-care company. This paper reports on the application of the LSS define-measure-analyze-improve-control (DMAIC) approach for reducing supplier selection lead time.

The study features a real-world case study of the LSS DMAIC application to improve the supplier selection process of a large health-care company. The key issues that were identified are lack of information visibility, top-down changes and unclear communication lines. To counteract these three root causes, the lean six sigma techniques that are implemented are the 5S, stakeholder analysis and standard operating procedure.

This research provided empirical evidence of how practical challenges in SSP can be managed with the use of LSS. It further proposed plausible solutions for reducing and sustaining improved outcomes. As the study is limited to one case, the validity of the results can be improved by including more organisations and more case studies from other similar organisations.

Research in supplier selection processes rarely links continuous improvement ideology such as LSS to support strategic selection and procurement of logistics services. This paper could serve as a resource for both practitioners to derive useful implications and to academicians as it contributes to the LSS body of knowledge for further theory testing.

The purpose of this study is to integrate two well-established frameworks with an aim to reduce the unwanted rejection rate recurring in the drug production process in pharmaceutical industries. The effectiveness of an integrated framework has been demonstrated by a real-time case study in a complex industrial environment, providing a platform for quality tools application in the pharmaceutical industry.

The hazard analysis and critical control points (HACCP) provided a basic framework for hazard analysis and its blending with statistical process control (SPC) aided in data-driven decision-making. The extensive brainstorming and Pareto analysis helped to identify potential critical-to-quality characteristics followed by SPC, x¯ and R charts, histograms and C_p and C_pk analysis to spot the critical control point. The fishbone diagram led to the extraction of the leading cause behind the identified problem. Then, based on recommended corrective actions, control limits were adjusted and the process was brought into control. Finally, a product-based cost analysis is also performed to illustrate the financial impact resulting from the proposed method’s successful implementation.

The integrated framework is applied to a drug production process which has a higher rejection rate (3%) because of the non-conformities. Based on Pareto analysis, potential failure causes were classified and prioritised as inappropriate composition (2.54%), packaging (0.35%), out-of-specification (0.069%), equipment failure (0.022%), input materials (0.018%) and miscellaneous (0.002%). It is found that 84% of the total rejection rate is contributed by inappropriate composition. After taking corrective actions, it is observed that the proposed method has helped to reduce the process rejection rate significantly (2.54-0.82%). In the monetary terms, 2.50% decline per unit costs is noted in this case study work. The proposed integrated framework’s success is further motivating other pharmaceutical industries to implement and expand it to other processes.

The case study is an attempt to contribute to the existing literature of quality management in pharmaceutical industries. In particular, it is a novel example to introduce the simple and user-friendly SPC tool into well-established HACCP framework to enhance its effectiveness in hazard identification. The case study results motivate managers to adopt quality techniques for achieving a higher quality standard and operational excellence.

Considers the thesis that intelligence differences and EEG‐intelligence correlations can both be explained in terms of differences in the frequency of neural transmission errors. Considers an alternative theory which holds that intelligence variance and correlated EEG variance are both caused by variation of cerebral arousability. Refers to technical and methodological problems that bedevil the EEG‐intelligence literature and measurement difficulties that have arisen through lack of adequate concepts. Concludes that the principal measurement problems derive from failure to appreciate the important distinction that must be made between “cerebral arousal” and “cerebral arousability”; and that any useful EEG‐intelligence concept must go beyond vague and general ideas such as “neural efficiency” or “neural transmission errors” to explain how EEG differences relate to differences in brain function that can account for the main facts recorded in the intelligence literature.

An indirect symmetric Galerkin BEM (SGBEM) is applied to 2D potential problems in this paper. Based on the assumption that solutions from different methods should be the same, the hypersingular matrix appeared in SGBEM is approximately expressed by those matrices appeared in asymmetric Galerkin BEM (AGBEM). As only strong and weak singularities need to be solved, the problem becomes much simpler. The space derivatives of potential are expressed with a set of new meaning distributed flux, which will produce the same potential on the boundary position for Ω in the unbounded domain Ω+Ω′, so that hypersingularity will not appear for boundary points. Therefore, there is no need of C^1,α for the spatial interpolation function (no Galerkin integration can be used for this purpose). Formulations for both the steady‐state and time‐domain potential problems are given. Three numerical examples are analyzed to demonstrate the effectiveness and accuracy of the proposed indirect method.

The primary aim of this article is to ascertain the modalities of leveraging Lean Six Sigma (LSS) for Industry 4.0 (I4.0) with special reference to the process industries. Moreover, it intends to determine the applicability of simulation-based LSS in the automation of the mineral water industry, with special emphasis on the robust design of the control system to improve productivity and performance.

This study adopts the action research methodology, which is exploratory in nature along with the DMAIC (define-measure-analyze-improve-control) approach to systematically unearth the root causes and to develop robust solutions. The MATLAB simulation software and Minitab statistical software are effectively utilized to draw the inferences.

The root causes of critical to quality characteristic (CTQ) and variation in purity level of water are addressed through the simulation-based LSS approach. All the process parameters and noise parameters of the reverse osmosis (RO) process are optimized to reduce the errors and to improve the purity of the water. The project shows substantial improvement in the sigma rating from 1.14 to 3.88 due to data-based analysis and actions in the process. Eventually, this assists the management to realize an annual saving of 20% of its production and overhead costs. This study indicates that LSS can be applicable even in the advent of I4.0 by reinforcing the existing approach and embracing data analysis through simulation.

The limitation of this research is that the inference is drawn based on a single case study confined to process industry automation. Having said that, the methodology deployed, scientific information related to optimization, and technical base established can be generalized.

This article is the first of its kind in establishing the integration of simulation, LSS, and I4.0 with special reference to automation in the process industry. It also delineates the case study in a phase-wise manner to explore the applicability and relevance of LSS with I4.0. The study is archetype in enabling LSS to a new era, and can act as a benchmark document for academicians, researchers, and practitioners for further research and development.

This paper is a case study on the successful application of Six Sigma methodology in the information technology industry. The purpose of this paper is to improve the resolution time performance of an application support process.

Through brainstorming, the potential factors influencing the resolution time are identified. From the potential factors, the important factors, namely, day-wise ticket volume, team’s software engineering skill and domain expertise are shortlisted using test of hypothesis, correlation, etc. Then a model is developed using principal component regression, linking the critical to quality characteristic with the root causes or important factors. Finally, a solution methodology is developed using the model to obtain the team composition and size with optimum software skill and domain expertise to resolve the tickets within the required time.

The implementation of the solution resulted in improving the process performance significantly. The process performance index increased from 0.00 to 1.2 and parts per million reduced from 501366.31 to 153. 33.

The software engineers can use the similar approach to improve the performance of core software activities such as coding, testing and bug fixing. The approach can also be used for improving the performance of other skill-based operations such as error reduction in medical diagnostics.

This is one of the rare Six Sigma case studies on improving skill-based processes such as software development. The study also demonstrates the usefulness of the Six Sigma methodology for solving dynamic problems whose solution needs to be continuously adjusted with the changes in the input or process conditions.

This study aims to explore the factors influencing electrical accidents. Here, the authors aim to understand and model the causes of electrical accidents at multiple levels.

In the study, the authors have tried to put causes of accidents in the electricity distribution segment, in the framework of the Swiss Cheese model. Delphi kind of expert survey was conducted to find the Cheese Slice (level) and the causes (holes) for electrical accidents. Inputs from a hundred experts having more than five years of experience in electrical utility companies have been used to find Cheese Slice and holes, to explain the occurrence of an electrical accident.

Effective training for safe work practices, safe knowledge and closer supervision would go a long way to plug the holes in the Cheese Slice in human factors. The difference in perception of managers, supervisors and workers on the importance of various causes of electrical accidents are also presented and discussed.

This research is based on expert opinion and survey where respondent perception is reported. Actual accident data has not been used here.

The holes or causes of accidents at different levels (Cheese Slice) have been identified for plugging or removal for better safety.

Electrical energy is widely used, and therefore, electrical safety is a social concern and also improving it is a social need.

The study contributes to electrical safety issues in the electrical utility sector.

The purpose of this paper is to set out a method for evaluating environmental impacts in the area of gas stations.

The design and implementation of this study followed steps that enabled a survey to be conducted by combining a wide variety of sources and bibliographical material, such as manuals, regulations, standards, laws and articles necessary for drawing up the model and the indicators of environmental impacts; and next the authors used two case studies to test the proposed model and exemplify the application.

This research identified the sources that cause adverse environmental impacts and the main preventive actions, as well as those for eliminating environmental impacts caused by the activities of the gas stations, so was possible developing a model which evaluated the real environmental situation of gas stations, using indicators to identify opportunities for improvements in the enterprises with ISO 14001 certification and non‐certificated enterprises.

This study used some international standards and some specific laws from Brazil, but it can be adapted to the current standards for gas stations in other countries.

Based on findings, it is believed that by using the model proposed in this research study, it is possible to diagnose the real environmental situation of the gas stations, thereby contributing to the preservation of the environment, sustainable development and above all to improving people's quality of life.

The originality of this study is the development of a viable model that can be used by enterprise, researchers and governmental environmental agencies for evaluating the environmental impacts of gas stations, integrating four different variables.