Application of Practical Problem-Solving Techniques to Reduce Wells Process Safety Incidents in Workover Operations

This RCA case study has been initiated before the Gas Turbo generator failure took place by timely intervention when the Gas Turbine incident alarm triggered. Root cause analysis (RCA) process was introduced in ADGAS back in 2004, the process was designed to ensure the elimination of defects and incidents with an integrity exposure or causing production losses from repeating by identifying the root cause and putting in place robust actions to ensure incidents don't reoccur. The RCA process enabled ADGAS to put in place a practical methodology for the initiation and execution of an investigation to resolve an incident that could cause a significant loss in production, Loss of functions and / or process contamination, an integrity risk or a repetitive problem that had to be eliminated. The RCA findings would have to undergo a review before the findings and actions are approved and issued. LG6 Gas Turbine is generating 1/3 of Das Island electrical power and very critical for ADMA / ADGAS production sustainability. In May2011 LG6 encountered a severe failure of its Gear Box, entire mechanical package misalignment, load coupling compression, severe foundation tilting and load gear box tilting. The inspection findings revealed a high risk of coupling destruction and production losses. Risk assessment highlighted that if the coupling damage while machine running, it could cause a flying objects to surrounding by 30.5 meters away and 4 meter width. This RCA case study has been initiated before the LG6 power generation Gas Turbine failure took place by timely intervention when the Gas Turbine incident alarm triggered. Risk has been assessed and decision made to shut down the machine immediately for site investigation and remedial actions. RCA team members faced a big challenge to get the machine back in service safely and efficiently as soon as possible to save the plant production and avoid bad reputation of partial electrical power off- black out. This also saved a company a rental fees of pack up power generation unit (estimated 24 MM US$ for two years) and assure providing of the required power to keep the operation of LNG, OAG trains and commission of IGD projects on time with no power shortage. This project resulted in significant potential enhancements for all of the ADGAS Turbo machinery units through the innovative application of a proven root cause analysis and remedial actions to identify the truly underlying "root causes" of incidents and developing sustainable repairs. Using a fault tree analysis process this project successfully identified 85 critical possible causes for the rare Frame 5 Gas turbine fault, eliminate by verification one by one pinpointed the cause of failure and developed a repair actions that prevent failure reoccur.

ABSTRACTThis study evaluates whether auditor use of root cause analysis (RCA) for an identified client misstatement affects auditors' assessments of underlying control issues and materiality in an integrated audit setting. We also test whether auditor cognitive style moderates these effects given prior findings that a misfit between task structure and cognitive style undermines performance. This research is motivated by concerns about integrated audit quality and auditors failing to consider control deficiencies indicated by client misstatements. We randomly assigned 147 auditors to four RCA treatments (No RCA, Unstructured RCA, Structured “5 Whys” RCA, Structured “Fishbone” RCA). As predicted, the results suggest that auditors using (not using) structured RCA are more (less) likely to identify control‐related root causes of a financial misstatement and judge the misstatement to be more (less) material. Also consistent with our prediction, we find that the assessed severity of identified control deficiencies mediates RCA's effect on materiality judgments. Finally, the materiality judgment results reveal the expected significant interaction between structured RCA method and auditor cognitive style, suggesting the importance of allowing flexibility in the specific RCA method applied in practice. Overall, the study's results provide evidence that auditor use of RCA as a judgment framework prompts deeper evaluation of audit findings and stronger consideration of critical links between financial reporting and related internal controls in integrated audit settings.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 180065, “Thermal Effects on Subsea Wellhead Fatigue During Workover Operations,” by L. Cantinelli Sevillano, J. De Andrade, S. Sangesland, and M. Stanko, Norwegian University of Science and Technology, prepared for the 2016 SPE Bergen One Day Seminar, Bergen, Norway, 20 April. The paper has not been peer reviewed. Intervention and workover operations can significantly affect the structural integrity of subsea-wellhead systems with regard to their fatigue life. The increasing frequency of these operations has called for a renewed focus on the fatigue capacity of subsea wells, which has greatly improved the overall methodology used for wellhead-fatigue analysis. However, thermal effects along the well have yet to be incorporated. This paper analyzes wellhead-fatigue damage during a workover operation considering the thermal effects. Methodology The goal of the present study is to investigate the effects of the temperature variation along the well on wellhead-fatigue- damage rates by incorporating the temperature profiles of casing strings and cement into the fatigue-damage assessment of a particular wellhead system during a workover operation. In this study, a decoupled approach is proposed. The temperatures of riser, wellhead, and well components are calculated for different instants during the workover operation using a finite-difference method. Then, the temperature profiles for a given moment during the operation are incorporated into a 3D finite-element model (FEM) of the wellhead system. A structural analysis with focus on stresses at the fatigue hot spots is performed. Subsequently, a dynamic analysis of the riser provides the loading time history to which the wellhead is subjected; finally, combining the results of the structural analysis and the riser-response analysis enables the fatigue damage during the simulated operation to be estimated. The well adopted in this study follows a conventional subsea-completion program on the Norwegian continental shelf, with four casing strings and a production liner. Temperature Calculations. It is assumed that enough time has passed—between the shutting down of production and the moment that the workover riser is connected to the wellhead and the workover operation begins—for the temperature in the well to reach the undisturbed geothermal temperature profile. The workover operation simulated for temperature calculations consisted of injecting and circulating a heavy fluid until the hydrocarbons in the well were displaced. After that, circulation was stopped. The temperature profiles were calculated with a finite-difference method. During the simulated cold-fluid injection into the well, the deepest sections of the well are subjected to the largest temperature drop, given that the fluid is at lower temperature than the surrounding formation and well fluid, while the uppermost sections experience the effects of a circulating fluid at a higher temperature. Circulation was deemed to last approximately 3 hours.

Developing a Tool for Assessing Competency in Root Cause Analysis

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 there were 80 and 40 dispensing errors which met the study criteria, respectively. Results: Crude incidence of dispensing errors before and after RCA were 2.54 per 1000 (95%CI: 1.98-3.10) and 1.26 per 1000 (95%CI: 0.87-1.65), respectively. The decrease in dispensing error after RCA was 50.39%. The ratio of dispensing error incidence rates after and before the RCA is 0.49. Significant decrease in the incidence of dispensing errors was only found in drug identity errors of 1.27 per 1000 (95%CI: 0.88-1.66) before an RCA and 0.06 per 1000 (95%CI: -0.03-0.15) after RCA, or decreased by 95.27% and there was no significant decrease in other dispensing errors. Conclusion: The decrease of dispensing errors after the RCA was only found in the medication identity error and not found in the other dispensing errors. Direct observation and intensive supervision are needed in order to accurately calculate and reduce the incidence of dispensing errors.

Root cause analysis (RCA) is widely used to investigate adverse events in health care and is mandated by many organizations and governments. RCA employs a combination of techniques to establish the factors contributing to a harmful outcome. Once the factors are identified, then interventions are usually designed in order to prevent further harms from occurring. Prior to deciding which intervention(s) to implement, we must make judgements of causal importance in the context of multiple, interacting conditions. Clearly, we must take action to prevent adverse events, but we need not take action against every contributing cause. I aim to show that many causal factors can be identified by RCA, but current approaches do not adequately distinguish among these causes, leaving numerous potential targets of intervention. I argue that this is because the literature on RCA (with few exceptions) has largely neglected the literature on philosophy of causation and explanation. In this paper, I focus on demonstrating how Strevens' kairetic approach to explanation and Tinbergen's four questions to explain behaviour have the potential to work synergistically with the present RCA methods. There are important lessons we can bring to RCA from the literature on causation and explanation, particularly from the philosophy of science and biology. This work could enhance the effectiveness of RCA by identifying and understanding the causes that really make a difference to adverse events. This ought to reduce the number of targets and focus intervention following RCA.

While root cause analysis (RCA) is used to analyze medical errors with a systems approach, evidence demonstrating its effectiveness in reducing patient harm remains sparse. The heterogeneity of the RCA methodology at different health care organizations has posed challenges to studying its value. The Department of Veterans Affairs (VA) has an established and standardized RCA approach, making it an ideal context to study RCA's impact. This review assessed whether implemented interventions recommended by RCAs were effective in mitigating preventable adverse events at the VA. PubMed, Web of Science, CINAHL and Business Source were searched for studies on RCAs performed at the VA that evaluated effectiveness of interventions and were published between 2010 and 2020. The Appraisal Tool for Cross-sectional Studies (AXIS) was used to assess bias of bias. The majority of studies eliminated during our eligibility process reported on RCAs without attention to their specific impact on patient safety. Ten retrospective studies met inclusion criteria and were part of the final review. Studies were grouped into adverse events related to incorrect surgical/invasive procedures, suicides, falls with injury, and all-cause adverse events. Six studies reported on effectiveness by demonstrating quantitative changes in adverse events over time or by location following a specific intervention. Four studies reported on the effectiveness of implemented interventions using a facility-based rating of "much better" or "better." Of the studies included in this review, all reported improvements following interventions implemented after RCAs, but with variability in study definitions and methodology to assess effectiveness. Increased reporting of outcomes following RCAs, with an emphasis on quantitative patient-related outcome measures, is needed to demonstrate the impact and value of the RCA.

<h3>Background</h3> Following the introduction of a new iodine-containing contrast medium (IC) (iomeprol) to our hospital formulary, an unexpected increase in adverse drug reactions (ADRs) to the IC was observed. Consequently, a root cause analysis (RCA) was made to identify the causes of adverse events, and to suggest improvements to prevent recurrences. <h3>Purpose</h3> To determine the corrective measures resulting from an RCA to investigate the unexpected increase in ADRs associated with the introduction of a new IC (iomeprol) in the hospital, and to evaluate the effectiveness of measures implemented. <h3>Material and methods</h3> The study was made in a 460-bed specialty hospital. The RCA multidisciplinary team was composed of medical and nursing directors and supervisors of radiology and pharmacy units. Steps followed in RCA involve: 1-problem description and data collection, 2-organisational system analysis, 3-human factor analysis, 4-team and material management analysis, 5-patient-related factors analysis, 6-RCA team proposal. The monthly number of ADRs notified before and after RCA was used to assess the effectiveness of corrective measures. Notifications of IC ADRs were extracted from the records of yellow card reports, as well as patient data, drug data and ADR data. <h3>Results</h3> Proposals generated by RCA were: 1-to retrain radiology technicians and doctors on the use of IC pumps for administration, 2-to inspect pump calibration, 3-to verify the premedication needed. In the period 2009–2012 average notification of IC ADRs was 0.87/month. Since iomeprol was introduced in 2013/03 until RCA was performed (2013/05/08) 9 notifications were recorded (6/month); type and severity were similar to the previous period. Retraining and pump calibration inspection were finalised in June. The average IC ADR notification rate in the period July–December 2013 was 1.67/month. In the period January–October 2014, the notification rate was 0.89/month, similar to that before introduction of the new IC. <h3>Conclusion</h3> 1. Technical training, machine calibration and patient evaluation were identified by RCA as aspects to improve. 2. After corrective measures had been taken, IC RCA notification has returned to the usual value. <h3>References and/or acknowledgements</h3> No conflict of interest.

Adverse events reportedly occur in 5% to 10% of health care episodes. Not all adverse events are the result of error; they may arise from systemic faults in the delivery of health care. Catastrophic events are not only physically devastating to patients, but they also attract medical liability and increase health care costs. Root cause analysis (RCA) has become a key tool for health care services to understand those adverse events. This study is a review of all the RCA case reports involving neurosurgical patients in New South Wales between 2008 and 2013. The case reports and data were obtained from the Clinical Excellence Commission database. The data was then categorized by the root causes identified and the recommendations suggested by the RCA committees. Thirty-two case reports were identified in the RCA database. Breaches in policy account for the majority of root causes identified, for example, delays in transfer of patients or wrong-site surgery, which always involved poor adherence to correct patient and site identification procedures. The RCA committees' recommendations included education for staff, and improvements in rostering and procedural guidelines. RCAs have improved the patient safety profile; however, the RCA committees have no power to enforce any recommendation or ensure compliance. A single RCA may provide little learning beyond the unit and staff involved. However, through aggregation of RCA data and dissemination strategies, health care workers can learn from adverse events and prevent future events from occurring.

BackgroundConducting root cause analysis (RCA) is complex and challenging. The aim of this study was to better understand the experiences of RCA team members and how they value their involvement in the RCA to inform future recruitment, conduct and implementation of RCA findings into clinical practice.MethodsThe study was set in a health network in Adelaide, South Australia. A qualitative exploratory descriptive approach was undertaken to provide an in-depth understanding of team member’s experience in participating in an RCA. Eight of 27 RCA team members who conducted RCAs in the preceding 3-year period were included in one of three semi-structured focus groups. Thematic analysis was used to synthesise the transcribed data into themes.ResultsWe derived four major themes: Experiences and perceptions of the RCA team, Limitations of RCA recommendations, Facilitators and barriers to conducting an RCA, and Supporting colleagues involved in the adverse event. Participants’ mixed experience of RCAs ranged from enjoyment and the perception of worth and value to concerns about workload and lack of impact. Legislative privilege protecting RCAs from disclosure was both a facilitator and a barrier. Concern and a desire to better support their colleagues was widely reported.ConclusionsClinicians perceived value in reviewing significant adverse events. Improvements can be made in sharing learnings to make effective improvements in health care. We have proposed a process to better support interviewees and strengthen post interview follow up.

BackgroundDespite over a decade of efforts to reduce the adverse event rate in healthcare, the rate has remained relatively unchanged. Root cause analysis (RCA) is a process used by hospitals...

The identification of defect causes plays a key role in smart manufacturing as it can reduce production risks, minimize the effects of unexpected downtimes, and optimize the production process. This paper implements a literature review protocol and reports the latest advances in Root Cause Analysis (RCA) toward Zero-Defect Manufacturing (ZDM). The most recent works are reported to demonstrate the use of machine learning methodologies for root cause analysis in the manufacturing domain. The popularity of these technologies is then summarized and presented in the form of visualizing graphs. This enables us to identify the most popular and prominent methods used in modern industry. Although artificial intelligence gains more and more attraction in smart manufacturing, machine learning methods for root cause analysis seem to be under-explored. The literature survey revealed that only limited reviews are available in the field of RCA towards zero-defect manufacturing using AI and machine learning; thus, it attempts to fill this gap. This work also presents a set of open challenges to determine future developments.

Objective To explore the effect of root cause analysis(RCA) on reducing the turnover rate of nurse staff from a tertiary stomatology hospital. Methods It was collected that the nurses in Stomatological of Chongqing Medical University from January 2012 and December 2016. 2015-2016, using the method of RCA scientific management, establishment of RCA team, the reason of high turnover rate of nurses were analyzed using RCA method, the improvement plan was worked out. It was analyzed that the nurses turnover rate before and after improvement plan. Results The turnover rate of nurses was 9.35%, 12.30%, 13.70%, 4.23% and 5.05% respectively from 2012 to 2016. From 2012 to 2014, the total number of nurses was 971, with a total turnover of 113 and an average turnover rate of 11.80%. From 2015 to 2016, the total number of nurses was 831, with a total turnover of 37, an average turnover rate of 4.66%, Comparing the turnover rate from 2012 to 2014, the average turnover rate was reduced significantly after improvement, the difference was statistically significant (χ2=29.292, P<0.005). Conclusion RCA is a scientific method in the management of nursing human resources. RCA method can solve the problem of high turnover rate of nurse staff to reduce the loss of the oral specialized nurse. Key words: Root cause analysis; Stomatology hospital; Specialized nurse; Turnover rate

Root Cause Analysis (RCA) has been recommended as a specific problem-solving approach for addressing disproportionate discipline outcomes. RCA differs from other problem-solving models through its in-depth analysis that draws from the perspectives of individuals who are impacted by the issue being addressed. When applied to disproportionate discipline, this means that RCA would include perspectives from all school staff, as well as students and families who are over-represented in discipline outcomes. This paper describes an approach to conducting RCA and presents two case studies that illustrate what stakeholders may gain by incorporating RCA into a school’s efforts to increase disciplinary equity. Suggestions for first steps school teams can take to conduct a root cause analysis will be provided.

The Theory of Constraints was used as a method in a root cause analysis (RCA) to identify system performance bottlenecks, wherein the constraint with the strongest correlation with system performance is identified as the bottleneck. In the present study, this method was applied in a large district cooling plant to diagnose steam absorption chillers’ performance anomalies including performance deterioration, spikes, large variation, etc. Many root causes were identified through a ten months’ continuous diagnosis, such as drastic reduction in chilled water flow rate, faulty steam control valve, cooling demand reduction, etc. More than 30 anomalies were diagnosed and more than 80% diagnosis accuracy was achieved. The diagnosis results were verified by the plant operator, which proved the effectiveness of the Theory of Constraints as a method for root cause analysis in diagnosing anomalies in district cooling plant operations. It was however discovered that even though the operational component identification accuracy was high, the determination of the actual root cause still presents lots of challenges, due to the large set of domain knowledge and operation conditions required. A knowledge-based supporting tool may be needed as part of the RCA to facilitate a speedy and complete analysis to enable these anomalies to be resolved.