Find Root Causes Research Articles

Exploring the Role of Action Research in Enhancing Quality Management in Teacher Education: A Case Study

The sincere pursuit process called educational research has developed in modern times. Thus, academic research is a systematic activity devoted to discovering and developing well-organized knowledge that always seeks to find or solve a problem. At present, due to the increasing modernization and engineering development in the education system, research has become inevitable in solving operational problems, as well as in the teacher education field, various problems related to teaching and training and action by inventing various developmental approaches in the field of quality management Research. According to Palmer and Johnson (1971), action research is a method of using research for social activities that involve groups of people to solve problems and find root causes, as if the research itself is a part of empowerment and action. This article will explore the inter-dependence of action research and quality management in teacher education.

Transforming Employee Motivation to Enhance Employee Performance at PT Bio Farma (Persero)

This study was conducted at PT Bio Farma (Persero). This Indonesian state-owned company focuses on the research and production of life-science products. During the last three years of implementing the Performance Management System, employee performance has decreased from 2019 – 2021. This study explores the decline in employee performance and the factors that cause it. The research was conducted using quantitative and qualitative analysis methods. The quantitative approach was performed through a survey involving 125 Bio Farma employees as respondents. The survey questions cover 5 (five) elements that can contribute to employee performance: shared values, leadership style, organizational culture, perceptions of organizational practices, and employee motivation. In comparison, the qualitative method was performed through interviews, observation, and internal documentation. To help find root causes and gaps, current practice conditions in the company are also discussed in this study. This study found that employee motivation is the main factor contributing to decreased performance, especially regarding career opportunities and the remuneration system. These business issues lead to proposed solutions to improve the career opportunity system at Bio Farma. Talent management is used in determining the future career of employees. This study suggests the application of competency-based assessment to obtain employee competency data that will be included in employee talent data. The proposed solution will be based on an implementation plan through the implementation of four main activities: identifying employee competencies, defining employee competencies, implementing competency-based assessments, and creating employee talent data which includes performance, potential and competency data.

Defect Analysis of Printing Process in Offset Printing Industry by Using Failure Mode Effect Analysis (FMEA) and Fault Tree Analysis (FTA)

KOP Corp. is an offset printing company, especially in packaging printing (folding boxes). KOP Corp. faced many defects in production. This has an impact on increasing cost and customer dissatisfaction. This paper discusses Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) to find root cause of problem. FMEA use to prioritized sources of problem. Moreover, FTA is used for finding out the root of the problem. Based on Risk Priority Number (RPN), three failure modes with the largest RPN, namely defect printed, color is not up to standard and defect in the picture. By using the FTA method, analyzed the root problems of these failure modes. After creating a Fault Tree Diagram and looking for a minimum Cut Set, it can be recommended several improvements such as the socialization of a good sampling plan, the design of a training program, Quality Control Circle development, and the selection of good suppliers.

Rejection Analysis of Casting Defect Using Statical Quality Tools

Abstract: In the industry different type of casting component are produced, nowadays increasing demand of high-quality casting component at right time. For the quality casting component required skill and knowledge. In small industry use trial and error technique defect analysis it is used for reduced rejection percentage of casting compound but this process is time consuming and economical and also this process has less control on rejection of casting components the main aim is produced defect free components at right time and increase the quality of casting components, in this paper used statistical quality tools and Auto-cast simulation software for finding root cause of casting defect. Ishikawa diagram, why-why analysis and brain storming this are statistical quality tool used for rejection analysis casting. Using statistical quality tools cover defect like sand drop, sand fusion, blow hole cold shut etc. but leakage defect root cause not found using statistical quality tool. For minimize leakage defect use auto-cast simulation software find out the root cause. Taking the corrective action and reduced rejection percentage of casting defect of RDP Carrier.

The Challenges of Digital Supply Chain Implementation: A Case Study in Project MANTRA Tool in Fast-Moving Consumer Goods Company

PT UNIKACA PROBANA (a disguised name), a pioneer in digital supply chain transformation journey, developed an auto-tracking tool called MANTRA. MANTRA is a digitized innovation planning tool that automates master data management and packaging material development in a single touchpoint. MANTRA is expected to help businesses by providing analytics and insights for better decision-making. However, MANTRA's utilization rate is still not optimized, hovering around 63% up to October 2019. This presents the biggest challenge that needs to be addressed. The research goal is to help find root causes and suggest actions to make this tool more beneficial to users. This research uses a qualitative methodology, with data and information collected through direct observation and interviews with nine respondents from three different clusters. Interview results were analyzed through mind-mapping and narrowed down to two factors: core technical capabilities and non-technical factors. Several actions for improving the utilization rate include introducing a change agent, distributing performance reports, and transforming MANTRA from a "by-choice" to a "must-use" tool. The final section concludes with a diagnostic framework that can be utilized to implement digitization in the supply chain environment

Non Communicable Disease Programme of Colombo District, Sri Lanka: A Technical Report

Non Communicable Diseases (NCD) are the dominant chronic health problem in Sri Lanka. NCDs are basically classified into 2 types; acute NCD & chronic NCD. Policies, Strategies, Activities and monitoring and evaluation plans are in place in the National NCD programme.
 The objective of this case study is to study the Non Communicable Disease Programme of the division of Regional Director of Health Services (RDHS) – Colombo. Key informant’s interviews, review of secondary literature and observation in district review meetings were used to collect information.
 It was found that RDHS division - Colombo is responsible for both preventive and curative heath care for a population of 2.2 Million through 56 health care institutions. With regard to NCDs; injury surveillance, advocacy, capacity building, development of information, education & communication material, social media strategies and regular reviews are in good progress while gaps were seen in pre admission care, coverage of service, utilization pattern, treatment of NCDs, health promotion, inter sectorial corporation and information management system.
 Nominal group technique was used for prioritization. The issue of “NCD curative care provision is not optimum” was selected as the highest priority problem. Fish born diagram was developed to find root causes. The arm of “Physician factors” was selected to give recommendations and action plan was prepared accordingly.

Surface Defect Detection and Root Cause Analysis

Artificial Intelligence has played an increasingly important role in surface defect detection in recent years. At the same time, there are many challenges using deep learning for this area, such as the detection accuracy, shortage of data and, lack of knowledge of root cause of defects. To solve the problem of data shortage, we propose a taxonomy method called DataonomyTM to extend a meta defect datasets with a small number of samples for training defect classifiers. For the accuracy, we apply two latest deep neural network(DNN) architectures, Inception v3 and fully convolutional networks (FCN) so as not only to classify whether there are defects but also to make a pixel-wise prediction to inference the areas of defects. For those detected defects, we combine DNN with traditional AI methods to find root causes of detected defects. We use a generalized multi-image matting algorithm to extract common defects automatically. We apply this technology to identify defects that stem from systematic errors in the surface operation. Experimental results have shown great capability and versatility of our proposed methods.

Image Defect Detection and Root Cause Analysis

Artificial Intelligence has played an increasingly important role in visual defect detection in recent years, while there are many challenges using deep learning for this application, such as the shortage of data, lack of knowledge of root cause of defects. In this paper, we combine deep learning with traditional AI methods, not only to solve unshaded defect detection but also find root causes of detected defects. First, we propose a taxonomy method called DataonomySM to extend a meta defect dataset with a small number of samples and a deep learning method to detect the image defects. For detected defect images, we use a generalized multi-image matting algorithm to extract common defects automatically. We apply this technology to identify defects that stem from systematic errors in a product line and later extended its use to watermark processing. Experimental results have shown great capability and versatility of our proposed methods.

Closed Drain Transfer Pump Failure Analysis using Root Cause Failure Analysis (RCFA) Method

Maintenance is a process carried out to maintain the reliability of individual/group assets. Positive displacement type pumps are commonly used in closed drainage systems as transfer pumps in oil and gas processing plants. However, there are times when the pump fails which requires further effort to prevent the failure from recurring. Efforts that can be made to overcome this are using the method of Analysis of the Root Failure (Root Cause Failure Analysis). The RCFA method uses recollection of evidence related to design, procurement, and operation of a tool to find root causes and latent causes of problems. As a result of gaps found between the design process, procurement which leads to the root cause of pump failure, this study recommends pump-operating companies to pay more attention to piping installation to support pump performance and coordination between owner, design, and procurement to prevent this failure from recurring.

An Effective Method for Online Disease Risk Monitoring

ABSTRACTMany diseases can be prevented or treated if they can be detected early or signaled before their occurrence. Disease early detection and prevention (DEDAP) is thus important for health improvement of our society. Traditionally, people are encouraged to check their health conditions regularly so that readings of relevant medical indices can be compared with certain threshold values and any irregular readings can trigger further medical tests to find root causes or diseases. One limitation of such traditional DEDAP methods is that they focus mainly on the data collected at the current time point and historical data are not fully used. Consequently, irregular longitudinal pattern of the medical indices could be neglected and certain diseases could be left undetected. In this article, we suggest a novel and effective new method for DEDAP. To detect a disease by this method, a patient’s risk to the disease is first quantified at each time point, and then the longitudinal pattern of the risk is monitored sequentially over time. A signal will be triggered by a large cumulative difference between the longitudinal risk pattern of the patient under monitoring and the longitudinal risk pattern of a typical person without the disease in concern. Both theoretical arguments and numerical studies show that it works well in practice. Supplementary materials for this article are available online.

Monitoring and Improving Syndromic Surveillance Data Quality

Monitoring and Improving Syndromic Surveillance Data Quality

Integration of process control protection layer into a simulation-based HAZOP tool

This paper discusses the framework methodology behind the proposed simulation-based HAZOP tool. Simulation-based approach is one of the many ways to support conventional HAZOP by its automation. Compared to knowledge-based and other approaches, a HAZOP software tool based on deviations simulation is able to examine the investigated process more into detail and so find root causes of hazardous consequences. Another advantage is the ability to identify also potential hazards which did not occur in the past and might be overlooked. The presented framework methodology uses a layer of protection analysis (LOPA) concept of independent protection layers (IPLs) testing. Control system integrated into the raw process design represents the first of various protection layers of the LOPA concept. As a case study, a CSTR chemical production with nonlinear behavior under Proportional-Integral-Derivative (PID) actions as the predominant type of classical feedback control strategy is used. The presented tool identifies hazardous regimes under conditions when control loop introduces hazardous consequences or even acts synergically with existing hazardous events. Risk derived from different consequences is ranked by the risk assessment matrix (RAM) as a part of the conventional quantitative HAZOP study.

Unsupervised classification of multichannel profile data using PCA: An application to an emission control system

Abstract Modern sensing technologies have facilitated real-time data collection for process monitoring and fault diagnosis in several research fields of industrial engineering. The challenges associated with diagnosis of multichannel (multiple) profiles are yet to be addressed in the literature. Motivated by an application of fault diagnosis of an emission control system, this paper proposes an approach for efficient and interpretable modeling of multichannel profile data in high-dimensional spaces. The method is based on unsupervised classification of multichannel profile data provided by several sensors related to a fault event. The final goal is to isolate fault events in a restricted number of clusters (scenarios), each one described by a reference pattern. This can provide practitioners with useful information to support the diagnosis and to find root cause. Two multilinear extensions of principal component analysis (PCA), which can analyze the multichannel profiles without unfolding the original data set, are investigated and compared to regular PCA applied to vectors generated by unfolding the original data set. The effectiveness of multilinear extensions of PCA is demonstrated using an experimental campaign carried out on an emission control system. Results of unsupervised classification show that the multilinear extension of PCA may lead to a classification with better compactness and separation of clusters.

Reduction of Adhesive Joining Defect in Optical Transceiver Assembly Process

An optical Transceiver is a device that is used for transmitting and receiving digital data which is modulated into the light source, and also consisted of two main parts as lens (one for transmitter (Tx) and another one for receiver (Rx)) and flexible printed circuit board (FPCB). The surfaces of the FPCB was manually cleaned by Isopropyl alcohol (IPA) using cotton buds, and then were joined to the lens using the glues of the adhesive Urethane Acrylate (UAA) which cured using UV light, and followed by the adhesive Black Epoxy (BEA), respectively. The joined specimen then was cured in a thermal oven. The work-piece, especially the joined between lens and FPCB was inspected by optical appearances and shear force test. The nonconformance (NC) of work-piece that is the lower specification of shear force and turbidity of the cured UAA was found about 35% of the production. The aim of this research was to reduce the joining defect of the lens and FPCB in the optical Transceiver assembly process. The applied condition and obtained output of each workstation started from backward of the process was characterized applying the Scanning Electron Microscope (SEM), the quality tools and statistical analysis in order to find root causes of the problem and to improve the process. The study found that (1) the lower shear force was related to the higher turbidity of cured UAA which normally was transparences after thermal curing; (2) the turbidity of cured UAA was resulted by repeated rubbing of using one cotton bud of worker during cleaning the FPCB surface that causes the surface contaminated and then lower adhesive force of the joint; (3) a single trip of rubbing per cotton-bud was applied and could remarkably decrease the adhesive joining defect (NC) of work-piece to 7% of the production.

Institutional Growth and Industrial Competitiveness: Exploring the Role of Strategic Flexibility Taking the Case of Select Institutes in India

The internationalization of human resources, supply chains and technology management is driving the rise of institutes from Asia. The focus may shift from institutional growth to dynamism for technology-based focal institutes keen to contribute to industrial competitiveness. The role of strategic flexibility to enhance the contribution of institutes to competitiveness is an unexplored area. We study situations and trends in the growth of select leading institutes in India to explore patterns and problems. We attempt to structure the key problem factually to find root causes. While literature review is of limited help to detect any key patterns, interactions and observations indicate that flexibility in the ability to shift proportion of paths in the portfolio of an institute may enhance its vitality and competitiveness. The study contributes to the method of ‘problem structuring’ by proposing ‘actor-based root cause diagram’, and ambiguities to evolve sharper research questions. The study identifies several topics for further research to accelerate catch-up by institutions on quality and vitality.

Full-Wafer Voltage Contrast Inspection for Detection of BEOL Defects

This paper details an application where E-beam inspection (EBI) can be used for 100% full wafer inspection, generally considered a mythical target for EBI. For process layers where the line-widths and defects of interest are large, very large pixel size and high scan frequency can be used, thereby making full wafer inspection feasible. The metal layers in the back-end-of-line fit this bill when scanned in voltage contrast (VC) mode. Shorts or opens at any previous layer connected to the surface nodes can cause a VC signal, therefore the electrical health of each wafer is assessed for multiple layers simultaneously across the full wafer. The advantage of this scan is that failure sites can be identified and somewhat localized well before wafer final test. This application is more appropriate for semi-mature technologies where there are few defects per wafer, and therefore a full wafer scan is needed to catch a reasonable number of defects. The challenge with this type inspection is in identification of the root cause. A number of studies to map VC defect strength to types of physical defects are described. These studies demonstrated that this technique successfully finds yield limiting defects, but not all yield limiting defects will be detected. A plan for how to use the VC inspection to find root cause is presented.

Knowledge-assisted BIM-based visual analytics for failure root cause detection in facilities management

Abstract Facilities managers need to identify failure cause–effect patterns in order to prepare corrective and preventive maintenance plans. This task is difficult because of the complex interaction and interdependencies between different building components. Standardization based on Building Information Modeling (BIM) provides new opportunities to improve the efficiency of facilities management (FM) operations by sharing and exchanging building information between different applications throughout the lifecycle of the facilities. This paper aims to utilize BIM visualization capabilities to provide FM technicians with visualizations that allow them to utilize their cognitive and perceptual reasoning for problem solving. It investigates a knowledge-assisted BIM-based visual analytics approach for failure root-cause detection in FM. For this purpose, the inspection and maintenance data of Computerized Maintenance Management System (CMMS) are integrated with a BIM. Moreover, various sources of building knowledge such as fault trees and relationships between components are formally represented. These resources are used to create custom visualizations through an interactive user interface which helps in exploiting the heuristic problem solving ability of field experts to find root causes of failures in a building.

Near misses—private or public concern?

Near miss incidents include those releases and/or fires that do not result in significant employee injury or costs. In many cases there are federal reporting requirements that include reports to the National Response Center. Loss of containment releases are often near misses for catastrophic incidents and provide evidence of process safety program weaknesses. Facilities have an interest in conducting incident investigations to find root causes, lessons learned, and make safety improvements. Small sites often do not have the expertise to conduct good investigations while some large sites may tend to blame operator error rather than admit management system errors or process design issues. This article explains 2002 amendments of the Delaware requirement to report releases. The amendment adds the reporting of flammable gas releases and expands the existing written follow up report requirements to explain the “facts and circumstances leading to the release and the measures proposed to prevent the future releases and remedy any deficiencies in the prevention program.” Having this “public” examination of near miss investigations puts pressure on both industry and our regulatory program to seek root causes and make practical improvements in site process safety programs—without adding any substantial regulatory burden to industry. © 2013 American Institute of Chemical Engineers Process Saf Prog 32: 328–331, 2013

Application of Six Sigma Methodology in Production Organization

In the last years and also due to today's economic situation and crises in the world, each organization is looking for a continuous improvement of processes and business performance. The major task of each production organization or services is the saving of money, which is lost because of scrap, long cycle times, wrong process maps and inventory differences. The goal of this article is to describe the implementation of Six Sigma in a production organization focusing on the production of interior parts for the automotive industry. During the summer time, there was delamination between thermoplastic foil and plastic substrate, which caused increasing of scrap, additional substandard works as well as the risk of quality complaints from customer. Six Sigma and DMAIC cycle were used to find root causes and to implement permanent corrective actions to remove this kind of problem from production.

Thermal Stress Analysis in Structural Elements of HRSG Casing

Heat recovery steam generators (HRSGs) are arranged at the tail end of gas turbines in combined cycle power plants (CCPPs), and are designed to withstand the hot gas environment approaching 600℃. In addition to higher thermal to power efficiency, CCPPs show superior response characteristics compared to those of other conventional steam power plants. For that reason, frequent load changes on the system, which sometimes include daily start and stop (DSS) operation, would impose additional burden on the structural elements. The main objective of this work is to analyze the thermal stress conditions as related to the observed failure on the structural elements of HRSG casing, and to find root causes of failure of mechanical integrity. To achieve this goal, field measurements were performed to record temperatures of wall and stiffener of the casing from a real plant in operation. To consider the effect of hot gas on the casing, computational fluid dynamic (CFD) analysis of gas flow inside the HRSG with appropriate wall conditions using FLUENT V12. Thermal stress analysis on the thin wall of the casing and stiffeners of HRSG was conducted with the temperature data from the CFD results, using ANSYS Workbench V12. Summarizing the computational results, some limited ideas were presented which would be useful to prevent damages.