Significant Performance Indicators Research Articles

Neural network driven sensitivity analysis of diffraction-based overlay metrology performance to target defect features

Overlay (OVL) is one significant performance indicator for the lithography process control in semiconductor manufacturing. The accuracy of the OVL metrology is extremely critical for guarantee the lithography quality. Currently, diffraction-based overlay (DBO) is one of the mainstream OVL metrology techniques. Unfortunately, the accuracy of the DBO metrology is largely affected by the defect features of the OVL target. Therefore, there is a strong need to investigate the impacts of these target defects on the DBO metrology performance. However, efficiently investigating the statistical and interactive impacts of various DBO target defects remains challenging. This study aims to address this issue through proposing an intelligent sensitivity analysis approach. A cumulative distribution based global sensitivity analysis (GSA) method is utilized to assess the nonlinear influences of multiple defects in the OVL target on the DBO inaccuracy. The scenarios with both known and unknown distributions of the OVL target defects are considered. For the former, a neural network driven forward model is constructed for fast calculating the optical diffraction responses to accelerate the GSA process. For the latter, another neural network based inverse model are built for efficiently estimating the distribution of the target defects. Finally, a series of simulation experiments are conduct for typical DBO targets with multiple common defect features. The results demonstrate the effectiveness and robustness of the proposed approach as well as give valuable insights into the DBO defect analysis. Our study provides a strong tool to assist the practitioners in achieving intelligent and efficient DBO analysis and thus in enhancing OVL metrology performance.

A metrics-driven approach for customer experience management evaluation: the case of commercial banks in developing countries

PurposeCustomer experience management (CXM), which aims to achieve and maintain customers' long-term loyalty, has attracted the attention of many organizations. Improving customer experience management in organizations requires that, first, their relevant capabilities be evaluated. The present study aimed to offer a set of key performance indicators for evaluating customer experience management in commercial banks.Design/methodology/approachThe study, first, attempted to identify the components of evaluating customer experience management by reviewing the related literature and conducting interviews with experts. Then, the extracted components were transformed into assessable metrics using the goal question metric method, and the key performance indicators relevant to customer experience management in commercial banks were selected according to the experts' opinions and the Fuzzy Delphi method. FindingsAccording to the findings of the study, 21 key performance indicators were identified for customer experience management in commercial banks, and customer satisfaction, the mean number of calls to resolve an issue in customer journey touchpoints, the NPS, and the ratio of the budget allocated to the CXM department to the budget of the marketing department were found as the most significant performance indicator according to banking experts.Originality/valueThe present study was among the first research projects intended to evaluate CXM and offer key performance indicators that could help the managers of commercial banks assess the maturity levels of their CXM.

Experimental Validation of an Upper Limb Benchmarking Framework in Healthy and Post-Stroke Individuals: A Pilot Study.

In the context of neurorehabilitation, there have been rapid and continuous improvements in sensors-based clinical tools to quantify limb performance. As a result of the increasing integration of technologies in the assessment procedure, the need to integrate evidence-based medicine with benchmarking has emerged in the scientific community. In this work, we present the experimental validation of our previously proposed benchmarking scheme for upper limb capabilities in terms of repeatability, reproducibility, and clinical meaningfulness. We performed a prospective multicenter study on neurologically intact young and elderly subjects and post-stroke patients while recording kinematics and electromyography. 60 subjects (30 young healthy, 15 elderly healthy, and 15 post-stroke) completed the benchmarking protocol. The framework was repeatable among different assessors and instrumentation. Age did not significantly impact the performance indicators of the scheme for healthy subjects. In post-stroke subjects, the movements presented decreased smoothness and speed, the movement amplitude was reduced, and the muscular activation showed lower power and lower intra-limb coordination. We revised the original framework reducing it to three motor skills, and we extracted 14 significant performance indicators with a good correlation with the ARAT clinical scale. The applicability of the scheme is wide, and it may be considered a valuable tool for upper limb functional evaluation in the clinical routine.

Transient Response of Homogenous and Nonhomogenous Bernoulli Production Lines

The transient response of production systems is of significant importance especially if present advancements in Digital Twinning technology are taken into account. While the steady-state response enables long-term strategic decision making, the transient response enables more detailed simulation concerning aspects like production losses and preventive maintenance. This is especially relevant if nonhomogenous aspects of production systems are taken into account. An analytical and approximative solution to the problem of the transient response of homogenous and nonhomogenous Bernoulli production systems is developed in this paper based on the eigendecomposition of transition matrices, the eigenvalue problem, and the finite-state method. In particular, sub-resonant and resonant nonhomogeneous production lines are introduced for the first time. Also, the most significant key performance indicators are developed as functions of the time elapsed from the first cycle. Finally, the relationship between the number of eigenvalues and the accuracy of the results is inspected by employing a sensitivity analysis. The presented theoretical framework was employed in the case of a wood processing facility to present the potential application of the theory in the case of long- and short-term management of production systems.

Artificial-Intelligence-Based Hybrid Extended Phase Shift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency

Dual active bridge (DAB) converter is the key enabler in many popular applications such as wireless charging, electric vehicle and renewable energy. ZVS range and efficiency are two significant performance indicators for DAB converter. To obtain the desired ZVS and efficiency performance, modulation should be carefully designed. Hybrid modulation considers several single modulation strategies to achieve good comprehensive performance. Conventionally, to design a hybrid modulation, harmonic approach or piecewise approach is used, but they suffer from timeconsuming model building process and inaccuracy. Therefore, an artificial-intelligence-based hybrid extended phase shift (HEPS) modulation is proposed. Generally, the HEPS modulation is developed in an automated fashion, which alleviates cumbersome model building process while keeping high model accuracy. In HEPS modulation, two EPS strategies are considered to realize optimal efficiency with full ZVS operation over entire operating ranges. Specifically, to build data-driven models of ZVS and efficiency performance, extreme gradient boosting (XGBoost), which is a state-of-the-art ensemble learning algorithm, is adopted. Afterwards, particle swarm optimization with state-based adaptive velocity limit (PSO-SAVL) is utilized to select the best EPS strategy and optimize modulation parameters. With 1 kW hardware experiments, the feasibility of HEPS has been verified, achieving optimal efficiency with maximum of 97.1% and full-range ZVS operation.

Persistent Performance of Alpha in Evaluating and Predicting the Returns of Chinese Stock Mutual Funds

Alpha has been examined to be a significant performance indicator for mutual funds. It was developed in 1968 by Jensen and was widely applied as a measure in the evaluation of mutual funds managers. It quantitatively show the gap between the model-based expected returns and the actual fund returns. In my research, I wonder whether the persistence of alpha for different portfolios exist. I apply three mutual fund performance evaluation models in this paper and calculate the alpha of mutual funds under each model. Then I rank the alpha of each fund and group them into four portfolios. I keep tracking the alpha and performance of each portfolio from January 2008 to July 2020, and find that the portfolio with the highest historical alpha keeps beating the other three portfolios while having the highest alpha. Although there are still some parts of the experiment that could be improved, the empirical results of my research show that the alpha seems to be a persistent indicator of the performance of Chinese mutual funds.

Availability and quality of primary health care in the compulsory health insurance system in Kazakhstan

<p><strong>Aim</strong> <br />To evaluate patient satisfaction with primary healthcare services and determine effectiveness indicators within Kazakhstan's compulsory health insurance system.<br /><strong>Methods</strong> <br />An analytical observational study with cross-examination was conducted in Kazakhstan's primary healthcare (PHC) organizations. Patient satisfaction was assessed through a 35-item closed-question questionnaire. An analysis of stimulating component result indicators for per capital standard financing in PHC organizations based on their achieved outcomes was performed.<br /><strong>Results</strong> <br />Among surveyed patients, 54.0% (1.80±1.108) expressed complete satisfaction with medical care, while 59.4%<br />(1.82±1.269) perceived laboratory tests as readily accessible. Notably, males exhibited higher satisfaction levels with medical care and the availability of laboratory tests compared to females. The city polyclinics № 3 and № 14 in Almaty, Kazakhstan, achieved significant performance indicators, resulting in a 1.1-fold increase in the incentive component of per capital funding.<br /><strong>Conclusion</strong> <br />Within the framework of compulsory health insurance, primary healthcare organizations in Kazakhstan offer affordable and effective medical care, as attested by surveyed patients and the final result indicators of the polyclinics.</p>

Prioritizing the attributes of sustainable banking performance

PurposeGrowing concern over sustainability adoption has presented an array of challenges to businesses. While vital to an economy's success, banking is not immune to societal, environmental and economic consequences of business practices. The study has examined the sustainable performance of banking institutions on the suggested multidimensional framework comprising economic, environmental, social, governance and financial dimensions and 52 sustainability indicators. The study benchmarks the significant performance indicators of leading banks indispensable to sustainable banking performance. The findings attempt to address research questions concerning the extent of sustainable banking performance, ranking the sustainability dimensions and indicators and standardizing sustainability adoption metrics.Design/methodology/approachTo determine the responsiveness of the banking industry to sustainability dimensions, content analysis was conducted using NVivo software for the year 2021–2022. Furthermore, a hybrid multicriteria decision-making (MCDM) approach is used by integrating entropy, the technique for order preference by similarity to ideal solution (TOPSIS) and VlseKriterijumska Optimizacija KOmpromisno Resenje (VIKOR) to provide relative weights to performance indicators and prioritize banks based on their sustainable performance. Sensitivity analysis is used to ensure the robustness of results.FindingsIn the context of the Indian banking industry, the pattern of sustainability reporting is inconsistent and concentrated on addressing environmental and social concerns. The results of the entropy methodology prioritized “Environmental” sustainability over other selected dimensions while “Financial” dimension has been assigned the least priority in the ranking order. The significant sustainable performance indicators delineated in this study should be used as standards to ensure the accountability and credibility of the sustainable banking industry. Additionally, the research findings will provide valuable inputs to policymakers and regulators to assure better contribution of the banking sector in meeting sustainability goals.Originality/valueConsidering the paucity of studies on sustainable banking performance, this study makes two significant contributions to the literature. First, the suggested multidimensional disclosure model integrating financial and nonfinancial indicators would facilitate banking institutions in addressing the five aspects of sustainability. As one of the first studies in the context of the Indian banking industry, the findings would pave the way for better diffusion of sustainability practices. Second, the inclusion of MCDM techniques prioritizes the significance of sustainability indicators and benchmarks the performance of leading banks to achieve better profits and more substantial growth.

A framework to model the performance indicators of resilient construction supply chain: An effort toward attaining sustainability and circular practices

AbstractIn existing dynamic market place, supply chain disruptions have become a common phenomenon. Emergence of new technologies coupled with variable customer demand and uncertain pandemic has fueled the disruptions across the supply chain ecosystem. To cater the unanticipated disruptions, supply chains of every business has to be circular and sustainable and construction industry is no exception to this. The present study concentrates on identifying the major performance indicators of resilient Construction Supply Chain (CSC) and prioritize the most significant ones. Fuzzy–Decision Making Trial And Evaluation Laboratory (DEMATEL) method was used to reveal the influential relationship of performance indicators on the resilience level in CSCs. Further, a strategy map is prepared to highlight the organizational strategy and cause‐effect approach. The findings from study revealed that maintaining appropriate security level, strong collaboration among supply chain partners, efficient supply chain designs, ability to detect discrepancies, bottlenecks, and vulnerabilities, and conservation of resources to facilitate sustainable operations are the top seven performance indicators that are evident in the causal group for sustainable CSC. In the effect group, prominent performance indicators are flexibility, financial strength, and efficient allocation of resources. The study adds on to the existing literature by identifying and analyzing significant performance indicators for establishing resilient, sustainable and circular practices in the construction industry.

Effects of Machining Parameters of C45 Steel Applying Vegetable Lubricant with Minimum Quantity Cooling Lubrication (MQCL)

One of the most significant performance indicators for measuring the machinability of materials is tool wear and surface roughness. Choosing the best combination of cutting parameters can help reduce production costs, which is what the manufacturing industry is interested in. At the same time, industries are always looking for an alternative to conventional flood cooling since its use creates an environmental burden and health concerns for the operators. Therefore, vegetable oil-based minimum quantity cooling lubrication (MQCL) is considered a cutting environment. Sunflower oil is utilized as base fluid in MQCL and applied to the cutting zone through a nozzle. The turning experiments are conducted on C45 material which is widely used in various industrial applications, including numerous automotive components. Since flood cooling is widely utilized in machining C45, it is the present-day need to assess alternative cooling and lubricating approaches to avoid the adverse effects of flood cooling. The Taguchi method was used in the present work to minimize surface roughness and tool wear. L9 orthogonal array was constructed, and experiments were performed on C45 steel using coated carbide cutting tools. The statistical approach is utilized to evaluate the effect of cutting parameters on output responses. The optimal cutting settings for cutting speed, feed, and depth of cut to minimize surface roughness are 100 m/min, 0.18 mm/rev, 0.150 mm, and 80 m/min, 0.18 mm/rev, and 0.150 mm for tool wear. According to the findings, cutting speed, feed rate, and depth of cut varied surface roughness by 1.9%, 78.3%, and 14.04%, and tool wear by around 43.8%, 37.9%, and 6.3%, respectively. The outcomes can be useful to metal-cutting industries to identify the combination of machining parameters with vegetable oil-based MQCL.

A Review on the Methodological Basis of Nature-Based Solution (NBS) Applications in Basin Restoration Projects

Nature-based solutions (NBSs), a sustainable landscape restoration approach, covers rebuilding ecological functionality and integrity in a watershed. The objective of restoration with NBSs is to revitalize the ecosystems to provide and sustain multiple services. Therefore, it is more than just planting trees or rewetting wetlands. NBSs can provide effective landscape restoration and management tools but should be applied on a methodological basis to get the full benefits. The methodological basis includes the type and nature of NBS, the application principles, and the tools to assess the efficiency of the set of NBS applied. However, most literature on NBSs is theoretical, while practitioners need applicable guidance. In this paper, we reviewed the latest literature on the NBSs and tried to connect the theory with some practical examples. We also underlined that NBSs applied in landscape restoration should relate to watershed processes since streamflow and/or stream quality are significant performance indicators. The NBSs should strengthen the resiliency towards multiple stressors and disturbances in a landscape. The widespread stressors in Türkiye landscapes are related to water balance that compares precipitation and evapotranspiration. Therefore, we suggest Budyko theory application in evaluating NBS options instead of typical climate models. Overall, this paper defines NBSs, provides examples, discusses possible methodologies, and comes up with some practical conclusions. The points we discuss are the resiliency assessment approach, scale, and location of the application, identifying the problems in a watershed through adequate quantitative indicators, and setting up the thresholds planned to be achieved.

Experimental and numerical studies on bending characteristics of woven CFRP reinforced aluminum thin-walled automotive structures

Metal/composite hybrid thin-walled structure is the most preferential approach to achieve dual contradictive objectives of high crashworthiness and lightweight of auto body. Its collapse with regard to different fiber layup patterns is one of the governing mechanisms of energy dissipation, which is yet to be explored. Especially, the effect of different fiber layup angles and layup sequences on bending collapse, which is one of the most significant performance indicators, has received little attention. To this gap, this study investigates experimentally and numerically the bending characteristics of aluminum/carbon fiber reinforced plastic (Al/CFRP) hybrid structures with different layup angles and layup sequences. To start with, three-point bending tests are carried out on specimens to derive the bending failure behavior and crashworthiness, and the internal section damage is observed by CT scan. Finite element model is then constructed and benchmarked against the test results to be proficient. On this basis, the effects of Al thickness, number of CFRP layers and CFRP wrapping range on the bending performance of hybrid tube are analyzed numerically. The simulation results show that layup angle has greater effect on the bending performance than layup sequence. Increasing Al thickness and the number of CFRP layers can effectively improve the bending resistance of structure, and appropriate partial wrapping of CFRP can increase the specific energy absorption (SEA) by 10.92% compared with that of complete wrapping. The revelation from this study provides sound reference for the crashworthiness design of metal/composite hybrid thin-walled structure.

Structure Fault Tolerance of Bubble-Sort Star Graphs

As two significant performance indicators, structure connectivity and substructure connectivity have been widely studied, and they are used to judge a network’s fault tolerance properties from the perspective of the structure becoming faulty. An n-dimensional bubble-sort star graph BSn is a popular interconnection network with many good properties. We find the upper bounds of κ(BSn;K1,3) and κs(BSn;K1,3) in this paper. Furthermore, we establish κ(BSn;H) and κs(BSn;H) of BSn, where H∈{K1,K1,1,K1,2}.

Enhancing road performance measurement in Indonesia: Proposed changes and future directions

This research aims to evaluate the fulfillment criteria of road performance indicators in the current long segment scheme in Indonesia by considering road performance indicators in other countries in PMBC. The research utilized the Confirmatory Factor Analysis (CFA) model in Structural Equation Modeling (SEM). The respondents were service providers and users, and the sampling technique was random. The study found that all significant road performance indicators affect the latent variable, based on the evaluation of road performance indicators listed in the 2018 Revision 2 General Specification of the Ministry of Public Works and Housing that are currently in effect. The CFA on 40 road performance indicators indicates that nine indicators do not have a significant influence on road performance. Therefore, only 31 indicators are proposed concerning response time. In addition, new road performance indicators, such as uneven patching, raveling, and dirty drainage, are proposed to be included. Response time to the indicators also needs to be updated based on service users' and providers' questionnaire survey results. This study provides valuable information for policymakers and stakeholders to improve road preservation outcomes in Indonesia.

Proposed framework for applying data mining techniques to detect key performance indicators for food deterioration

One of the most prosperous domains that Data mining accomplished a great progress is Food Security and safety. Some of Data mining techniques studies applied several machine learning algorithms to enhance and traceability of food supply chain safety procedures and some of them applying machine learning methodologies with several feature selection methods for detecting and predicting the most significant key performance indicators affect food safety. In this research we proposed an adaptive data mining model applying nine machine learning algorithms (Naive Bayes, Bayes Net Key -Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), J48, Hoeffding tree, Logistic Model Tree) with feature selection wrapper methods (forward and backward techniques) for detecting food deterioration’s key performance indicators. Therefore, results before and after applying wrapper feature selection methods have been compared, analyzed, and interpreted. In conclusion the proposed model applied effectively and successfully detected the most significant indicators for meat safety and quality with the aim of helping farmers and suppliers for being sure of delivering safety meat for consumer and diminishing the cost of monitoring meat safety.

What do border disputes cost? Evidence from an emerging market

PurposeThe study aims to examine the impact of six events related to the escalating Indo-China border conflicts in 2020 on the Indian stock market, including the role of firm-specific variables.Design/methodology/approachThis study employs an event-study method on a sample of 481 firms from August 23, 2019 to March 3, 2022. A cross-sectional regression is employed to examine the association between event-led abnormal returns and firm characteristics.FindingsThe results show that, although the individual events reflect heterogeneous effects on stock market returns, the average impact of the event categories is negative. The study also found that net working capital, current ratio, financial leverage and operating cash flows are significant financial performance indicators and drive cumulative abnormal returns. Further, size anomaly is absent, indicating that more prominent firms are resilient to new information.Research limitations/implicationsThe ongoing conflict between Russia and Ukraine is an example of how these disagreements can devolve into a disaster for the parties to the war. Although wars have an impact on markets at the global level, the impacts of border disputes are local. Border disputes are ongoing, and the study's findings can be used to empower investors to make risk-averting decisions that make their portfolios resilient to such events.Originality/valueThis study provides firm-level insight into the impacts of border conflicts on stock markets. The authors compare the magnitude of such impacts on two types of events, namely injuries and casualties due to country-specific border tensions and a government ban on Chinese apps. Key implications for policymakers, stakeholders and academics are presented.

Investigating temporal dynamics of urban densification on the buried water infrastructure performance

Urban densification has dominated the land uses and land covers which may jeopardize the quality of life and sustainable development. Moreover, urban densification process exerts stress on buried water infrastructure (BWI) performance. In this study, the need of predicting the change in urban densification and its subsequent impacts on BWI performance over time has drawn attention to conduct a temporal analysis. A hybrid approach was used to select the significant control performance indicators (CPIs) and conduct a temporal analysis. Eight scenarios were generated using the Canadian Council of the Ministers of the Environment Water Quality Index approach to address the change in drinking water quality. The proposed approach was implemented in a municipality of British Columbia, Canada, as a case study. The results showed a 40 % decrease in the BWI performance due to the urban areas have rapidly grown both in population and built-up areas over three decades. Furthermore, an ideal situation was assumed to show that the targeted service level (i.e., 0.5) can be achieved with 3 % to 5 % improvement in every five years of service level. These findings will assist the decision makers to understand the linkage between CPIs to maintain and achieve the required BWI performance.

Investigation of the consistency of methods for assessing the technical level of construction dump trucks

The article offers a minimum list of the most significant performance indicators of construction dump trucks, a comparative analysis of which allows an assessment of their technical level in the interests of choosing consumer preferences for road construction work. The weighting coefficients of these indicators obtained as a result of an expert survey are given. Methodological approaches and results of comparative calculations of the technical level by various methods are presented: cluster ranking based on expert assessments of the weighting coefficients of individual and complex indicators of operational properties; direct ranking; matrix method. For the analysis, three-axle and four-axle dump trucks of domestic and foreign production with a load capacity from 18 to 20 tons were selected. Based on the results of the analysis, it is concluded that it is permissible to use traditional methods of assessing the technical level to justify the choice of a dump truck model by the consumer. The directions of further improvement of methodological approaches to solving this issue are proposed. Keywords dump truck, technical level, evaluation methods, expert research, ranking

Key components of successful post–hurricane reconstruction of transportation infrastructures

PurposeIn the aftermath of hurricanes, the damage levied on transportation infrastructures increases the timeliness of emergency responses and recovery procedures, making it essential that they are reconstructed as quickly as possible – on time and within budget. The aim of this study was to determine significant performance indicators (PIs) that considerably affect cost and schedule performance as well as reworks in post–hurricane reconstruction of transportation infrastructure including highways, bridges, roadways, etc. Additionally, the determined PIs were clustered to investigate key components.Design/methodology/approachThe root causes of reconstruction projects' poor performance were identified through the existing literature, and 30 transportation infrastructure case studies were analyzed to determine the significant PIs that corresponded to cost, schedule performance and reworks. The factor analysis method was used to cluster the significant PIs and determine the key components affecting them.FindingsEight key components were found for cost, eight for schedule performance and six for reworks. The key components of cost performance are shortage of resources, information management, coordination, safety, location, quality of materials, quality of resources and project complexity. The key components of reconstruction schedule performance are human resources, risk management, work suspension, material resources, productivity, on-site inspections, geometrical characteristics and level of reconstruction complexity. The six key components of reconstruction reworks are logistic management, pace of decision-making, accommodation for staff, environmental issues, available temporary paths and volume of debris.Originality/valueThe outcomes of this research will assist authorities and decision makers in identifying and evaluating the critical root causes of poor cost performance, poor schedule performance and reworks and will enable them to facilitate the timely and effective allocation of resources.

Confirmatory Factor Analysis of Performance Measurement Indicators Determining the Uptake of CPS for Facilities Management

With the use of cyber-physical systems (CPS) advanced computational capabilities, the delivery of facilities management (FM) mandates are efficiently and effectively conducted. Since performance measurement is an important yardstick in ascertaining the outcome of FM approaches, this study assesses the performance measurement indicators that influence the uptake of CPS for FM functions. Using a structured questionnaire, data were collected from built environment professionals in the Gauteng province of South Africa. Data collected was analysed using a five-stage process which includes: data reliability and validity, descriptive statistics, establishing a difference in groups’ opinion, principal component analysis, and model testing and fit statistics for confirmatory factor analysis. Results from the study indicate that three significant performance indicators are influential in determining the uptake of CPS for FM, which are operations efficiency, facility adaptation, and client’s satisfaction. The study contributes immensely to the body of knowledge. It unveils the significant performance measurement indicators that would help organisations, facilities managers, and policymakers guide their decisions hinged on the espousal of innovative technologies. Furthermore, the study serves as a solid theoretical base for further studies showcasing a roadmap for digitalisation for FM functions by unravelling the significant performance measurement indicators.