Continuous Performance Improvement Research Articles

An adaptable end-to-end maintenance performance diagnostic framework

PurposeThis paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.Design/methodology/approachThe case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.FindingsTo improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.Originality/valueMethodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.

Wave‐based inversion at scale on graphical processing units with randomized trace estimation

AbstractThanks to continued performance improvements in software and hardware, wave‐equation‐based imaging technologies, such as full‐waveform inversion and reverse‐time migration, are becoming more commonplace. However, widespread adaptation of these advanced imaging modalities has not yet materialized because current implementations are not able to reap the full benefits from accelerators, in particular those offered by memory‐scarce graphics processing units. Through the use of randomized trace estimation, we overcome the memory bottleneck of this type of hardware. At the cost of limited computational overhead and controllable incoherent errors in the gradient, the memory footprint of adjoint‐state methods is reduced drastically. Thanks to this relatively simple to implement memory reduction via an approximate imaging condition, we are able to benefit from graphics processing units without memory offloading. We demonstrate the performance of the proposed algorithm on acoustic two‐ and three‐dimensional full‐waveform inversion examples and on the formation of image gathers in transverse tilted isotropic media.

Blood culture contamination in a tertiary care hospital: a retrospective three-year study

BackgroundBloodstream infections (BSI) are a leading cause of morbidity and mortality in hospitalized patients worldwide. A blood culture is the primary tool for determining whether a patient has BSI and requires antimicrobial therapy, but it can result in an inappropriate outcome if the isolated microorganisms are deemed contaminants from the skin. Despite the development of medical equipment and technology, there is still a percentage of blood culture contamination. The aims of this study were to detect the blood culture contamination (BCC) rate in a tertiary care hospital in Palestine and to identify the departments with the highest rates along with the microorganisms isolated from the contaminated blood samples.MethodBlood cultures that were taken at An-Najah National University Hospital between January 2019 and December 2021 were evaluated retrospectively. Positive blood cultures were classified as either true positives or false positives based on laboratory results and clinical pictures. Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS) version 21. A p-value of less than 0.05 was considered statistically significant for all analyses.ResultsOut of 10,930 blood cultures performed in the microbiology laboratory from 2019 to 2021, 1479 (13.6%) were identified as positive blood cultures that showed microbial growth. Of these, 453 were blood culture contaminations, representing 4.17% of total blood cultures and 30.63% of the positive blood culture samples. The highest rate of contamination was in the hemodialysis unit (26.49%), followed by the emergency department (15.89%). Staphylococcus epidermidis was the most prevalent (49.2%), followed by Staphylococcus hominis (20.8%) and Staphylococcus haemolyticus (13.2%). The highest annual contamination rate was observed in 2019 (4.78%) followed by 2020 (3.95%) and the lowest was in 2021 (3.79%). The rate of BCC was decreasing, although it did not reach statistically significant levels (P value = 0.085).ConclusionThe rate of BCC is higher than recommended. The rates of BCC are different in different wards and over time. Continuous monitoring and performance improvement projects are needed to minimize blood culture contamination and unnecessary antibiotic use.

Provider Awareness of Postpartum Hemorrhage Risk Assessment Tool at the Time of Admission at a Community Setting

Objectives: The primary objective of this study was to determine the provider's awareness of the postpartum hemorrhage risk assessment tool at the time of admission. In addition, in keeping with the organization’s continual performance improvement philosophy, education on postpartum hemorrhage risk was provided to survey respondents who self-reported that they were unaware or requested additional resources. Methods: This cross-sectional study utilized an anonymous survey methodology. We distributed a postpartum hemorrhage awareness risk assessment questionnaire and collected participant responses without personal identifiers over a 3 month time period, January 2023 – March 2023. Analysis was completed using Fischer’s exact test. Alpha level was set to 0.05. Results: 39 participants completed the questionnaire attending physicians: n=10 (25.6%), nursing staff: n=15 (38.5%), and resident physicians: n=14 (35.9%). 7 of the 10 attending physicians (70%) and 9 of the 15 nursing staff (60%) have worked over 10 years in their profession, while 11 of the 14 resident physicians (78.6%) have worked in their profession for 1-5 years (p=<0.0001). 5 of the 10 attending physicians (50%) and 7 of 15 nursing staff (46.7%) were 36-50 years old, while 13 of 14 resident physicians (93%) were 25- 36 years old (p=<0.0001). Majority of the participants were White; 5 attending physicians (50%), 11 nursing staff (73.3%), and 9 resident physicians (64.3%). Nursing staff had the most awareness of the postpartum hemorrhage awareness risk assessment tool at the time of admission (100%) in comparison with attending physicians (50%) and resident physicians (64.3%), (p=0.005). Nursing staff had the most knowledge of where to access the assessment (93.3%) in comparison to attending physicians (10%) and resident physicians (0%), (p=<0.0001). Conclusions: Our study revealed a statistically significant difference in awareness of the postpartum hemorrhage risk assessment tool at the time of admission amongst the 3 groups of providers; attending physicians, nursing staff, and resident physicians. The nursing staff had the most awareness in comparison with other providers. The data also highlighted the inconsistencies with accessing the risk assessment and with communication of information obtained through the assessment among providers. A quality improvement project should involve notifying providers of patients that are stratified to high risk, developing a simpler method for all providers to readily access the risk assessment tool, and increasing preparedness by creating an algorithm or bundle.

Lightweight image de-snowing: A better trade-off between network capacity and performance

The single image de-snowing task is an essential topic in computer vision, as images captured on snowy days degrade the performance of current vision-based intelligent systems. Existing methods build complex network structures with numerous parameters to pursue continuous performance improvement. Nonetheless, they generally ignore the negative impact of large memory consumption in real applications. This paper aims to address the above problem by making a trade-off between network capacity and performance. We propose two novel networks suitable for different application scenarios. For devices with small memory and requiring fast inference speed, we propose an extremely lightweight recursive network (XLRNet). XLRNet is constructed by a single recursive strategy and two novel lightweight modules. For devices with large memory and pursuing better de-snowing performance, we propose a coupled lightweight dual recursive network (CLDRNet). CLDRNet cascades two XLRNets by a novel dual recursive strategy and a novel dual coupled LSTM module (DC-LSTM). Extensive experiments demonstrate the effectiveness and superiority of our two models on three synthetic datasets and real-world datasets.

How can industrial heat decarbonisation be accelerated through energy efficiency?

The ongoing energy transition necessitates commitments from various sectors to utilise resources more efficiently. Amongst these, the industrial sector, which is associated with high energy and resource consumption and emissions, has been attracting attention specifically aimed at performance enhancements and continuous progress in energy utilisation. The continued evolution of industrial operations and performance requires energy efficiency measures to be developed and implemented. Diverse portfolios of products, wide-ranging types of equipment, processes and, subsequently, plants, are adopted in the industrial sector, such that energy efficiency measures vary widely, along with their effectiveness, technological maturity, technical and economic impact. It remains a challenge to select the optimal energy efficiency measure(s) for a specific industry, plant and process, given the specific asset requirements. In this context, the development of systematic approaches for identifying optimal energy efficiency measures is of great interest. In this vision paper, we present an assembly of available systematic tools for advancing the energy efficiency of plants and sites in the industrial sector. The contribution of this work to the field of industrial heat decarbonisation arises from developing and proposing the use of a new holistic framework as a guide for the continuous performance improvement of thermal-energy-intensive industries through a series of energy efficiency measures and actions. Specifically, the framework suggests initiating efforts from a proposed top-down peer benchmarking practice aimed at identifying gaps in energy-efficiency performance across products, plants, processes and equipment. In a second stage, recommendations are made in form of a list of steps to close these gaps, starting with conducting equipment gap closure analyses, followed by design improvement studies at the process, plant and site levels using tools such as pinch analysis, steam system optimisation and residual waste heat recovery. We finally propose that simultaneous attention should be given to operational energy management programs along with a sequence of recommended actions to minimise deviations from the targeted energy-efficiency performance. In this vision paper, key technical tools needed to achieve the goal of continuous heat decarbonisation through energy efficiency are reviewed, and the organisational and management aspects required for effective energy targeting and management, and stakeholder engagement are addressed, based upon which relevant research challenges and opportunities are identified.

Six SIGMA evaluation of 17 biochemistry parameters using bias calculated from internal quality control and external quality assurance data.

Six Sigma is a popular quality management system that enables continuous monitoring and improvement of analytical performance in the clinical laboratory. We aimed to calculate sigma metrics and quality goal index (QGI) for 17 biochemical analytes and compare the use of bias from internal quality control (IQC) and external quality assurance (EQA) data in the calculation of sigma metrics. This retrospective study was conducted in Marmara University Pendik E&R Hospital Biochemistry Laboratory. Sigma metrics calculation was performed as (TEa-bias)/CV). CV was calculated from IQC data from June 2018 - February 2019. EQA bias was calculated as the mean of % deviation from the peer group means in the last seven surveys, and IQC bias was calculated as (laboratory control result mean-manufacturer control mean)/ manufacturer control mean) x100. In parameters where sigma metrics were <5; QGI=bias/1.5 CV) score of <0.8 indicated imprecision, >1.2 pointed inaccuracy, and 0.8-1.2 showed both imprecision and inaccuracy. Creatine kinase (both levels), iron and magnesium (pathologic levels) showed an ideal performance with ≥6 sigma level for both bias determinations. Eight of the 17 parameters had different sigma levels when we compared sigma values calculated from EQA and IQC derived bias% while the rest were grouped at the same levels. Sigma metrics is a good quality tool to assess a laboratory's analytical performance and facilitate the comparison of the assay performances in the same manner across multiple systems. However, we might need to design a tight internal quality control protocol for analytes showing poor assay performance.

Research on status‐driven hybrid evaluation method for mission success probability

AbstractMission Success Probability is a top‐level indicator that integrates reliability, maintainability, and spare parts security during the system's mission. Numerical simulation is used for mission success evaluation of complex system because it can consider any form of system structure and component failure distribution model. In actual engineering, system components usually deteriorate or fail with the extension of service time and need to be repaired or replaced, so there are dynamic changes in component status during the life cycle. To evaluate the mission success in such dynamic scenarios, it is necessary to repeat the simulation based on the whole system once the local parameters are adjusted. Despite the continuous improvement in computational performance, traditional numerical simulations are not well matched for rapid evaluation and timely decision making in dynamic scenarios. Therefore, an evaluation method that mixes proxy model and simulation sampling is proposed in this paper. The method uses the simulation to complete the data acquisition, and then analyzes the data by inverse function sampling and Copula function to obtain the model training samples, and finally realizes the approximate description of the local unit simulation process by proxy model. The experimental results show that the method can reduce the repetitive simulation scale from the whole system to local unit while ensuring high accuracy, avoiding many repeated calculations in variable scenarios.

Strategic Planning and Performance of Savings and Credit Cooperative Societies in Nairobi City County, Kenya

SACCOs play a crucial role in granting access to sustainable fiscal assistance and are identified as most effective models in enhancing productivity with over 80% of the population in Kenya, deriving their livelihood directly or indirectly from the cooperative sector. However, SACCOs are facing challenges in performance as a result of stiff competition from other financial institutions, modern technology, problems in financial management, poor leadership, and governance issues. This review narrows the gap by evaluating the impact of strategic planning on SACCO performance in Nairobi City County, Kenya. A descriptive survey research design was utilized. The research targeted 47 licensed SACCOs in Nairobi City County using a census sampling method. Results revealed that all independent variables comprise environment analysis, strategy formulation and strategy selection, were significant and had a positive relationship with SACCO performance. Therefore, it was concluded that strategy planning delivers positive results in a firm, with strategy selection contributing most to the performance of SACCOs, followed by strategy formulation and then environmental analysis. The study recommends that SACCOs should review its strategic plan every quarter of the year for continuous improvement of performance as well as that the top management of SACCOs ought to incorporate the other strategic planning practices in order to improve their performance and competitiveness. SACCOs should acquire a steady improvement in performance by reviewing its strategic plan every quarter of the year. This will enable SACCOs to develop a better strategy. Based on the research results, top management ought to play the key role on ensuring the strategic plan process is success in SACCOs and it is a critical factor in the SACCO performance in NCC. There is need to embrace good leadership structure to ensure improvement on strategic plan implementation.

Self-assessment of Public Healthcare Facility in Conformity with Accreditation Guidelines for Quality Services

There is a growing global concern for healthcare quality and patient safety and several countries have initiated accreditation and self assessment programmes for improved quality healthcare and patient safety. Both are based on the quality improvement framework and standards. Case studies have shown that: I) Accreditation certification of hospitals and healthcare facilities has been improved the quality of healthcare and related healthcare services. ii) Self-assessment by healthcare organisations has proved to be very useful tool for continuous and sustainable improvement in organization performance, quality of services, patient satisfaction over and above building the self-confidence of the care providers. In context of facility assessed it was carried out using a checklist specifically designed for this study with 318 items. The scoring pattern comprised total points and percent compliance for functional capacity of the hospital in comparison to prescribed norms. Assessment revealed maximum compliance in the categories of MIS and communication (100%). The facility lacked standard operating procedures, quality assurance system and fire safety system. Self-assessment as continuous feature will lay the basis for planning new interventions for impacting over all quality healthcare outcomes as well sustainability.

Research on Influence Law of Pressure Wave Based on Copper Ball Manometric Method

With the continuous improvement of artillery performance, internal ballistics and charge performance, abnormal phenomena of internal ballistic environment will appear during the firing process of artillery, mainly manifested as strong fluctuations in chamber pressure. If the pressure fluctuation exceeds a certain level, the pressure (overload) acting on the projectile will not be continuous and uniform, which will inevitably bring about the repeated loading process under dynamic conditions, resulting in the compatibility of the internal ballistic environment of the artillery launching guided munitions. According to the copper ball pressure measurement method commonly used in large-caliber artillery, this paper establishes the effect of the copper ball pressure gauge under different pressure curves in the bore, and verifies the established transient dynamic model. The force process of caliber-artillery projectiles under different transient pressure conditions in the bore (with and without pressure waves) is compared and analyzed, which provides a theoretical reference for the strength design of guided artillery projectiles and the coupling design of artillery projectiles, guns and powders.

Status of the Water Supply and Sanitation Projects in Pakali and Bharaul of Sunsari District

Purpose: The paper is aimed to compare the current Status of the projects in Pakali and Bharaul water supply and sanitation projects in Sunsari district. Design/Methodology/Approach: The effectiveness of the water user supply committee, the project's productivity index, the payback period, and the operating ratio of the chosen projects were analysed. Findings/Result: The functionality status of Pakali and Bharaul water supply projects is found good but needs better by increasing the business. The operating ratio of the Pakali and Bharaul water supply projects was found 0.8 and 0.72 respectively which means they can bear their operating and maintenance cost. The selected projects are found technically feasible, and economically viable. Projects have profitability indices that are more than 1, indicating the potential to be implemented. Both water supply projects are water user supply committee registered, having own staff, Operation and maintenance fund, efficient water tariff collection, reliability, and accessibility but lack of water user supply committee meetings, and record keeping proper in Bharaul compared to Pakali whereas lack of water safety plan in both projects. Originality/Value: The study will be a benchmark for continuous performance improvements of the systems and a reference for the department for assessing the performance of any system of water supply. Paper Type: Status inquiry Research

Algorithm Analysis of Face Recognition Robot Based on Deep Learning

With the continuous improvement of computer software and hardware performance, a large amount of image and video data can be easily collected and quickly transmitted, and new recognition methods that introduce deep learning are emerging, making the application and research of face recognition technology. The value is also increasingly prominent. The purpose of this paper is to study the face recognition robot implementation algorithm based on deep learning. The research background and significance of face recognition and expression recognition, which are the core of facial biological information extraction, are introduced. The face feature extraction network structure of Inception-ResNet-V1 has been improved, and high recognition features of faces can be obtained. At the same time, the training of the feature extraction model of the self-built training set and the adjustment of hyperparameters are completed. Finally, the effectiveness of the improved network in this paper is fully verified in the LFW test set and the actual robot environment. It is verified by experiments that the proposed optimization method can improve the performance of the network. It also verified the significant research significance of the current deep learning direction through practice.

Implementation of the Lean Manufacturing Concept to Reduce Waste in Spare Part Repair Activities at PT. X

The competition in the manufacturing industry is currently moving very fast. Competitive advantage, increased production effectiveness in operational activities, continuous performance improvement and business strategy Good quality is something that manufacturing companies must pay attention to to be able to compete globally. PT.X is a manufacturing company that specializes in repairing Automated Teller Machine (ATM) machine spare parts. In the process of repairing this spare part, there are problems with the use of the application system, the number of parts that cannot be repaired as before and the performance of employees is lacking, causing waste. This waste has an impact on performance and operational activities being not optimal and hampering the process of repairing spare parts. The lean manufacturing approach aims to identify and eliminate waste that occurs during operational activities in order to be more efficient and effective with the method Value Stream Mapping (VSM) for mapping the flow of spare part repairs and information flow, identifying waste which is divided into 7 categories and conducting analysis. The root cause of waste with fishbone diagrams, the result of which is the cause of waste by humans, is the lack of insight or knowledge of employees, machines that are damaged due to continuous use and the methods used by the company are not appropriate. The results of the identification of waste are waste waiting, transportation, processing, inventory and defective products. &#x0D; Keywords: Lean Manufacturing, Waste, Value Stream Mapping, Fishbone Diagram.

A Computationally Efficient High-Fidelity Multi-Physics Design Optimization of Traction Motors for Drive Cycle Loss Minimization

Continuous improvement in performance of interior permanent magnet (IPM) machines is critical for electric vehicle traction applications. However, due to the cross-coupling and saturation effects, a significant amount of time-consuming finite element analysis (FEA) simulations are required to accurately estimate machine performance. Moreover, iterative design optimization will take significantly longer. In this article, an improved rapid performance estimation technique utilizing surrogate models is developed and coupled with a design optimization algorithm. The proposed framework has significantly less computational cost than alternative surrogate-based approaches, and efficiently employs drive cycle loss minimization for a multi-physics, multi-objective traction motor design optimization. Simulation and experimental results suggest the proposed optimization framework yields optimal designs more efficiently than existing methods while maintaining accuracy.

Continued Performance Improvement—What Practicing Surgeons Can Learn From Athletes

This Viewpoint describes how surgeons can optimize performance with methods for continuous performance improvement used by athletes.

On-chip mechanical computing: status, challenges, and opportunities

As electronic computing is facing increasing challenges towards continued scaling and improvement in performance, mechanical computing has started to attract growing interests. Leveraging the mechanical degree of freedom in solid state devices, micro/nano-electromechanical systems (MEMS/NEMS) provide alternative solutions for future computing and memory systems with ultralow power consumption, compatibility with harsh environments, and high reconfigurability. In this review, we survey MEMS/NEMS-enabled memories and logic processors, and analyze the prospects and challenges for future on-chip mechanical computing.

The Interaction Mechanism and Dynamic Evolution of Digital Green Innovation in the Integrated Green Building Supply Chain

Although building enterprises are actively developing towards the direction of an integrated building supply chain (IBSC), they still face many difficulties in digital green innovation (DGI) activities. The purpose of this study is to reveal the interaction mechanism between the digital integration degree, green knowledge collaboration ability, and the DGI performance of IBSC enterprises in DGI activities under the influence of environmental characteristics of the integrated supply chain. In this study, firstly, a hierarchical regression method and a structural equation model are used to empirically study the static mechanism of DGI among enterprises in the IBSC. Secondly, this study adopts a complex system theory to construct a logistic dynamic analysis model to explore a dynamic evolution mechanism. The results of the study are as follows. (i) The digital integration degree and green knowledge synergy ability of the IBSC are conducive to improvements in digital green innovation performance among the enterprises involved in this chain. The digital integration degree of this chain is the dominant factor affecting the performance of digital green innovation among these enterprises. (ii) The digital network capability of this chain has a significant impact on its digital integration degree but has no significant effect on green knowledge synergy ability. The quality of digital relationships in the IBSC affects both the digital integration degree and green knowledge synergy ability. It has a higher impact on the digital integration degree than on the synergy ability of green knowledge. The resilience of the IBSC can effectively promote the improvement of digital integration and green knowledge synergy ability, but has no significant effect on digital green innovation performance. (iii) In the early stage of an IBSC, the effect of the digital integration degree on DGI performance is more obvious. Over the long term, under the effect of different digital relationship qualities of the IBSC, green knowledge collaboration ability plays a pivotal role. Improving this ability is conducive to the continuous improvement of DGI performance.

Nexus between information technology investment and bank performance: The case of Jordan

Bank stakeholders, such as creditors, investors, regulators, and other bank stakeholders, expect continuous performance improvement. To achieve this goal, bank managers can use information technology (IT) as a strategic resource to improve their bank’s capabilities and accordingly gain competitive advantage. In this study, the profitability and efficiency of commercial banks in Jordan are compared to investment in information technology (IT). Return on equity (ROE), return on assets (ROA), and net interest margin (NIM) are used to measure bank profitability while controlling for bank size and financial leverage. Cost efficiency is measured using the cost efficiency ratio. The study sample consists of 13 commercial banks listed on the Amman Stock Exchange between 2010 and 2021. To determine the relationship between the variables, descriptive statistics, correlation analysis, the panel least squares approach, and fixed effects multiple regression models are used. The findings show that banks, on average, spend 0.61 percent of their total assets on information technology (hardware and software). Additionally, banks that invest in IT are predicted to perform better over time, as evidenced by their increased profitability and efficiency. Small banks have more IT investment as a percentage of assets than larger banks. In comparison to highly leveraged banks, less leveraged banks typically have a greater IT investment to asset ratio (0.69%). The findings show that profitable banks (measured by ROE) invest more than 1.1% of their total assets in IT. Meanwhile, highly efficient banks also invest more in IT (0.65%) compared to less efficient banks. AcknowledgmentWe are indebted to the Middle East University (MEU) - Jordan ) for the financial support needed for this article.

Increasing Motivation and Teamwork to Encourage Services for Posyandu Cadres in the City of Pematang Siantar

Teamwork in the organization is considered crucial to encourage continuous performance improvement. Teamwork will become a driving force that has energy and synergy for individuals who are members of teamwork. Communication will run well based on awareness of the responsibilities of each member. The purpose of implementing this service is to help those who need understanding and practice implementing effective teamwork when providing services to the community. Partners are posyandu cadres in the Kahean Village with the address Jl. Tualang, No. 28, Kel. Kahean, Kec. North Siantar. The stages of implementing this event include the opening and introduction of solid teamwork, an explanation of teamwork, and a presentation on some of the problems that Posyandu cadres often face when providing services to the community, then continued discussions on building and developing service quality based on teamwork aspects. After the community service activities are completed, follow-up interviews are conducted regarding the impact of the community service activities. In accordance with the results of the interviews, it is known that the understanding of Posyandu cadres related to an increase in motivation in communication increased by 80%, and the work and implementation of solid teamwork increased by 90%.