Key Performance Indicators Research Articles

Promoting health information system in guiding decisions for improving performance: an intervention study at the Research Institute of Ophthalmology, Giza, Egypt.

This study aims to design and test a platform of key performance indicators (KPIs) and indices emphasizing achievements and improvement and helping decision-making. An operations research study was designed to analyze data from the Hospital Management Information System (HMIS) from July 2017 to June 2018 at the Research Institute of Ophthalmology (RIO), Giza, Egypt. The HMIS data were submitted to reform covering parameters in service delivery and corresponding indicators and indices. Data were grouped into four themes: human resources and outpatient, inpatient, and surgical operations. A total of 14 performance indicators were deployed to four specific indices and total performance indices and applied to six teams of ophthalmologists at RIO. The decision matrices were deliberated to demonstrate achievements and provide recommendations for subsequent improvements. Throughout 1 year, six teams of ophthalmologists (n = 222) at RIO provided the following services: outpatient (n = 116,043), inpatient (n = 8,081), and surgical operations (n = 9,174). Teams 2, 1, and 6 were the top teams in the total performance index. Team 4 had plunges in the outpatient index, and Team 5 faced limitations in the inpatient index. The study provided a model for upgrading the performance of the management information system (MIS) in health organizations. The KPIs and indices were used not only for documenting successful models of efficient service delivery but also as examples of limitations for further support and interventions.

Research on novel hybrid structure AACMM based on 3-RPS parallel mechanism

Abstract The articulated arm coordinate measuring machine (AACMM), widely utilized in the field of industrial measurement, is assessed based on key performance indicators such as measurement accuracy, measurement space, and flexibility. To enhance these aspects of the AACMM, this paper introduces a novel type of AACMM. The new model is based on a 3-RPS (revolute joint R, prismatic joint P, spherical joint S) parallel mechanism (3-RPSPM). The working principle of the 3-RPSPM is detailed, and a corresponding computational model is established. An algorithm is proposed based on this mathematical model to determine the theoretical achievable accuracy of the 3-RPSPM. Additionally, a spatial error analysis of the 3-RPSPM is conducted to verify its compliance with AACMM accuracy requirements and to demonstrate a certain level of accuracy improvement. Through simulation analysis, the differences in measurement accuracy, measurement space, and flexibility between the new type of AACMM based on the 3-RPS parallel mechanism (3-RPSAACMM) and traditional AACMMs are compared. The results indicate that the 3-RPSAACMM, with its novel parallel structure free from series accumulation errors, not only maintains measurement flexibility but also achieves improvements in measurement accuracy and space. The hybrid structure adopted by the new 3-RPSAACMM offers a new direction for the future development of AACMMs, presenting significant research value and application prospects.

Evaluating the Impact of Private Sector Participation on Operational Efficiency in Container Terminals: A Case Study of Colombo Port

Sri Lanka, strategically located in South Asia, has the potential to become a significant hub for international maritime trade. However, the current port infrastructure, particularly in Colombo, faces capacity constraints that limit its ability to accommodate larger vessels and manage increasing container traffic. This study evaluates the impact of private sector participation on the operational efficiency of Colombo’s container terminals - Jaya Container Terminal (JCT), South Asia Gateway Terminal (SAGT), and Colombo International Container Terminal (CICT). Using Key Performance Indicators (KPIs) and Data Envelopment Analysis (DEA), the study found that private sector involvement significantly enhances terminal efficiency. SAGT, a privately operated terminal, exhibited the highest overall efficiency, while CICT demonstrated the highest productivity. JCT, though publicly operated, showed commendable performance but lagged behind the private terminals. The findings emphasize the value of public-private partnerships (PPPs) in optimizing port operations, offering critical insights for policymakers and stakeholders aiming to strengthen Sri Lanka’s maritime economy.

FEATURES OF THE DESIGN AND IMPLEMENTATION OF INVESTMENT AND CONSTRUCTION PROJECTS UNDER CONDITIONS OF BALANCED DEVELOPMENT

The development and implementation of investment and construction projects on the basis of balanced development is critical for achieving sustainable growth. This article examines the key features and challenges associated with such projects, emphasizing the importance of integrating economic, environmental and social practices into construction activities. The study provides insights into best practices and strategies for effectively managing investment and construction projects to ensure long-term success and sustainability.The main goals of this article are the definition of the fundamental principles of balanced development in the context of investment and construction projects, the analysis of features that contribute to the achievement of balanced development.The article uses a comprehensive review of the literature and case studies, which allows for a holistic understanding of the multifaceted nature of investment and construction projects in conditions of balanced development. Emphasis is placed on the integration of sustainable development principles from the initial stages of design. This includes consideration of environmental impact assessment, efficient use of resources and use of sustainable materials and technologies. Also, the goal of project implementation is that the projects are economically feasible and provide long-term financial returns. This involves careful market analysis, cost-benefit analysis and risk management strategies to mitigate potential financial problems. The importance of involving all relevant stakeholders, including local communities, government bodies and investors, in the decision-making process is emphasized. Effective communication and collaboration are necessary to address diverse interests and reach consensus. Ensures compliance of projects with national and international rules and standards. This applies to environmental regulations, building regulations and labor legislation. Compliance minimizes legal risks and increases project credibility.Focused on optimizing the use of resources such as materials, labor and time, implementing lean construction methods and advanced project management practices can increase efficiency and reduce waste.The implementation of advanced technologies such as building information modeling (BIM), automation and renewable energy systems increase design accuracy, reduce costs and increase sustainability. Conformity of construction work to established quality standards, regular inspections, testing and adherence to best practices are critical to obtaining high quality results.Constant monitoring of project progress and effectiveness is emphasized. The use of key performance indicators (KPIs) and regular evaluations help to identify problems early and make the necessary adjustments.The development and implementation of investment and construction projects in conditions of balanced development requires a complex and integrated approach. By prioritizing sustainability, economic viability, stakeholder engagement and regulatory compliance, stakeholders can ensure these projects contribute positively to long-term growth and development. The paper provides a road map to navigate the complexities of such projects, ultimately contributing to a more resilient and sustainable human-made environment

EU social taxonomy for sustainable economic activities: exploring the known and navigating the current issues as well as future research

This research aims to initiate academic discussion on the European Union (EU) social taxonomy for the purpose of promoting sustainable economic activities that ultimately contribute to achieving the United Nations’ sustainable development goals (SDGs) in the EU. The paper examines the historical evolution of the social taxonomy concept and presents the chronological order of the regulatory advancements that have paved the way for the establishment of both the EU environmental and social taxonomies. This study emphasizes the role of the EU environmental taxonomy as the frontrunner and highlights three fundamental distinctions between taxonomies in terms of objectives, foundations, and measurability. By defining the key performance indicators applicable to entities engaged in taxonomy-aligned economic activities, the paper offers a tabulated framework to understand the core focus areas, sub-objectives, and types of substantial contributions related to each of the three social objectives outlined in the EU taxonomy. Moreover, this paper aims to emphasize the contemporary challenges and the prospective avenues for future research in the field of social taxonomy.

IMPLEMENTASI PERANCANGAN INTEGRASI SWOT BALANCED SCORECARD DALAM PENILAIAN KINERJA BISNIS PAKAN KELINCI PADA RABBIT BROTHERS DI KABUPATEN BANDUNG

Rabbit Brothers is one of the rabbit breeders established in 2017 located in West Java, West Bandung Regency. Rabbit Brothers rabbit feed sales in 2023 fluctuated. The tighter the competition, the company needs to determine strategies in business management to determine the company's current performance. The purpose of this study is to describe the strategy based on SWOT analysis, design a Rabbit Brothers rabbit feed strategy map based on SWOT Balanced Scorecard integration, performance measurement and performance assessment of Rabbit Brothers rabbit feed based on SWOT Balanced Scorecard integration, and improve Rabbit Brothers rabbit feed business performance based on SWOT Balanced Scorecard integration. The methods in this research are SWOT Analysis, Balanced Scorecard, Analytical Hierarchy Process Software Expert Choice, and Key Performance Indicator Lead Indicator. Rabbit Brothers rabbit feed strategy and strategy map, one of which is increasing profits, Rabbit Brothers rabbit feed performance is 93.04%, meaning that the company's performance is in a very healthy condition with the category (AAA). The performance of the four performance perspectives that are not optimal is improved on strategic initiatives, one of which is the content creation program.

The Importance of Surgical Cutting Time as a Key Performance Indicator Alongside Touchtime Utilisation in Operating Theatre Efficiency Optimisation.

Aims The Getting It Right First Time(GIRFT) programme has set targets to achieve 85% touchtime utilisation by 2024/25. Touchtime utilisation is a measure of theatre productivity, defined as the time from the start of anaesthesia to the time a patient leaves the theatre for all cases on a defined theatre list as a percentage of total available theatre time. No published evidence examines touchtime utilisation as a measure of theatre efficiency and its correlation with surgical cutting time. This study aims to determine if there is a statistical relationship between touchtime utilisation and surgical cutting time, and whether the use of touchtime utilisation is sufficient to inform about surgical productivity. Methods A retrospective analysis of two orthopaedic theatres spanning 100 days at both a major trauma centre and an elective hospital in London was performed. Electronicrecords identifiedanaesthetic start time, knife-to-skin time, end-of-procedure time, and patient-leaving-theatre time. Time intervals were calculated and the relationship between touchtime utilisation and surgical cutting time was assessed using Pearson's correlation coefficient (r). Results The mean total touchtime was 403 minutes (SD, 84 minutes) at the major trauma centre and 383 minutes (SD, 103 minutes) at the elective hospital. The mean total surgical cutting time was 259 minutes(SD, 72 minutes) at the major trauma centre and 233 minutes (SD, 75 minutes) at the elective hospital, from a total available time of 510 minutes per list. There was a significant correlation between touchtime and surgical cutting time at both hospitals (elective hospital: r (198) = 0.815, p < 0.001; major trauma centre: r (198) = 0.892, p < 0.001). The mean touchtime utilisation was 79.31% for the major trauma centre and 75.20% for the elective hospital; however, the mean total surgical cutting time was 51% and 46%, respectively, of total available time. Conclusion Despite a good correlation between touchtime and surgical cutting time, the range between these measures suggests that using touchtime utilisation alone to measure theatre efficiency may not sufficiently inform about efficient practices. We suggest complementing touchtime utilisation data with surgical cutting time may provide more information to contextualise efficiencies or inefficiencies in an operating theatre.

A Comprehensive examination of utilizing neutrosophic parameters in manufacturing industry through queueing approach

Queueing theory plays a pivotal role in analyzing the dynamics of manufacturing systems subject to random arrivals and service times. The M/G/1 queueing model, which represents a single-server queue with general distributions for inter-arrival and service times, is fundamental in this regard. However, traditional queueing models often fail to account for the inherent uncertainties encountered in real-world manufacturing scenarios. Neutrosophic theory provides a robust framework for modeling indeterminacy, ambiguity, and inconsistency in queueing parameters, thereby offering a more adaptable and precise depiction of system behavior. This research investigates the utilization of Neutrosophic sets in defining arrival rates, service times, and queue length distributions within the M/G/1 framework tailored to manufacturing settings. By employing numerical examples and comparative analyses, the study explores the effects of Neutrosophic parameters on key performance indicators such as mean waiting time, queue length distribution, and server utilization, considering distributions like Exponential, Erlang, and Deterministic. Additionally, it delves into the implications of integrating Neutrosophic parameters into queueing theory, providing valuable insights into improved decision-making and system optimization across various manufacturing operational contexts.

Board Size and Corporate Performance in the Industrial Property Sector in Malaysia

This research investigates the relationship between the size of the board of directors and the financial performance of publicly listed industrial property firms in Malaysia. The study examines secondary data from annual reports, financial statements, and corporate governance disclosures, focusing on key financial performance indicators such as Return on Assets (ROA), Return on Equity (ROE), and Net Profit Margin (NPM). The study reveals significant correlations between board size and financial performance using correlation analysis and multiple regression. The findings provide valuable insights for regulators, investors, and business leaders, emphasizing the importance of refining corporate governance standards to ensure long-term financial success in Malaysia's industrial property sector.

Сегнетоэлектрические материалы в современных вычислениях

Background: Ferroelectric materials, known for their spontaneous electric polarization, are reshaping the landscape of modern computing. These materials have unique qualities, such as non-volatility, high-speed operation, and energy efficiency, which are critical for advancing modern computer technology. Objective: This study intends to investigate integrating ferroelectric materials into current computer systems, emphasizing to improve memory devices and processors and solve the accompanying technological obstacles and possibilities. Methods: A thorough analysis of existing literature and experimental data was carried out to determine the capabilities and limitations of ferroelectric materials in computing applications. Key performance indicators examined include polarization retention, energy consumption, scalability, and integration with existing semiconductor technology. Results: The results show that ferroelectric materials considerably increase memory device performance and efficiency by allowing quicker write/read operations and lowering power use. However, concerns such as material deterioration, data retention, and integration complexity with silicon-based technology remain. Conclusion: Ferroelectric materials provide exciting prospects for the next generation of computer technology. While they provide significant gains in memory and processing power, addressing the technological obstacles is critical to their effective adoption into mainstream computer applications. Further research and development are needed to solve these issues and fully realize the promise of ferroelectric materials in improving computer performance.

Evaluation of Handoff Drop Call Rate in GSM Network in Delta State with Dynamic Cut off Channel Allocation Scheme

This study aims at evaluating Handoff drop call rate in GSM Network using dynamic Cut off Channel Allocation Scheme by evaluating different Mobile Network Operators, MNOs, and comparing with Nigerian Communication Commission (NCC)’s Key Performance Indicator (KPI). A hybrid handoff algorithm was developed to reduce drop calls, analyze the performance of the hybridized handoff algorithm; and compare the simulated results of the hybridized algorithm with that of the existing Mobile network operators, MNOs. The current handoff failure and drop call rates of the best mobile communication network in Nigeria was evaluated and was discovered that the existing Hand off failure rate HFR per cell was 5% and the drop call rate DCR was 10%. These were above the NCC maximum target of 2%. These defects account for the unacceptable drop call rates experienced and thus negatively impact on the quality of service QoS. An optimal solution was provided by developing an enhanced and highly sensitive handoff algorithm from two different algorithms - the Entire Channel Allocation, and the Fixed Channel Allocation - while putting the Modified Reserved Channel Scheme with Guard Channel, and the Fuzzy handoff initiation method into consideration. A software known as Netbeans 7.2 was interfaced with Octave 5.1.0 and used to simulate the developed algorithm. The programme trial was made to run repeatedly for 1200s. Our simulation results indicated HFR of 3% as against 5% from that of the existing network, and DCR of 6% as against the 10% from the network. In further comparing the existing DCR with that obtained from our simulation, an average of 40% dropped calls reduction was realized. This implied that the algorithm reduced drop calls thereby enhancing connectivity and mobility management through the minimization of handoff failures.

A Guideline Enabling Knowledge Managers to Communicate Better with Business Managers

Aligning Knowledge Management (KM) with overarching business strategies is considered as important for organizational success and sustainability. But this crucial element is often missing in the implementation and operation of KM. This paper explores the concept of "business alignment" within the context of KM, elaborating its critical role in enhancing collaboration, minimizing errors, and supporting optimal outcomes across the enterprise. We suggest a comprehensive definition of KM alignment, where KM activities are strategically integrated with business objectives, ensuring visible and measurable benefits to employees and executives. The research addresses key questions such as what constitutes an organization and how KM can facilitate its survival and growth. An organization is not merely a standalone entity but a collective endeavor that thrives on managing internal and external relationships. We argue that the effective alignment of KM with business strategies ensures that these relationships are optimized, thereby enhancing organizational resilience and adaptability. This holistic perspective visualizes the interconnected nature of businesses and highlights the essential role of KM. Our approach involves a systematic examination of business relationships and their alignment with KM practices. We analyze one case study from the construction industry, illustrating how strategic KM initiatives contribute to their sustained success. Additionally, we propose a set of Key Performance Indicators (KPIs) derived from real-world scenarios, linking them to specific business needs and challenges. These KPIs serve as a roadmap for C-level managers, guiding them in integrating KM into their strategic frameworks. The findings underscore the value of KM in mitigating risks associated with poor relationship management. We provide a process and actionable insights for business leaders on leveraging KM to foster innovation, streamline processes, and enhance overall performance. The paper concludes with practical recommendations for implementing KM solutions tailored to different organizational maturity levels and industry contexts.

Effect of Piston Geometry on Performance Characteristics of VCR Engine with and without EGR when Fueled with Blends of Methyl Ester

The growing population and exhaustion of fossil fuels necessitate our search for new sources of energy. The study for this research encompasses an amalgamation of interest in alternative fuels, advanced engine technology such as variable compression ratio VCR, engine component modification, and a methodical approach to testing for assessing the effects on key performance of the engine. A 3.5 kW compression ignition (CI) engine was fueled with blends of behada, chicken fat, and turmeric oil methyl ester. Engine operating parameters, such as the compression ratio (CR), rate of exhaust gas recirculation (EGR), and piston top geometry, are optimized to maximize engine performance. CI engine was modified by changing the piston head (square and tangential groove top) for methyl ester diesel blend operations. In the study, diesel fuel is designated as B00 and methyl ester as B20. The influence of compression ratio (CR16 and CR18) with exhaust gas re-circulation (EGR 0% and EGR 10%) was evaluated. The key performance indicators: brake thermal efficiency (BTE), brake-specific energy consumption (BSEC), brake-specific fuel consumption (BSFC), air-to-fuel ratio (AFR), and exhaust gas temperature (EGT) are investigated. Results indicate that an increase in BTE accompanies an increase in load, suggesting enhanced thermal efficiency with increased power output. The consequence of VCR is also investigated, and it is determined that a higher CR results in a higher BTE due to an increase in compression pressure and temperature, thereby enhancing combustion. Due to the re-combustion of unburned hydrocarbons with the addition of EGR at a 10% rate, BTE increases further. Utilizing a piston geometry with tangential grooves and methyl ester blends also contributes to increased BTE. BSEC increases with increasing load, with an important rise observed when operating at maximum capacity. However,at CR 18, BSEC decreases as a result of enhanced combustion efficiency. EGR has different effects on BSEC depending on the geometry of the piston and the kind of fuel used. Enhanced air-fuel blending and re-combustion of unburned hydrocarbons reduce the BSEC of the engine. The tangential groove top piston operates with 10% EGR. Similar to BSEC, BSFC decreases with increasing CR and improves with the use of a piston with a tangential groove and 10% EGR operation. AFR decreases as the consumption of fuel increases to meet the power demand, and higher CR values result in a lower AFR. EGT rises with load, and CR18 has a lower EGT than CR16 as a result of a higher compressing temperature and pressure. 10% EGR operation reduces EGT by decreasing the concentration of oxygen in the combustible area.

Cost-benefit analysis of implementing a solar powered water pumping system – A case study

Solar-powered water driving scheme (SPWDS) has been successfully employed as a practical solution to guarantee reliable water supply in various hilly regions without electrical infrastructure. The Water Supply Systems / Schemes (WSS) focus on using pumping systems for delivering potable water to the community but face practical difficulties and financial hurdles at different implementation stages. These challenges encompass the practical complexities, the absence of non-renewable energy sources, and ongoing expenses for consumable and non-consumable items incurred during the water project's execution and maintenance. The present research study evaluates the performance of four water supply systems in Nepal which use solar energy as their primary power source. The key performance indicators are assessed, including the functionality index for facility distribution. Additionally, the research aims to evaluate the feasibility of transitioning from non-renewable to sustainable renewable energy source to achieve net zero energy consumption. This evaluation concentrates explicitly on calculating the cost-effectiveness index as a key metric. A proportional analysis is undertaken to evaluate the cost-benefit of the SPWDS, considering both the potential advantages and challenges associated with these initiatives. The present study affirms the technical feasibility and economic viability of operating a WSS using renewable and eco-friendly solar energy as the power source. This finding opens avenues for reducing energy consumption and contributes significantly to developing a policy framework to for tapping solar energy.

Visualizing Hospital Management Data in R Shiny-A Case Study.

There is a demand to make hospital management information beyond basic key performance indicators (KPIs) accessible for clinicians. We developed an interactive application (IAPP) in R Shiny to visualize such information. We provided the IAPP source code online. As a use case, we recorded basic KPIs (numbers of patients (NPs), reimbursed valuation ratios (RVRs), mean length of stay (LOS)), main diagnoses (MDGNs), main procedures (MPRCs), and catchment area (CA) by district from April 2022 to March 2024 at the index department in central Germany, where a neurotrauma and spinal surgery service was resumed on 1 April 2022. Case mix indexes (CMIs) were calculated. We retrieved information about online-reported patient satisfaction (ORPS) from an online physician rating platform between January 2022 and March 2024. Information on longitudes and latitudes of the index department and neighbouring hospitals was collected. We calculated car travelling isochrones (CTIs) of the hospitals as a proxy variable for accessibility. Chi-square and Fisher's exact served as statistical tests. During the observation period, the monthly NPs increased from 26 to 43, the RVR showed a 3.96-fold increase, the CMI showed a 2.41-fold increase, and the LOS reached a steady state in the 2nd year after service resumption. CA (p = 0.03), MDGNs, and MPRCs diversified. ORPS trended towards better overall evaluation after service resumption (p = 0.09). CTI mapping identified a unique market position of the index department. The IAPP makes extended hospital management data accessible to clinicians, can inform other stakeholders in healthcare, and can be tailored to local conditions.

ORPP—An Ontology for Skill-Based Robotic Process Planning in Agile Manufacturing

Ontology plays a significant role in AI (Artificial Intelligence) and robotics by providing structured data, reasoning, action understanding, context awareness, knowledge transfer, and semantic learning. The structured framework created by the ontology for knowledge representation is crucial for enabling intelligent behavior in robots. This paper provides a state-of-the-art analysis on the existing ontology approaches and at the same time consolidates the terms in the robotic task planning domain. The major gap identified in the literature is the need to bridge higher-level robotic process management and lower-level robotic control. This gap makes it difficult for operators/non-robotic experts to integrate robots into their production processes as well as evaluate key performance indicators (KPI) of the processes. To fill the gap, the authors propose an ontology for skill-based robotics process planning (ORPP). ORPP not only provides a standardization in the robotic process planning in the agile manufacturing domain but also enables non-robotic experts to design and plan their production processes using an intuitive Process-Task-Skill-Primitive structure to control low-level robotic actions. On the performance level, this structure provides traceability of the KPIs down to the robot control level.

Nitrogen-rich sulfur-containing heterocyclic adsorbents for effective selective adsorption of Au(III)/Pd(II)/Pt(IV)

Recovering precious metals from secondary resources has elicited considerable attention, and exploring an efficient adsorbent is a challenge. In this work, we have specifically tailored three highly effective adsorbents (THDA@PEI, DCTA@PEI and DCTD@PEI) by crosslinking PEI with sulfur-containing heterocyclic cross-linking agents (2,5-thiophenedicarboxaldehyde, 2,4-dichlorothiazole and 3,4-dichloro-1,2,5-thiadiazole) for recovery of Au(III), Pd(II), and Pt(IV). These agents are distinguished by a range of nitrogen atom counts that extend from zero to two, offering a foundation for exploring the correlation between their molecular structure and adsorption performance. THDA@PEI, DCTA@PEI, and DCTD@PEI exhibit remarkable adsorption capacities for Au(III), Pd(II), and Pt(IV), with values reaching up to 2169, 2240, and 2536 mg/g for Au(III), 771, 886, and 846 mg/g for Pd(II), and 832, 1021, and 887 mg/g for Pt(IV), respectively. Among the three materials, DCTD@PEI stands out with a broader pH applicability range for both gold (pH 2 to 9) and platinum (pH 1 to 11) adsorption and exhibits a more rapid adsorption rate for Au and Pd. The adsorption processes of the three adsorbents on precious metals are spontaneous and entropy-increasing processes. Increasing the adsorption temperature could improve the adsorption performance of the three adsorbents, except for Pd adsorption by DCTD@PEI. All of the three adsorbents exhibit good selectivity and reusability for Au, Pd, and Pt, with DCTA@PEI being the most outstanding. It is observed that an increase in nitrogen content in the adsorbents correlates positively with the improvement of key performance indicators, including a wider pH range, higher adsorption capacity, faster kinetics, better selectivity, and enhanced reusability, while the substituent positions of crosslinking agents also have a strong impact on the adsorption performance, especially for Pd and Pt.

493 Predicting pellet quality using multiple linear regression with Principal Component Analysis (PCA)

Abstract Pellet quality is a crucial key performance indicator (KPI) for commercial feed manufacturing, which influences both the efficiency of the feed mill and downstream performance of animals fed these diets. However, due to the complexity of feed manufacturing and the large number of factors involved in the manufacturing process, controlling pellet quality is an ongoing challenge for the feed industry. Previous studies have mainly explored the impact of a few factors on pellet quality under experimental settings, and empirical equations have been seldomly developed to reflect the relationship between the factors and pellet quality under the commercial feed mill settings. This study aimed to establish a relationship between pellet quality and factors collected under the settings of a commercial feed mill. The data were collected from Trouw Nutrition Canada’s feed mill located in St. Marys, Ontario (Plant 2), between December 15, 2021, and December 6, 2022. During this period, 2,691 observations were collected, with each observation representing an individual batch of pelleted feed. A total of 75 factors were recorded, including 4 factors associated with the general information of each batch, 10 manufacturing parameters, 41 feed ingredients, 8 factors regarding the nutrient composition of each diet, and 12 environmental factors. Pellet Durability Index (PDI), which was the response variable, was determined for each batch using the Holmen method. The data were randomly split into an 80% subset for training and a 20% subset for testing. The training subset was used to construct the model via a 5-fold cross-validation, while the testing subset was withheld as an independent dataset to evaluate the generalization performance of the model. The response variable (PDI) was transformed (tPDI) using the Box-Cox method to meet a normal distribution assumption. To avoid multicollinearity, Principal Component Analysis (PCA) was used to reduce the dimensionality of the numeric factors before building the multiple linear regression model. The model prediction performance was evaluated on both the training subset (using 5-fold cross-validation) and the testing subset, and the prediction performance metrics were consistent between the two subsets (Mean Absolute Error = 1.94 ± 0.102 vs. 2.02; Root Mean Square Prediction Error = 2.47 ± 0.111 vs. 2.58; Mean Square Prediction Error = 6.12 ± 0.538 vs. 6.68; Concordance Correlation Coefficient = 0.538 ± 0.0231 vs. 0.490; Pearson Correlation Coefficient = 0.606 ± 0.0247 vs. 0.553, respectively). Most feed ingredients and nutrient compositions showed either positive or negative loadings on Component 1 (17.87% of total variance), and outdoor/indoor environmental factors were positively loaded on Component 2 (14.21% of total variance). The model developed in this study could help commercial feed mills better understand how various factors impact pellet quality and optimize the manufacturing processes of pelleted feeds.

CO2 Electrolysis Technologies: Bridging the Gap toward Scale-up and Commercialization.

CO2 electroreduction (CO2E) converts CO2 into carbon-based fuels and chemical feedstocks that can be integrated into existing chemical processes. After decades of research, CO2E is approaching commercialization with several startups, pilot plants, and large initiatives targeting different products. Here, we analyze the global efforts in scaling up CO2E, addressing implementation challenges and proposing methods for acceleration. We present a comparative analysis of key performance indicators (KPIs) between laboratory and industrial settings and suggest a stepwise technoeconomic analysis (TEA) framework, supported by industrial data, exploiting interactions within the academic and industrial communities. We identify the lack of systems-oriented standardization and durability as the main bottlenecks slowing down progress in the lab-to-prototype-to-market pathway of CO2E technologies. Inspired by electrolysis and fuel cell technologies, we outline protocols to advance fundamental research and aid catalyst development progress in performance, upscaling, and technology readiness level of CO2E.

KPI-oriented process monitoring based on causal-weighted partial least squares

With the increasing demand for product quality, Key performance indicator (KPI)-oriented process monitoring plays an important role in modern industrial. Partial least squares (PLS)-based methods are widely adopted for KPI-oriented process monitoring, in which the process variable space is decomposed into a principal component subspace that has a strong correlation with KPIs and a residual subspace unrelated to KPIs, and the two spaces are monitored separately. However, if a KPI-unrelated fault occurs in a variable that has no causal relation with any KPI, but has a spurious correlation with some KPIs because of the existence of confounders, PLS based methods may mis-regard the KPI-unrelated fault as a KPI-related fault. This occurs because as a correlation analysis-based method, PLS cannot discriminate whether a variable is a real cause of KPIs or has a spurious correlation with KPIs. Motivated by this, this paper proposes two causal-weighted PLS methods for KPI-oriented process monitoring by combining the LiNGAM-based causal discovery with PLS, which first calculate causal weights based on the modified LiNGAM algorithm and bootstrap strategy, and then employ the causal weights to reweight the weight vectors of PLS to enhance the influence of causal variables in the KPI-related principal subspace and reduce the influence of spurious correlations. Case studies based on a simulated dataset, Tennessee Eastman Process dataset and field data from finishing rolling mill process show that the proposed methods can significantly reduce the false alarm rate for KPI-unrelated faults (i.e., the probability that a KPI-unrelated fault sample is mis-regarded as a KPI-related fault sample) caused by spurious correlation without significantly compromising the fault detection rate of KPI-related faults.