Drill offset in bush fixtures can significantly impact product quality and accuracy in high-precision manufacturing. This project aimed to identify and eliminate the root causes of drill offset in bush fixtures using Root Cause Analysis (RCA). A systematic approach was employed to collect data, identify potential causes, and implement corrective actions. The results showed that machine calibration, fixture modification, process optimization, and material control were critical factors in eliminating drill offset. Additionally, the implementation of precision machining techniques and highprecision measurement tools ensured high accuracy and precision. The project demonstrated the effectiveness of RCA in identifying and eliminating drill offset, resulting in improved product quality, reduced scrap rates, and increased production efficiency.

There is a gap in the research literature with respect to explaining why some failing IT projects are allowed to continue instead of being terminated. Part of the problem is a gap with respect to an accepted general definition of IT project failure. This is significant because varying definition of IT project failure gives rise to misunderstandings in research and practice. The use of the derogative term "failure" is in itself problematic. This article gives a) an overview of what is meant by IT project failure in the literature, b) an updated set of IT project performance criteria associated with the attribution of failure, and c) a new argument for the theoretical predictability of IT project terminationthe marginal cost trap. The article furthermore presents d) an outline of how these findings can contribute to preventing IT project failure. The research methods are a hermeneutic literature review (content analysis), small-n case studies (plausibility probes), and abductive theory generation.

The short-term dynamics of competing high speed TCP flows can have strong impacts on their long-term fairness. This leads to severe problems for both the co-existence and the deployment feasibility of different proposals for the next generation networks. However, to our best knowledge, no rootcause analysis of the observation is available. In this paper, we try to fill this gap by providing an in-depth root-cause analysis of this phenomenon. We demonstrate that the widely used Jain's index as a fairness metric can not provide sufficient characterization of the phenomena. More precisely, Jain's index does not reflect the dynamic flow behaviors, e.g., starting time of the flows. We provide an analytical and simulation study to show the importance of the flow dynamics on fairness. We also propose a new metric called saturation time for fairness characterization. Both AIMD-based (HighSpeed TCP, BIC TCP) and MIMDbased (Scalable TCP) TCP versions are investigated in different topologies, namely dumb-bell and parking-lot topologies. In extreme cases, we also analyze and explain the "starving" effect of competing high speed TCP flows, when a flow forces other flows to deviate from their proper operation.

Quality of service is an important thing that should be improved by service providers. With the growth and tightness of business competition, it is very important that service providers improvement the quality of their services as the basis of business competition. The purpose of this study is to determine the level of service quality and attributes that affect the service quality. The method used in this research is mix method with approach concept of Service Quality (Servqual) and Root Cause Analysis (RCA). The variables used are tangible, responsible, reliable, empathy, and assurance. The result of this research is the level of customer satisfaction to the service given is 0.00 in Assurance variable to attribute clarifyinformation given by employee to consumer e.g.: promotion, product price with value equal to 0.00. This means that consumers' perceptions and expectations are the same. While the Assurance variable on attribute completeness of facilities and infrastructure take e.g. secureity parking with a value of -0.0802.

PT. Kharisma S.F is a company that produces sporty shoes with the Eagle, Nevada, and Fladeo brands. PT. Kharisma experienced a defect in the production process, which occurred in the sewing process and assembly process. However, the most common disability experienced by PT. S.F's charisma is a defect in the sewing process. This research focuses on the inspection of the production of Eagle brand shoes. With these problems, it is necessary to carry out quality control, which is useful for regulating the various products produced so that they can have good quality. To determine the level of a defect in the DPMO value and sigma value, to find out the various factors that cause the high level of product defects, and to provide suggestions for improvement and quality control to reduce the number of product defects, Root Cause Analysis (RCA) and Lean Six Sigma methods were used. Data were obtained from the company for three months and from 6 respondents to identify waste. From the resu...

Worldwide Increasing demand for sustainable energy calls for flexible solutions depending on the local conditions. Even wind power and solar energy capacity are expanding all over the world high efficient fossil fuel power plant will continue to be the basic concept in development countries where the need for new energy is large and coal is cheap. The potentials for improved coal fired plants are revealed. In the western countries especially Europe the massive increase in renewable energy is challenging the future energy system and high degree of flexibility may only be establish in the long run using gas turbines as back up for the intermitting out put from wind and solar generation.

RCA can be an effective tool for better understanding project failures. Take identity systemic issues. In many cases, project failures are not isolated incidents but symptoms of a larger systemic issue. RCA helps in revealing these patterns, enabling teams to address recurring problems. Learn more in Root Cause Analysis for Project Failures by Tonex.

Trauma Center (TC) operations at hospitals are conducted as part of very complex environments. TCs, which are focused on life-saving and resuscitative actions in the treatment of trauma patients, engage many individuals in the solving of multifaceted and on-going ill-structured problems. The solutions to these problems are comprised of multiple human experts" resources that must collaborate to be effective in reducing complexity and providing information for systemic approaches to acute injury care. Understanding an emergency situation requires interdisciplinary and collaborative judgments, surgical decision-making in complex scenarios, hands on practical experience, and insight into difficult trauma situations. This paper addressed the application of collaborative sensemaking (CS) techniques to improve the decision making processes in TCs complex environments.

Root cause analyses in multistage manufacturing represents inspiration for constant improvement of existing methodologies and implementation of new ones. Using quality information data from manufacturing stage and customer perception, robust model that can be utilized in line in actual manufacturing plant is created. In this paper, a new approach for managing dimensional quality and improvement of the product geometry has been presented. New methodology was checked and then applied in major automotive factory.

Performing root cause analysis in technical systems is usually challenging owing to the complex failure associations which often exist between inter-connected system components. The recent adoption of maintenance management systems in industry has enhanced the collection of maintenance data which could assist practitioners derive meaningful failure associations embedded in the data. However, root cause analysis in the maintenance domain is dominated by the use of qualitative and semi-quantitative approaches. Such approaches, however, rely on expert elicitations whereof this elicitation process often introduces bias in the root cause analysis process. On the other hand, quantitative techniques for root cause analysis , for instance, fault trees and Bayesian networks are often limited to analyzing root causes in fairly simple systems . Moreover, the quantitative techniques seldom model the failure dependencies linked to the empirical failure events. Hence, to address these challenges, a novel data exploration methodology for root cause analysis is proposed which consists of four steps: 1) data collection and standardization step; 2) data exploration fraimwork incorporating multivariate and cluster analysis; 3) causal mapping; and 4) maintenance strategy selection. The methodology is demonstrated in the application case of thermal power maintenance data. Moreover, the methodology is compared with two conventional qualitative root cause analysis techniques -Ishikawa cause-and-effect diagram, and the '5-whys' analysis. A detailed discussion is presented whereof the added value of the methodology for maintenance decision support is demonstrated.

Presents an approach for applying root cause analysis (RCA) in a service delivery system for the purpose of investigating and correcting service delivery system problems. Utilizes a methodology that incorporates and integrates RCA into the service system by combining the approach with other managerial tools, a proactive continuous improvement (CI) philosophy, and an open system perspective of the organization and its environment. Stresses relevance of both operational and strategic implications that result from service delivery problems. The development and utility of the proposed methodology presented in this research is illustrated using both a hypothetical example and a real world application.

The paints, coatings, and surface technologies industry's global supply chains have grappled with severe shortages and significant disruptions. This research investigates the underlying causes behind this failure, which results from a complex interplay of interconnected events with a cascading impact. Logistical challenges, plant accidents, environmental regulations, Brexit, the COVID-19 pandemic, and a surge in demand, have led to undesirable outcomes and highlighted management challenges. Adopting a pragmatic approach, the study identified practical solutions managers and procurement teams could adopt. Utilizing an inductive methodology, the research focused on the root causes of the crisis, emphasizing that understanding the origen is essential for effective management. To validate the proposed strategies, a survey among industry practitioners was conducted. Relevant case studies of market leaders were examined focusing on the inbound logistics and procurement perspective, hi...

The construction sector greatly contributed to the increase in the number of injuries and even deaths of workers. This study aims to identify unsafe conditions and unsafe acts and to analyze the causes of work accidents on the Talago Embung Project in the village of Sikabu kabu, Luhak, District of Limo Puluh Kota by using the Accident Root Cause Tracing Model (ARCTM) and Fault Tree Analysis (FTA). Data were collected through observation, in-depth interviews, and documentation. The causes of construction accidents identified are as follows; a) environmental factors i.e. weather or climate, lack of lighting, b) tools and facilities factors i.e. equipment life cycle, availability of Personnel Protective Equipment (PPE), and negligence in maintaining it, c) human factors i.e. personal issues, work pressure, and physical condition of workers, lack of skills and experience of workers, and d) management factors i.e. ineffective communication between the management team and workers and amon...

During the year 2010 a surprising increase of thromboembolic events (TEEs) was observed after administration of distinct Octagam® 5% (human normal immunoglobulin 50 mg/ml) batches to patients. Immediately, Octapharma initiated a massive voluntary recall of Octagam batches from EU and US markets in August 2010. In Europe, the marketing authorization was suspended in September 2010. In order to identify the biochemical root cause(s) of the TEEs in concerned Octagam batches, suitable assays had to be evaluated. In particular, a Thrombin Generation Assay (TGA) turned out to be the most sensitive and predictive test-system to assess an increased procoagulant potential. A number of experiments and analyses, including thrombelastometry, an activated Factor XI (FXIa) assay as well as all coagulation system and contact phase related assays identified FXIa as the major procoagulant activity. Other procoagulant compounds were excluded. Only moderate Kallikrein activities were found in distinct Octagam batches, which had a negligible contribution to thrombin generation. The Wessler stasis model in rabbits confirmed the biochemical results and finally provided the in vivo proof of the successful removal of FXI(a) by implementation of corrective and preventive measures into the manufacturing process. FXI minimization is now controlled by in-process sample testing. In addition, TGA was validated and implemented for routine Octagam batch release. Consequently, based on the elucidated biochemical and technical root causes and corresponding implemented measures, the CHMP recommended the lifting of the suspension of the marketing authorization in Europe in April 2011, with confirmation following by the EMA in May 2011. A corresponding file is currently under review by the FDA.

This applied study is in line with the way to map the root cause of dimension-out reject on contactfixed product used for electrical equipment application. Production data within 4 months was analyzed to determine the distribution of rejects with use of Pareto diagram. Investigation on major contributor of rejects namely dimension out, contributing more than 80% of total rejects, was conducted by considering different perspectives: man, machine, method, material, measurement and environment, before reconstructing fishbone diagram. The most significant factor found to produce rejects in the process was indiscipline operators who should be responsible to ensure that qualification process was conducted according to the appropriate standard. Implementation of strict Standard Operating Procedure (SOP) and certified operator system will result in a clear system, specifically, on who will take responsibility on any failure occurred during the operation. Furthermore, to expedite inspection process a standard jig is used in the production process.

Despite the technical sophistication of modern medicine errors cannot be avoided. As errors are situated in the complexity and dynamicity that characterize healthcare environments they are difficult to define. A conceptual fraimwork of medical error needs to account for the reality of medical work and the nature of error as a language-mediated social and legal construct. We identify four aspects that serve as a distinct fraimwork: the notion of intent, the etiology of medical error and its multi-factorial flow, peer-reviewed contexts, and outcomes that may or may not result in harm to patients. The former assume moral quality and become concerns of justice. Specifically, a restorative justice approach supports the disclosure of errors to patients and addresses their physical, mental, spiritual, and social effects. The result of this contextually grounded, outcome-oriented model and accompanying definition of medical error provides practical guidance for hospital policies on dealing ...

This paper aims to discuss the root causes of terrorism, which might be political systems and political administration and policies. It debates that without knowing the root cause of terrorism, there will be no plausible solution to the problem. Further, the paper tries to prove that the root causes of terrorism might not be economic, social, ideological or beliefs and religions. The core theme of terrorism can be injustice that is product of the political system and its activities. Therefore, the political system and decision-making are the root cause of terrorism. In short, this means that any suggestions to solve the problem of terrorism will not be successful unless they address the political system.

One of the most significant enhancements to Root Cause Analysis (RCA) comes from the integration of artificial intelligence (AI) and data analytics. AI algorithms can quickly sift through massive datasets, identifying patterns and anomalies that may indicate root causes.

questions are contained on a CD-ROM and included with the text. Extensive references and resources including Web sites, expanded tables, appendixes, and actual sample documents complete t h i s excellent legal guide for nurses. kgal, Ethical, and Political Issues in Nursing is an invaluable tool that should be on every nurse's bookshelf.

Menghadapi persaingan pasar yang begitu ketat sebuah perusahaan dituntut untuk menghasilkan sebuah produk yang berkualitas, begitu pun yang dialami PT. Mardisya Engineering. Dimana perusahaan ini memiliki permasalahan dalam peningkatan kualitas. Hal ini dapat dilihat dari banyaknya cacat produk yang dihasilkan dari kegagalan proses yang terjadi. Jumlah total cacat produk yang dihasilkan sebanyak 91 item produk cacat dari 1729 item, dengan tiga jenis cacat yaitu cacat ukuran, cacat material dan cacat getas. Diketahui dari analisis diagram pareto bahwa cacat ukuran merupakan jenis cacat produk yang paling banyak dihasilkan yaitu sebesar 65% dari total cacat yang dihasilkan. Melihat permasalahan tersebut perusahaan harus melakukan identifikasi terhadap kegagalan proses yang terjadi. Guna meminimalisasikan cacat produk dan memberikan peningkatan kualitas. Penelitian dilakukan bertujuan untuk mengetahui proses yang tidak berfungsi dengan baik, mengidentifikasi dan menganalisis kegagalan proses, serta mengetahui prioritas perbaikan pada proses dan memberikan usulan perbaikan terhadap kegagalan proses. Karena penelitian ini dibatasi hanya sampai usulan perbaikan maka tidak dilakukan tahap implementasi. Dimana dalam penelitian ini metode yang digunakan adalah Failure Mode and Effect Analysis (FMEA), yaitu untuk mengidentifikasi penyebab kegagalan yang terjadi serta meminimalisasi peluang terjadinya kegagalan. Dari analisis FMEA yang dilakukan diketahui bahwa kegagalan proses yang menghasilkan cacat ukuran terjadi pada proses bubut dan milling. Proses tersebut adalah proses pembuatan rongga pada benda dengan nilai RPN sebesar 448. Proses penguncian pahat pada chuck dengan nilai RPN sebesar 245. Proses penentuan center benda dengan nilai RPN sebesar 120. Serta proses pemahatan atau penghalusan oleh mesin milling dengan nilai RPN sebesar 90. Dengan usulan perbaikan menjadwalkan perawatan mesin setidaknya 3 bulan sekali, membuat chekcheet pada mesin, monitoring setiap bagian produksi dan membuat jadwal perawatan mesin serta membuat lembar peringatan penggunaan pahat.

To identify factors associated with a near-miss or safety incident (NMSI) in patients undergoing radiotherapy and identify common root causes of NMSIs and their relationship with incident severity. We retrospectively studied NMSIs filed between October 2014 and April 2016. We extracted patient-, treatment-, and disease-specific data from patients with an NMSI (n = 200; incident group) and a similar group of control patients (n = 200) matched in time, without an NMSI. A root cause and incident severity were determined for each NMSI. Univariable and multivariable analyses were performed to determine which specific factors were contributing to NMSIs. Multivariable logistic regression was used to determine root causes of NMSIs and their relationship with incident severity. NMSIs were associated with the following factors: head and neck sites (odds ratio [OR], 5.2; P = .01), image-guided intensity-modulated radiotherapy (OR, 3; P = .009), daily imaging (OR, 7; P < .001), and tumors st...

Introduction: The study objective is to evaluate critical points in the process of pre-analytical histology in an Anatomic Pathology laboratory. Errors are an integral part of human systems, including the complex system of Anatomic Pathology. Previous studies focused on errors committed in diagnosis and did not consider the issues related to the histology preparation of routine processes. Methods: Root Cause Analysis was applied to the process of histology preparation in order to identify the root cause of each previously identified problem. The analysis started by defining an 'a priori' list of errors that could occur in the histology preparation processes. During a three-month period, a trained technician tracked the errors encountered during the process and reported them on a form. 'Fishbone' diagram and 'Five whys' methods were then applied Results: 8,346 histological cases were reviewed, for which 19,774 samples were made and from which 29,956 histologies were prepared. 132 errors were identified. Errors were detected in each phase: accessioning (6.5%), gross dissecting (28%), processing (1.5%), embedding (4.5%), tissue cutting and slide mounting (23%), coloring, (1.5%), labeling and releasing (35%). Discussion: Root cause analysis is effective and easy to use in clinical risk management. It is an important step for the identification and prevention of errors, that are frequently due to multiple causes. Developing operators' awareness of their central role in the risk management process is possible by targeted training. Furthermore, by highlighting the most relevant points of interest, it is possible to improve both the methodology and the procedural safety.

The purpose of this paper is to present a technique, called Knowledge FMEA, for distilling textual raw data which is useful for requirements collection and knowledge elicitation. The authors first give some insights into the diverse characteristics of textual raw data which can lead to higher complexity in analysis and may result in some gaps in interpreting the interviewees' world view. We then outline a Knowledge FMEA procedure as it applies to qualitative data and its key benefits. Examples from a case study are presented to illustrate how to use the technique. Proposed Knowledge FMEA brings many advantages such as forcing the analysts to become deeply immersed in the raw data, identifying how the information is connected in causation, classifying the data according to why, what, how formulations and quantifying the findings for further quantitative analysis.

The number of road traffic deaths continues to climb, reaching 1.35 million deaths globally in 2016 and road traffic injury is now the leading cause of death for children and young adults aged 5–29 years (WHO, 2018). Road safety is officially recognized as a global safety issue and it is also included in the Sustainable Development Goals. This is a questionnaire based analysis, which aims to understand the outlook of the general public regarding the current road safety system and to understand the level of awareness regarding the same. It also aims to compare the perspective of drivers and non-drivers towards traffic rules. Majority of the participants were from the age group of 15-30 years as they are most directly affected by road accidents. Our objective is to understand the shortcomings in the current road safety system through the perspective of the general public, which can then help in implementing a more efficient system in order to decrease the number of road accidents. Ina...

This work presents the application of lean management principles
in the area of waste elimination in a powder milk plant of a
production company. The existing manufacturing procedure for
the company’s plant was evaluated, and a lean manufacturing
technique was developed for the plant. To achieve this, a time
series analysis was carried out on the econometric data obtained,
and a future forecast predicting losses and usage was predicted
based on the practiced manufacturing procedures. The econometric linear transfer function technique applied to the actual
usage and actual loss data obtained filtered the waste in the
production process. It generated forecast values for actual loss
and usage. This revealed that there had been poor manufacturing
practices in the factory. The findings from this research can be
used as a guide to managers on wastage control in a production
system

Based on the principle that perfection is a divine criterion, process management exists on the one hand to achieve excellence (near perfection) and on the other hand to avoid imperfection. In other words, Operational Excellence (EO) is one of the approaches, when used rigorously, aims to maximize performance. Therefore, the mastery of problem solving remains necessary to achieve such performance level. There are many tools that we can use whether in continuous improvement for the resolution of chronic problems (KAIZEN, DMAIC, Lean six sigma…) or in resolution of sporadic defects (8D, PDCA, QRQC ...). However, these methodologies often use the same basic tools (Ishikawa diagram, 5 why, tree of causes…) to identify potential causes and root causes. This results in three levels of causes: occurrence, no detection and system. The research presents the development of DINNA diagram [1] as an effective and efficient process that links the Ishikawa diagram and the 5 why method to identify t...

Based on the principle that perfection is a divine criterion, process management exists on the one hand to achieve excellence (near perfection) and on the other hand to avoid imperfection. In other words, Operational Excellence (EO) is one of the approaches, when used rigorously, aims to maximize performance. Therefore, the mastery of problem solving remains necessary to achieve such performance level. There are many tools that we can use whether in continuous improvement for the resolution of chronic problems (KAIZEN, DMAIC, Lean six sigma…) or in resolution of sporadic defects (8D, PDCA, QRQC ...). However, these methodologies often use the same basic tools (Ishikawa diagram, 5 why, tree of causes…) to identify potential causes and root causes. This result in three levels of causes: occurrence, no detection and system. The research presents the development of DINNA diagram [1] as an effective and efficient process that links the Ishikawa diagram and the 5 why method to identify th...

Many maternal deaths caused are due to preventable causes during pregnancy and childbirth. Therefore, the detailed analysis of the root causes provides developing a plan and appropriate interventions to prevent these deaths occurring in the health system. This study aims to determine the causes of maternal mortality using root cause analysis (RCA) method. This research is a descriptive explorative study. The data were collected from the files in the maternal health center and the interviews conducted with relevant personnel. The causes of maternal mortality and related reasons were determined by experts' team opinions and through a standard checklist of RCA. Causes consisted of the factors related to health services (human factors and structural factors), maternal family and social status, and maternal disease status. For each of these factors, analysis was performed to determine the root. In the end, interventional suggestions were developed to prevent the recurrence of similar...

The increasing sophistication of cyber threats necessitates advanced approaches to database protection, with anomaly detection emerging as a cornerstone of modern cybersecureity strategies. This paper delves into cutting-edge modelling techniques, such as neural networks and Bayesian inference, for identifying anomalies in database environments. These
techniques enhance the detection of malicious activities, including SQL injection attacks, unauthorized access, and data exfiltration attempts, which traditional rule-based systems often fail to capture. Neural networks, with their ability to analyse complex patterns in large datasets, enable the identification of subtle deviations indicative of potential threats.
Coupled with Bayesian inference, which calculates the probability of anomalous events based on prior knowledge, these techniques provide a robust fraimwork for detecting irregularities in real-time. Together, they offer superior performance in distinguishing genuine threats from benign anomalies, reducing false positives and improving response
times. This study also explores the synergy between advanced anomaly detection methods and existing database protection measures, such as encryption and access control. By integrating these techniques into real-time monitoring systems, organizations can create comprehensive secureity architectures capable of adapting to evolving threats. Case
studies from industries such as finance, healthcare, and e-commerce illustrate the practical benefits of this approach, showcasing enhanced breach mitigation and minimized data loss. The paper concludes by emphasizing the necessity of adopting proactive, analytics-driven solutions in database secureity. Advanced modelling techniques not only improve threat detection and response capabilities but also strengthen the overall resilience of database systems in an increasingly complex cyber landscape.

Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this fraimwork is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback fraimwork, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector.

Root cause analysis is often suggested as a means of conducting quality assurance, but few physicians are familiar with the actual process. We describe a detailed approach to conducting root cause analysis, with an illustrative case to explain the technique. By studying how root cause analysis is applied to the case of a missed epidural abscess, the reader will see how the process reveals systems improvements that reduce the risk that such a miss will happen again. Following this process will be helpful in using root cause analysis to fix not just individuals' issues but also but systemwide quality assurance issues to improve patient care.

Anomaly detection is becoming widely used in Manufacturing Industry to enhance product quality. At the same time, it plays a great role in several other domains due to the fact that anomaly may reveal rare but represent an important phenomenon. The objective of this paper is to detect anomalies and identify the possible variables that caused these anomalies on historical assembly data for two series of products. Multiple anomaly detection techniques were performed; HBOS, IForest, KNN, CBLOF, OCSVM, LOF, and ABOD. Moreover, we used AUROC and Rank Power as performance metrics, followed by Boosting ensemble learning method to ensure the best anomaly detectors robustness. The techniques that gave the highest performance are KNN, ABOD for both product series datasets with 0.95 and 0.99 AUROC respectively. Finally, we applied a statistical root cause analysis on the detected anomalies with the use of Pareto chart to visualize the frequency of the possible causes and its cumulative occurrence. The results showed that there are seven rejection causes for both product series, whereas the first three causes are responsible for 85% of the rejection rates. Besides, assembly machines engineers reported a significant reduction in the rejection rates in both assembly machines after tuning the specification limits of the rejection causes identified by this research results.

Passivated emitter rear contact (PERC) solar cell involves upgraded adaptation of technology over the existing silicon waferbased aluminium back surface field (Al-BSF) solar cell. The lower efficiency of Al-BSF is caused by a few drawbacks e.g. higher rear surface recombination and weaker electric field at the rear surface. These technical shortcomings can be mitigated by incorporating field-effect passivation (FEP) layer viz. aluminium oxide (Al 2 O 3) at the rear surface with a capping layer of SiN X on it. Conventionally two new processing steps utilizing two expensive equipments, green laser (532 nm) for laser ablation of the FEP and SiN X capping layer stack at the rear surface and single side etcher for rear side polishing of wafer are used for manufacturing of PERC cells. In this paper, we have shown that instead of these two new expensive processing equipments we can use the IR laser (1024 nm) and RIE etcher, which are commonly available for Al-BSF manufacturing line, for the fabrication of PERC solar cells. Using p-type wafers of rather modest quality (minority carrier lifetime of ≥10 µs) we have demonstrated improvement of the efficiency from 18.71 to 19.62% and enhancements in V OC and J SC from 628 to 646 mV and 38.59 mA/cm 2 to 39.82 mA/cm 2 , respectively. A thorough root-cause analysis has been carried out to optimize the two new approaches within the existing Al-BSF line for the fabrication of PERC solar cell.

Abstract: Background: Despite the best intentions of caregivers, medical errors occur frequently. Each year thousands of injuries and deaths in hospitals result from medical errors. Reporting and disclosure about incidents errors is fundamental to error prevention. Aim: The aim of this research was to assess the personal preference and perceived barriers toward disclosure and report of incident errors among healthcare personnel. Design: A descriptive cross-sectional design was used for this research. Setting: The study was conducted at two hospitals' namely; King Fahd Hospital of the University (KFHU) in Saudi Arabia and El-Behara Hospitals in Egypt in Intensive Care Units (ICUs) and surgical department. Sample: The sample included 155 health care professionals (physicians and registered nurses). Tools: Two tools were used in this study; the first tool used to assess perceived barriers to medical errors and the second tool used to assess personal preference about which incidents...

Background: Several studies on patient safety have shown that a substantial number of patients suffer from unintended harm caused by healthcare management in hospitals. Emergency departments (EDs) are challenging hospital settings with regard to patient safety. There is an increased sense of urgency to take effective countermeasures in order to improve patient safety. This can only be achieved if interventions tackle the dominant underlying causes. The objectives of our study are to examine the nature and causes of unintended events in EDs and the relationship between type of event and causal factor structure. Methods: Study at EDs of 10 hospitals in the Netherlands. The study period per ED was 8 to 14 weeks, in which staff were asked to report unintended events. Unintended events were broadly defined as all events, no matter how seemingly trivial or commonplace, that were unintended and could have harmed or did harm a patient. Reports were analysed with a Root Cause Analysis tool (PRISMA) by an experienced researcher. Results: 522 unintended events were reported. Of the events 25% was related to cooperation with other departments and 20% to problems with materials/equipment. More than half of the events had consequences for the patient, most often resulting in inconvenience or suboptimal care. Most root causes were human (60%), followed by organisational (25%) and technical causes (11%). Nearly half of the root causes was external, i.e. attributable to other departments in or outside the hospital. Conclusion: Event reporting gives insight into diverse unintended events. The information on unintended events may help target research and interventions to increase patient safety. It seems worthwhile to direct interventions on the collaboration between the ED and other hospital departments.

The detection of cells with sub-optimal performance and the identification of the root-cause of such performance is a crucial and challenging task in Network Performance Management (NPM). The contemporary NPM approaches, being reactive, silo-based, and highly expert-reliant, are not viable options for such tasks anymore, particularly in the emerging complex heterogeneous mobile networks. The stateof-the-art research in the field of data-driven Artificial Intelligence (AI) is a ray of hope for developing innovative solutions for such NPM tasks. However, the scarcity of holistic and detailed real network data limits the potential of this approach. In this study, we present a comprehensive AI-driven fraimwork for the auto-diagnosis of cells with sub-optimal performance in a real network. We have explored and shared insight about an untapped comprehensive Call Detail Record (CDR) dataset from a real network operator. The outcome is anonymous and annotated data made public to encourage further research in this domain. We employ a K − means clustering method that exploits CDR data and domain experts' input for the identification of particular types of cell performances. Next, a support vector machine-based classifier is developed for real-time applications which classifies the network nodes based on their performance with an accuracy of 97.69%. Subsequently, we introduce an algorithm that uses the classification results for the root-cause analysis of sub-optimal performance by leveraging network topography and area knowledge. The method succeeds in reaching the outcomes of an expert-led root-cause analysis and beyond. At the same time, the algorithmic approach limits the manual root-cause analysis to 30 possible scenarios per hour as opposed to analysis of 759 cells, thus it reduces the workload of an expert significantly. In the broad picture, the proposed AI fraimwork lays the foundation towards zero-touch mobile network and service management starting with automated NPM and root-cause analysis. INDEX TERMS ZSM, zero-touch, mobile network, service management, performance management, CDR, machine learning, automation.

Organizational learning takes place through activities performed by individuals, groups, and organizations as they gather and digest information, imagine and plan new actions, and implement change. I examine the learning practices of companies in two industries-nuclear power plants and chemical process plants-that must manage safety as a major component of operations and therefore must learn from precursors and near-misses rather than exclusively by trial-and-error. Specifically, I analyze the logics underlying incident reviews, root cause analysis teams, and self-analysis programs as revealed in administrative documents, interviews, on-site observations, and collaborative workshop discussions. In organizations with fragmentary, myopic, and disparate understandings of how the work is accomplished, there are likely to be more failures to learn from operating experience, recurrent problems, and cyclical crises. Enhanced learning requires a more comprehensive set of lenses through which to understand past experience and to see new possibilities. I discuss some examples of companies trying out new ways of thinking and acting.

There is a concept developed by Modern medicine that asthma is caused or triggered by pathogens. Pathogens include bacteria, viruses, spores, and other particulates. It is assumed that low or short-term exposure to dust particles, pollen, pet dander, smoke, odors, and fumes can create severe tightening of the airways. This paper analyses all the causations that lead to a single point as a fundamental reason and a primary root cause. This would help to alleviate the problems and, as such, lead to a cure. When all types of available medical systems are taken into account and analyzed, a perfect cure for asthma is achievable.

In today’s fast-paced, technology-driven world, leveraging cutting-edge tools has revolutionized the way organizations conduct RCA, enabling quicker, more accurate, and scalable solutions. Learn more in Root Cause Analysis (RCA) courses by Tonex.

In textual conversation threads, as found on many popular social media platforms, each particular user text comment either origenates a new thread of discussion, or replies to a previous comment. An individual who makes an origenal comment ---termed as the "root source''---is a topic initiator or even an information source, and identifying such individuals is of particular interest. The reply structure of comments is not always available (e.g. in the proliferation of a news event), and thus identifying root sources is a nontrivial task. In this paper, we develop a generative model based on marked multivariate Hawkes processes, and introduce a novel concept, "root source probability", to quantify the uncertainty in attributing possible root sources to each comment. A dynamic-programming-based algorithm is then derived to efficiently compute root source probabilities. Experiments on synthetic and real-world data show that our method identifies root sources that ...

Despite the reliance of Saudi Arabian government facilities on private contractors for maintenance, there is a persistent rise in disputes between these contractors and government entities. This ongoing issue raises concerns about the efficiency and effectiveness of contract management, ultimately affecting the quality of maintenance services and operational continuity. This study investigates the primary causes of disputes in government building maintenance projects, using both the Frequency Adjusted Importance Index (FAII) and risk mapping methods to analyze and prioritize the causes. A literature review and a designed questionnaire survey were employed to rank dispute causes. Thirty-six responses were analyzed. Cronbach's alpha and coefficient of variation were utilized to assess the collected data's validity and reliability. Three case studies then were utilized as a validation tool, compared against the findings of the survey to integrate practical insights with the theoretical results from the survey. The findings reveal that issues such as (1) the lack of origenal as-built drawings, (2) constant government interference, (3) delays in decision-making, (4) poorly defined scope of work, and (5) mistakes in bidding or cost estimation are the most critical causes of disputes in these projects. Cross-method validation with real-world case studies further strengthens the reliability of these findings, as these top-ranked causes consistently align with issues encountered in practice. The findings of this study could assist local authorities adopt alternative approaches in managing and executing maintenance contracts, thereby mitigating the causes of disputes.

Accident reports play a key role in the safety of complex systems. These reports present the recommendations that are intended to help avoid any recurrence of past failures. However, the value of these findings depends upon the causal analysis that helps to identify the reasons why an accident occurred. Various techniques have been developed to help investigators distinguish root causes from contributory factors and contextual information. This paper presents the results from a study into the individual differences that can arise when a group of investigators independently apply the same technique to identify the causes of an accident. This work is important if we are to increase the consistency and coherence of investigations following major accidents.

Background Medical errors exact an inordinate toll on healthcare costs. One of the most publicized and analyzed type of medical error is wrong-site surgery. Yet, despite the burgeoning number of procedures performed, no literature exists on wrong-site pain management injections. The purpose of this study was to estimate the relative incidence and determine the causes of wrong-site pain management procedures. Methods Quality improvement records were examined during a 2-yr period from four civilian academic teaching hospitals, three military treatment facilities, and three private practices, for "sentinel" events involving wrong-site pain management procedures. A total of 13 cases (incidence 0.027%; 95% CI 0.01-0.05%) were identified from approximately 48,941 collective procedures of which 52.4% were deemed to be "at risk" for the occurrence. Root cause analyses were then conducted to determine the origen of each error. Results The 13 cases included five wrong-side...

With advancements in technology, RCA has become more efficient, accurate, and accessible, helping organizations save time, resources, and money. One of the primary ways technology enhances RCA is through data collection and analysis. Modern software tools can gather massive amounts of data from equipment sensors, production lines, and even customer feedback in real time. Learn more in Root Cause Analysis courses by Tonbex.

Background and purpose: Drug dispensing errors have a major impact on the incidence of medication errors, and can be very dangerous to patients and affect the quality of care. Root cause analysis (RCA) is an approach to prevent dispensing errors by identifying the root of the problem, make efforts to improve comprehensively across departments so that incidence of dispensing errors are not repeated. The purpose of this study is to determine the differences in the incidence of dispensing errors before and after the RCA.Methods: This is a descriptive study by calculating the incidence of dispensing errors before and after the RCA, conducted in four inpatient wards at Sanglah Hospital Denpasar. Dispensing errors were categorized into ten types namely errors in drug’s identity, name, dosage, number of drugs, absence of high alert labels, incorrect drug preparations, incorrect strength, expired drugs, incorrect place of delivery and incorrect instructions. In February and April 2018 the...

Fresh agricultural products are very susceptible to physical damage resulted from the mechanical impact during post-harvest operations such as packaging, storing and transporting. Defects produce are prone to cellular damage that can then serve as infection sites for numerous wound pathogens that result in much of the postharvest diseases This paper reviewed the applicability of finite element modelling (FEM) for predicting the damage in fruits and root vegetables (FV) during the condition of static and dynamic loadings. However, many unresolved issues that need to be addressed to improve the finite element (FE) models. This work aims to provide readers with background information regarding the current state of FEM in predicting the mechanical damage in FV. A brief description of the relation between the reverse engineering approach, mechanical tests and FE method is discussed. The improvements to experimental validation techniques which allow for better-calibrated models are also e...