A Perspective on DSN System Performance Analysis

This paper describes the implementation of a performance analysis (PA) review and a comprehensive root cause failure analysis (RCFA) for the artificial lift system (ALS) failures in heavy oil wells. The subject wells, located in Egyptian Eastern Desert (EED), have been operated by Canadian-Egyptian joint venture. Progressive cavity pump (PCP) and beam pump (BP) have been selected as the preferred ALS methods. With the objective of improving ALS performance, RCFA identifies the main causes of ALS failures and proposes guidelines and recommendations with a new open source service for the current and future development for EED Oil companies. PA has been applied using some Key Performance Indicators (KPI), such as: failure index, recurrence index, and average run life in order to track all failed and crucial issues. RCFA has been applied to different ALS, such as: BP and PCP. Therefore, the definition or limitation of the boundaries of each system and the classification of failures were performed. RCFA covered failures between 2012 and 2018 for average 150 active wells and 622 failures. Finally, the new open source service applied as a trial to evolve the failure tracking and decision making methodology. PA review showed a high failure and recurrence index that reached 3.0 and 3.7, respectively, in 2014 then declined to 1.0 and 1.7, respectively, in 2017 as a result of comprehensive corrective actions implemented. RCFA showed that rod string failure in BP was and still is a dominant failure with 200 failures over the last six years. Moreover, Down-hole pump failure in PCP was the major PCP failure system although its failures declined from 80 failures in 2014 to 14 failures in 2018. Several field cases were presented to cover the dominant cause of failures for both BP and PCP wells. Most wells had a significant improvement in their mean time to failure (MTTF) after reviewing design, installation and operation procedures. The procedure for carrying out this methodology and implementing lessons learned has been presented in this paper. In addition, the new open source integration service provides an increased visibility about individual well performance issues and more broadly, about field performance and ALS failures.

Root Cause Failure Analysis (RCFA) is a method used by maintenance and reliability industry professionals as one of the key tools to drive improvement. This book offers a quick guide to the applications involved in performing a successful RCFA by providing a foundational view of maintenance and reliability strategies. It also highlights the practical applications of RCFA and identifies how to achieve a successful RCFA, as well as discussing common equipment failures and how to solve them. Case studies on topics including pump system failure analysis and vibration analysis are included. Suggests examples on how to solve common failure on many types of equipment, including fatigue, pumps, bearings, and mechanical power transmission Highlights practical applications of RCFA Identifies key elements for how to achieve a successful RCFA Presents case studies on topics including pump system failure analysis and vibration analysis The book is a must-read for any reliability engineer, particularly mechanical reliability professionals.

With the astronomical growth in online presence vis-a-vis the IT industry across the globe, there is an urgent need to evolve cloud based DataCenter architectures that can rapidly accommodate web application integrations which can serve the energy industries, educational sector, finance sector, manufacturing sector, etc. Previous works in DataCenter domain have not investigated on cloud based DataCenter Servercentric characteristics for evaluation studies. This paper then proposed a Reengineered DataCenter (R-DCN) architecture for efficient web application integration. In this regard, attempt was made to address network scalability, efficient and distributed routing, packets traffic control, and network security using analytical formulations and behavioural algorithms having considered some selected architectures. In this work a simulation experiment was carried out to study six key performance metrics for all the architectures. It was observed that the network throughput, fault-tolerance/network capacity, utilization, latency, service availability, scalability and clustering effects of R-DCN responses with respect to above Key Performance (KPIs) metrics were satisfactory when compared with BCube and DCell architectures. Future work will show a detailed validation using a cloud testbed and CloudSim Simulator.

Modern large frame F, G, & J class gas turbine flow path component design requires the complex integration of multiple design disciplines that traditionally reside with distinct specialists. A traditional design system for an actively cooled gas turbine blade includes aerodynamicists, heat transfer engineers, structural engineers and a failure or lifetime prediction engineers passing information through a manual process with a small number of iterations between the disciplines. Design or manufacturing engineers can also be involved ensuring manufacturability and policing best practices in a predominantly deterministic design system. Over the past few decades robust design or probabilistic design philosophies along with cluster computing advancements have accelerated the release of commercial software that allows for the automation of multiple analytical evaluations at off design points. These software codes allow for process automation of several independent codes executed multiple times at various conditions for automated design of experiment (DOE), and reliability analysis using Monte Carlo or other advanced approximate probabilistic methods across the entire design system. In this paper, the authors are presenting a novel approach of using a commercially available process integration tool to fully integrate a series of other commercially available tools for a root cause failure analysis of a F class turbine blade rather than a new make design. The analysis incorporated a computational fluid dynamics model (CFD) to define inlet temperatures and pressure profiles, a fully conjugate thermal analysis interacting with a finite element (FEA) solver linked to a proprietary creep lifetime prediction model. A DOE was executed to define the meaningful parameters and help rule out potential causes of failure such as loss of coating or compromised cooling system as a contributing factor of the failure which greatly reduced the amount of time and money needed for the investigation. A probabilistic failure analysis was then executed and surrogate models created for quick probabilistic assessment for different operating conditions. This allowed for validation against fleet history to explain the single engine failure not previously observed. Setting up the non-deterministic models initially allowed for rapid redesign in less than 1 month time with confidence that the true root cause was identified and mitigated. It further allowed for feedback and calibrations to the traditional design system methodology.

Defect isolation and failure analysis is a key factor that drive development and manufacturing yield improvements in semiconductor packaging industry. From a manufacturing point of view, ensuring adequate package reliability is becoming more challenging due to increasing packaging complexity and a more pronounced impact from material physical property mismatch among packaging materials and components. The task of isolating defects and finding root cause is further complicated by ever shrinking feature sizes within the device and/or package, already approaching the nanometer range in contemporary semiconductor packages. Conventional failure analysis techniques such as physical cross sectioning or micro-cutting using focused ion beams(FIB) are sometimes no longer sufficient to find these defects. Both physical cross section and FIB are only capable of exposing the defect in two dimensions (x and y directions), which makes pinpointing the defect in depth, i.e., the z direction, extremely difficult when dealing defects with micron and submicron size. Additional complications are many times introduced during conventional sample preparation, which can introduce undesirable artifacts associated with the module and/or device depackaging. These artifacts may mask the true defects, or lead to misinterpretation of the true cause of failure. In this work, it has been determined that a three-dimensional failure analysis method is critical for finding some defects in silicon packages. For example, xenon difluoride (XeF2) has excellent selectivity to silicon and provides efficient material removal by chemical reaction, generating gaseous by-products that can be readily exhausted [1]. Furthermore, XeF2 has very little reaction with non-silicon materials, such as SiO2, and the metals and polymers commonly used in semiconductor devices and packages. This paper reports the application of XeF2 as an effective failure analysis technique to reveal defects in silicon packages. The mechanism of selective reaction between XeF2 and Si is discussed and key design features of the failure analysis tool are presented. The paper also highlights a few case studies which advantageously utilize XeF2 etching to expose defects. XeF2 was especially effective in detecting the source of electrical leakage in 3D packages having Through Silicon Via (TSV) structures. Due to its high etching selectivity to silicon, the leakage area in electrically failing samples was found to be due to damage of the TSV liner (passivation layer material) and further analysis reveals a three dimensional view of the TSV defect. With the addition of XeF2 etching, further characterization of defects by traditional methods such as FIB micro cutting also becomes more practical. The work suggests that a wider application of Si removal via XeF2 can be achieved by combining mechanical milling of bulk silicon followed by a final, low stress, silicon removal by XeF2 etching.

In 2017, Uber announced it had a “broken relationship” with its drivers. Yet what broke the relationship and what effect might it have on Uber’s organizational performance? This paper is a mixed-methods study of how conflict impacts the relationship between platforms and drivers. First, by drawing on 55 original interviews with rideshare drivers, this paper identifies conflict triggers that damage the relationship between platforms and drivers. Second, this paper uses new time diary data from 490 Uber, Lyft, Juno, and other Transportation Network Company (TNC) drivers from across the United States to empirically test if these conflict triggers are associated with key TNC performance metrics. Specifically, this paper finds that a “broken relationship” is associated with drivers withholding their working time from Uber and allocating it toward their competitor, Lyft. Additionally, this paper finds that drivers who have a broken relationship with Uber are more likely to recruit (‘steer’) passengers toward Lyft. These behaviors provide a link between organizational conflict and key performance metrics in the ‘gig economy.’

In this study, we conducted a comprehensive DC and AC analysis of Gate-All-Around (GAA) devices, focusing on the implications of increased gate capacitance both for wider and narrower device on key performance metrics. Our findings reveal that the elevated gate capacitance due to thin GaN cap layer significantly affects the transconductance (gm), Drain-Induced Barrier Lowering (DIBL), subthreshold swing (SS) and the on/off current ratio (Ion/Ioff). A new analytical linkage is formulated connecting gate capacitance ( C g ) with key DC performance metrics. The results indicated a significant enhancement in both ft and fmax, attributed to the high Ion/Ioff ratio of 1.72 × 10 13 , confirming the superior high-frequency performance of GAA structures. Our analysis underscores the critical role of gate capacitance in optimising the electrical characteristics of GAA devices, paving the way for their application in 5G wireless communication.

Historically, the most common failure analyses metrologies have been dye-and-pull, cross-sections, microscopy, optical and SEM. Using these traditional metrologies to find a root cause from a dynamic event can be very time consuming and sometimes inconclusive. The standard methodology is to work backward to reconstruct the “event” that caused or initiated failure. Often times the root cause is not immediately obvious and design improvements require an iterative process to identify the true root cause. This approach is costly in time, materials and resources. A high speed camera (HSC) allows identification of failure from a point of initiation. Using the point of initiation concept with reconstructive modeling allows a design team to discover potential initiating sources and better match a cause to the effect and implement corrective action. This decreases development time, minimizing product design cycle and increases market opportunities.

Gas engine power plant (PLTMG) is a power plant that uses a gas engine as the prime mover. Prime mover is equipment that has the function of generating the mechanical energy needed to rotate the generator rotor. The Arun PLTMG uses a type 20V34SG wartsila gas engine as the main engine. The 20V34SG type Wartsila engine has replaced several components but has not made the engine performance efficient again. One of the important components in supporting the electricity production process is the turbocharger. A turbocharger is a centrifugal compressor that gets power from a turbine whose power source comes from vehicle exhaust fumes. Usually used in internal combustion engines to increase power output and engine efficiency by increasing the air pressure entering the engine. The purpose of this paper is to calculate the efficiency of the equipment and analyze the results using the RCFA (Root Cause Failure Analysis) method to find out the basic problems that occur in the turbocharger. Based on the results of the calculation analysis showed that the lowest efficiency value for turbocharger A occurred in engine 14, which was 57%, and for turbocharger B efficiency, it was found in engine 13, which only reached 54%. By observing in the field there is oil seepage from the turbocharger which falls into the charge air cooler (CAC) area, wear and tear on the impeller mechanical sealing.

The purpose of this paper is to establish a basis for a criticality analysis, considered here as a prerequisite, a first required step to review the current maintenance programs, of complex in-service engineering assets. Review is understood as a reality check, a testing of whether the current maintenance activities are well aligned to actual business objectives and needs. This paper describes an efficient and rational working process and a model resulting in a hierarchy of assets, based on risk analysis and cost–benefit principles, which will be ranked according to their importance for the business to meet specific goals. Starting from a multi-criteria analysis, the proposed model converts relevant criteria impacting equipment criticality into a single score presenting the criticality level. Although detailed implementation of techniques like root cause failure analysis (RCFA) and reliability centered maintenance (RCM) will be recommended for further optimization of the maintenance activities, the reasons why criticality analysis deserves the attention of the engineers, maintenance and reliability managers are here precisely explained. A case study is presented to help the reader to understand the process and to operationalize the model.

This paper will present the design, manufacturing, testing and validation of the canned motor pump (CMP) as an alternative to typical electric submersible pump (ESP) systems to produce oil and gas with the goal of developing a robust system to extend the ESP run-life. The CMP technology is a seal-less topology currently employed in demanding applications including highly abrasive radioactive slurry service. This subsea system leveraged knowhow developed in other demanding applications and is adapted for ESP caisson applications. The canned motor ESP development included mockups to validate design features and manufacturing processes. A CMP system was manufactured and tested at the vendor's facility with water and at the end user's test facility with multiphase and viscous fluids. Unit validation included rigorous multiphase testing with fluid viscosities ranging from 2 cP up to 300 cP and varying gas volume factions at different speeds. The typical electric submersible pump has an average run life of approximately 2.5 years in subsea caisson applications. Root Cause Failure Analysis (RCFA) on current ESP systems has revealed that a majority of failures result from the protector seal and motor. The main function of the seal section is to protect the motor and thrust bearings from contamination by the process fluid. The CMP seal-less technology eliminates the need for a protector seal section and dielectric fluid by isolating the wound stator with a corrosion resistant liner and a thrust bearing system that operates in process fluid. This paper will include test data results from thrust bearing testing in varying conditions including multiphase fluid to demonstrate robustness and unit performance test results from testing in water and multiphase fluid with varying viscosities. The canned motor ESP provides a new approach for subsea caisson applications by eliminating the protector seal section and incorporating process lubricated thrust bearings. This paper will share background, learnings, and results that demonstrate that the canned motor pump technology is ready for deployment in a subsea ESP caisson.

This study aims to analyze the causes of component failure in the Power Train system of unit OHT773E CO2278 at PT. Cipta Kridatama, Samarinda, using the Root Cause Failure Analysis (RCFA) method. The Power Train system is responsible for transferring power from the engine to the final drive and other components, making it critical for the operational success of heavy equipment. Therefore, optimal maintenance is essential to prevent fatal failures that could impact the unit's performance. Based on the analysis, the dominant cause of failure is human factors, particularly technician negligence during component installation. This negligence results from a lack of understanding of the procedures and specifications recommended by the manufacturer, leading to incorrect installation of components. This failure impacts the achievement of the component’s expected lifetime, thus shortening the operational life of the components and increasing the risk of more severe damage. This also leads to higher repair costs and reduced unit productivity, resulting in longer downtime. To address this issue, several preventive measures are recommended, such as regular training for technicians to enhance their understanding of correct procedures and specifications, as well as the importance of following manufacturer guidelines during every maintenance and installation process. Additionally, it is advised to conduct routine discussions between technicians and supervisors to ensure that every maintenance step and installation complies with the established procedures. Increased oversight of the installation and maintenance process is also necessary, along with periodic rejuvenation of components to ensure the optimal performance of the Power Train system. Strengthening Preventive Maintenance (PM) practices is also crucial to minimize future damage potential. Implementing these solutions is expected to enhance the reliability of the Power Train system, extend component lifespan, and reduce failure frequency, ultimately improving the overall efficiency and productivity of the company.

Surface Controlled Subsurface Safety Valves (SCSSV) is a critical completion accessory to maintain the Safe Operation Envelope (SOE) of the well and ensuring the production sustainability. In PCSB, it is a requirement that SCSSVs are tested on specific periods to ensure this safety device meet the acceptance requirement as per company guideline. Monitoring and maintaining the SCSSVs is proven to be challenging for E1 gas fields, located in Offshore Malaysia. Wells in E1 field, recently transferred operatorship, is an aging field producing since August 1982. The wells are equipped with Wireline Retrievable SCSSV (WRSCSSV). Within few months after operating this well, few cases of SCSSVs inoperability were encountered, resulted in significant gas production loss from E1. The main problems with SCSSV are: Control line hydraulic pressure unable to build up and maintain, hence unable to flow the well as SCSSV unable to open. Abnormal hydraulic return observed. E11 wells tripped due to Wellhead Control Panel Hydraulic pressure header hit low-ow trip setpoint. Inoperable after well close in, indication of control line leak. Immediate action taken to rectify include retrieving the WRSCSSV and installing redressed old WRSCSSV, injecting and displacing of Pressure Activated Sealant through control line to patch leak point. Root Cause Failure Analysis (RCFA) conducted on the wells identified preliminary factors that lead to E1 SCSSV issues: Frequent SCSSV cycling with high control line pressure in depleted well pressure (Frequent well tripping and monthly Corrosion Inhibitor batching activity requires close in and opening of SCSSV). Non-compatible SCSSV elastomeric parts with production & CI batching chemical. Wear & tear and corrosion due to valve age (manufactured in 1982 & 1985). Worn out seal bore of BP-6 landing nipple. Short term solution such as reviewing the recommended hydraulic line opening pressure, downhole visual inspection, pressure activated sealant and caliper survey to confirm BP-6 Landing Nipple seal bore damage, Swellable Packer/O-ring (External) and re-dress using non-upgraded Elastomers (Internal) had been planned. Contingency for subsurface controlled SSV and replacement using new WRSCSSV had been put in place as long-term solution. This paper describes operator experience in managing the challenges in maintaining SCSSV operability, diagnostic and solution recommended to avoid production deferment due to this issue.

Well integrity management for High Temperature (HT) wells can be challenging due to stresses and cyclic behaviour during thermal expansion or corrosive stress cracking that may impact the fatigue life of wellhead, tubing and casing. The impact can be catastrophic and detrimental to production sustainability and surrounding asset. This paper discussed operator’s experience and case studies in managing well integrity issues while operating HT wells in two fields, Field X and Field Y, located in offshore Malaysia. Field X and Field Y in offshore Malaysia, consists of five prolific High Temperature (HT) gas producers respectively, with temperature exceeding 300⁰F. For Field X, since its first gas delivery in 2017, well integrity issues include the incident of wellhead seals failure, wellhead tilting, abnormal conductor growth, tubing leaks and Drive Pipe Housing Head (DPHH) sliplock issues, resulted in production deferment and loss of primary containment. Meanwhile, for Field Y, the wellhead growth issue was observed only recently, end of 2021, after wells were on production for almost 2 years since 2020. The sudden movement has impacted the flowline to bend and expose the surface system to disastrous situation. Subsequently, the platform was on total shut down for a few days and led to unplanned production deferment and penalty due to production commitment. Analysis for WELLCAT and wellhead design has shown minimal concern on the wellhead growth but restriction on the surface line has caused production curtailment. To-date, the only identified issue is on the relative pattern of Flowing Tubing Head Pressure (FTHP) vs the wellhead growth. Proactive and reactive measures are implemented including in-depth Root Cause Failure Analysis (RCFA) to understand gaps and mitigation required, which provide imperative insight and benchmark on strategies to manage HT wells. The key issues and observations based on operator’s experience in managing HT wells include: Impact of cement integrity and cyclic load on wellhead growth and axial load exerted on wellhead.Oxygen corrosion of tubing causing intergranular corrosion weakening the tubing wall due to wellhead failure.Possible stress corrosion cracking resulted from wellhead tilting and growth.Wellhead design and acceptance requires validation on cyclic load and analysis on the capacity of sliplock to cater axial load at 30" conductor.Surface system modification requirement including flowline to cater for the bending effect caused by the growth. This paper also highlighted preventive, monitoring practices and technology application to rectify well integrity issues in HT wells at Field X. Discussion on wellhead maintenance scope, nitrogen injection in annulus, tubing corrosion management and bracing support to address abnormal wellhead growth.

Failure analysis plays an important role in yield improvement during semiconductor process development and device manufacturing. It includes two main steps. The first step is to find the defect and the second step is to identify the root cause. In the past, failure analysis mainly focused on the first step, namely how to find the defect for a failure; because in the previous generations of technology, once the defect was found, its root cause was relatively easy to be understood. As the current advanced semiconductor technology has become tremendously complicated, especially 3D devices, like FinFET, a defect found by failure analysis can be substantially transformed from its original defect by subsequent processes and can be totally different from its origin in size and shape. Thus, sometimes, the second step, identifying the root cause for a defect becomes more challenging and takes more time than the first step. With combination of failure analysis and inline inspection, it enables us to establish the relationship between the failure analysis defect and an in-line defect. This can link the defect for a device functional failure to its source layer and process step more quickly, leading to fast root cause identification. In this paper, the methodology was validated by fast identification of the root causes for three case studies in the latest FinFET technology.