Improvement Of Processes Research Articles

Cost-Effective Temperature Sensor for Monitoring the Setting Time of Concrete

Concrete and Portland cement-based products are the most widely used materials in the construction industry. According to the Global Cement and Concrete Association (GCCA), 14 billion cubic meters of concrete are consumed worldwide every year. Knowledge of their properties is essential to ensure the quality of concrete products and structures. Knowing the evolution of certain parameters related to their durability makes it possible to prevent situations that affect compliance with quality requirements. Thanks to advances in IoT (Internet of Things) technologies, it is possible to know the evolution of these parameters in real time. The following work pursues the development and application of a prototype to monitor the setting time of concrete. This equipment provides real-time measurements, taking advantage of the Internet of Things (IoT) technology, allowing effective monitoring of the thermal behavior of concrete during its setting process. By measuring the temperature of the process and evaluating the resistance acquired during the setting time, we can correlate these two parameters, thus ensuring their correct evolution and allowing quick action to avoid future problems. For the development of this work, temperature measurements were made during the setting of 12 concrete specimens corresponding to four different mixtures (two types of cement with and without additives), assessed at three setting ages (28, 90, and 180 days). Through detailed experimental tests, the sensor was accurately and reliably validated, showing its ability to detect temperature changes, indicating the initial and final setting time. In addition, it was observed that the integration of the DS18B20 sensor does not compromise the structural properties of the concrete. The prototype’s cost-effectiveness, efficiency, and easy installation make it a valuable tool for construction professionals, offering an innovative solution to ensure the quality and durability of the concrete. This breakthrough could represent a significant step towards the digitalization and improvement of construction processes, with direct implications for the efficiency and sustainability of modern infrastructures.

Seed for the Future: Agricultural Advancement and Innovation for Sustainability Food Systems in Tanza, Cavite

Through the perspectives and adaptations of local farmers, this qualitative case study explores agricultural innovations and progress toward sustainable food systems in Tanza, Cavite. Using purposive sampling, the study included eight participants to investigate several important topics, including technology integration, the role of institutions and the government, and the continuous improvement of processes within the agricultural community. Six main themes are revealed by the results: an evolution from conventional to organic farming methods; the technological revolution enhancing productivity; overcoming challenges by innovative solutions; substantial government support affecting agricultural practices; the value of lifelong learning for ongoing development; and innovative farming methods such as the "rap giant" approach. These themes show how Tanza, Cavite, is experiencing a dynamic transition to more efficient and sustainable farming methods, supported by technology and legal structures that improve production, environmental sustainability, and community well-being.

Public Administration Analysis of Bleaching Motorized Vehicle Tax in Gorontalo Province

faced by the Gorontalo Provincial government in increasing local revenue (PAD) from the sector. The method used is a qualitative approach, with primary and secondary data collection to get an in-depth picture. The results showed that motor vehicle tax bleaching is part of the tax administration reform efforts aimed at improving performance through the improvement of administrative processes that are more efficient, economical, and responsive. In addition, this study also identifies various challenges in implementing the policy, including institutional, group, and individual aspects, which need to be addressed to maximize the potential revenue from the motor vehicle tax sector. This research provides recommendations for an improved tax administration system that can support the achievement of PAD targets more optimally.

Harnessing Text and Web Analytics to Enhance Decision-Making in Job Opportunity Categorization

Text analytics is defined as a method of analyzing compilations of structured text such as dates, times, locations, semi structured text, such as HTML and JSON as well as unstructured text, such as word documents, videos, and images, to extract and discover trends and relationships without requiring the exact words or terms to convey those concepts. Web analytics on the other hand is the technology that collects, measures, analyses, and provides reports of data on how users use websites and web applications. It is used to track a number of aspects of direct user-website interactions, such as the number of visits, time spent on the site, and click pathway. It also aids in the identification of user interest areas and the enhancement of web application features. We used clustering techniques to categorize the job opportunities that are available for the job seekers. By implementing text analytics, text data may be grouped with the goal of providing outcomes in the form of word frequency distribution, pattern identification, and predictive analytics. Text analytics may create one-of-a-kind values to use in the improvement of decision-making and business processes, as well as the development of new business models.

Effluent quality improvement in sequencing batch reactor-based wastewater treatment processes using advanced control strategies.

The treatment of wastewater is highly challenging due to large fluctuations in flowrates, pollutants, and variable influent water compositions. A sequencing batch reactor (SBR) and modified SBR cycle-step-feed process (SSBR) configuration are studied in this work to effectively treat municipal wastewater while simultaneously removing nitrogen and phosphorus. To control the amount of dissolved oxygen in an SBR, three axiomatic control strategies (proportional integral (PI), fractional proportional integral (FPI), and fuzzy logic controllers) are presented. Relevant control algorithms have been designed using plant data with the models of SBR and SSBR based on ASM2d framework. On comparison, FPI showed a significant reduction in nutrient levels and added an improvement in effluent quality. The overall effluent quality is improved by 0.86% in FPI in comparison with PI controller. The SSBR, which was improved by precisely optimizing nutrient supply and aeration, establishes a delicate equilibrium. This refined method reduces oxygen requirements while reliably sustaining important biological functions. Focusing solely on the FPI controller's performance in terms of total air volume consumption, the step-feed SBR mechanism achieves an excellent 11.04% reduction in consumption.

Improving Manufacturing Efficiency with Industry 4.0 Technologies: A Comparative Analysis of Smart Factories

The advent of Industry 4.0 technologies has ushered in a new era of manufacturing marked by the integration of cyber-physical systems, data-driven decision-making, and automation. This study presents a comprehensive comparative analysis of the impact of Industry 4.0 technologies on manufacturing efficiency through a focus on smart factories. The research examines how these technologies, such as the Internet of Things (IoT), artificial intelligence, and advanced robotics, contribute to operational improvements across diverse manufacturing environments. The methodology involves a comparative case study approach, analyzing multiple smart factories from various industries to identify common trends and distinct challenges. Key performance indicators (KPIs) related to efficiency, productivity, and resource utilization are assessed, providing a nuanced understanding of the transformative effects of Industry 4.0. The findings reveal that the implementation of smart technologies leads to significant improvements in production processes, reduced downtime, and enhanced product quality. Furthermore, the study explores the challenges encountered during the adoption of Industry 4.0, including cybersecurity concerns, workforce upskilling, and the integration of legacy systems. Insights gained from successful implementations serve as a guide for manufacturers seeking to optimize their operations through the adoption of Industry 4.0 technologies. The research contributes to the existing literature by offering a comparative perspective on smart factories, shedding light on best practices, and facilitating a deeper understanding of the factors influencing successful Industry 4.0 adoption.

Patterns of cognitive-emotional change after cognitive-behavioural treatment in emotional disorders: A 12-month longitudinal cluster analysis.

The aim of this study was to use cluster analysis based on the trajectory of five cognitive-emotional processes (worry, rumination, metacognition, cognitive reappraisal and expressive suppression) over time to explore differences in clinical and performance variables in primary care patients with emotional symptoms. We compared the effect of adding transdiagnostic cognitive-behavioural therapy (TD-CBT) to treatment as usual (TAU) according to cluster membership and sought to determine the variables that predicted cluster membership. 732 participants completed scales about cognitive-emotional processes, anxiety and depressive symptoms, functioning, and quality of life (QoL) at baseline, posttreatment, and at 12 months. Longitudinal cluster analysis and logistic regression analyses were carried out. A two-cluster solution was chosen as the best fit, named as "less" or "more" improvement in cognitive-emotional processes. Individuals who achieved more improvement in cognitive-emotional processes showed lower emotional symptoms and better QoL and functioning at all three time points. TAU+TD-CBT, income level, QoL and anxiety symptoms were significant predictors of cluster membership. These results underscore the value of adding TD-CBT to reduce maladaptive cognitive-emotional regulation strategies. These findings highlight the importance of the processes of change in therapy and demonstrate the relevance of the patient's cognitive-emotional profile in improving treatment outcomes.

Diamond-Like Carbon (DLC) Coatings : Classification, Properties, and Applications

This paper presents the most recent and important research trends on the friction and wear properties of diamond like carbon (DLC) coatings deposited on different types of materials. For this the invention, methods, techniques, and design related to this area are discussed. The different trends of tribological properties of materials under different operating conditions are observed. In this article, an attempt is made to provide an opportunity for the future researchers to identify the recent trend of these areas. It is expected that the applications of these results will contribute to the improvement of different concerned mechanical processes. This review article also includes some patents relevant to the method of producing a DLC film.

The Construction of the Pedagogical Space from the Narratives of the Early Childhood Education Teachers

Environments or learning spaces in school classrooms contribute to the improvement of educational processes. Specifically, in the Early Childhood Education, teachers can design learning spaces, which fosters an environment of safety and autonomy for the students of the Early Childhood Education. This study explores the teachers' narratives concerning the meanings they assign to the school space, the criteria by which they design and transform it, and its connection to model of educational. We have collected 34 stories of pre-primary education teachers through a semi-structured interview in which they had to reflect on this pedagogical design. As most relevant result we identify a model sustained under constructivist or cognitive criteria, rather than a dialogical one. We conclude that this epistemological perspective of the construction of the school environment should be oriented towards a more participatory and co-constructed model of the educational space.

Radiometry of forest canopies

The work is devoted to satellite microwave radiometric methods, which are of great scientific and practical interest for studies of tropical, temperate and boreal forests. Task: It is to assess the relevance and technological priorities of satellite microwave radiometry in relation to monitoring environmental and climatic processes occurring in forest canopies. The priorities and advantages of using satellite microwave radiometry in studying radiothermal radiation of forest canopies are highlighted. Obstacles in the development of this technology are noted. The results of the study can be used for decision-making in the field of technological renewal and improvement of forest ecosystem analysis processes. The article can also be useful for specialists working in the field of development and implementation of innovative technologies.

Technology Processes and Business Performance of Commercial Banks in Kenya

The general objective of the study was to examine the role of Technology Processes on business performance of Commercial Banks in Kenya. The philosophy that guided the research is positivism philosophy. The study adopted correlational research design. The target population was commercial Banks in Kenya register by the Central Bank of Kenya. The population consisted of all 42 commercial banks in Kenya. Respondents’ population comprised of five top managers from each bank translating to 210 top managers. Slovin’s formula was used to calculate the sample size. Purposive sampling technique was used to select 138 top managers of the 42 commercial Banks in Kenya. This study used a self-administered, closed and open-ended questionnaire to obtain primary data. A pilot study was conducted to test the validity and reliability of the data collection instrument. Quantitative data was collected and analyzed in this study by calculating the response rate with descriptive statistics such as mean, standard deviation, median and proportions using the Statistical Package for Social Sciences (SPSS) version 24). Regression analysis and correlation analysis was used to carry out inferential data analysis to determine the direction and strength of the relationship between the independent and the dependent variables. In order to test the influence of information technology capability on business performance of Commercial Banks in Kenya, the study employed a hierarchical regression analysis with moderation. The study results were presented through use of tables and figures. The study concludes that technology processes has a positive and significant effect on business performance of Commercial Banks in Kenya. The study revealed that idea generation, technology acquisition and technology Implementation influence business performance of Commercial Banks in Kenya. This implies that improvement in information technology processes (idea generation, technology acquisition and technology Implementation) would lead to improvement in business performance of Commercial Banks in Kenya. Based on the findings, the study recommends that the management of commercial banks in Kenya should ensure they have in place an effective plan for idea generation, technology acquisition and technology Implementation.

The use of native yeasts to improve the organoleptic characteristics and yield of artisanal mezcal

Objective: To assess the use of native yeasts on the yield and on the organoleptic characteristics of artisanal mezcal in Guerrero, Mexico. Design/Methodology/Approach: Native yeasts from fermentation vats containing Agave angustifolia and A. cupreata were subjected to molecular isolation and identification in three regions of the state of Guerrero. A consortium of yeasts was designed and used to produce artisanal mezcal, using A. cupreata as a substrate. The experimental mezcal (with yeasts) and the control (without yeasts, only producer lore) were compared. Finally, the physicochemical and sensory characteristics of the final product were assessed at the Concours Mondial de Bruxelles 2020. Results: S. cerevisiae A5GM, T. delbrueckii A6GM, S. cerevisiae A3GM, and K. marxianus A2GM were identified and used in a consortium that produced 46% more yield (8.3 kg L-1 compared to 10.5 kg L-1). The mezcal produced with this consortium obtained the Grand Gold medal based on its sensory characteristics. Study Limitations/Implications: To work with the producer in both systems with and without yeast. Findings/Conclusions: The consortium improved the production yield by 26%, along with the sensory characteristics; therefore, the use of native yeasts is feasible and recommended for the improvement of processes in the production of artisanal mezcal from Guerrero.

Transfer Dynamic Latent Variable Modeling for Quality Prediction of Multimode Processes.

Quality prediction is beneficial to intelligent inspection, advanced process control, operation optimization, and product quality improvements of complex industrial processes. Most of the existing work obeys the assumption that training samples and testing samples follow similar data distributions. The assumption is, however, not true for practical multimode processes with dynamics. In practice, traditional approaches mostly establish a prediction model using the samples from the principal operating mode (POM) with abundant samples. The model is inapplicable to other modes with a few samples. In view of this, this article will propose a novel dynamic latent variable (DLV)-based transfer learning approach, called transfer DLV regression (TDLVR), for quality prediction of multimode processes with dynamics. The proposed TDLVR can not only derive the dynamics between process variables and quality variables in the POM but also extract the co-dynamic variations among process variables between the POM and the new mode. This can effectively overcome data marginal distribution discrepancy and enrich the information of the new mode. To make full use of the available labeled samples from the new mode, an error compensation mechanism is incorporated into the established TDLVR, termed compensated TDLVR (CTDLVR), to adapt to the conditional distribution discrepancy. Empirical studies show the efficacy of the proposed TDLVR and CTDLVR methods in several case studies, including numerical simulation examples and two real-industrial process examples.

Devising a technique for assessing the accuracy of measuring electric motor torque

The object of this study is a technique for assessing the accuracy of measuring the torques of electric motors. This technique is based on the improvement of dynamic torque measurement processes under transient operating modes. Special attention was paid to devising adaptive methods to normalize the output signal, which take into account vibrations and nonlinearities of the measuring channel. In order to improve the accuracy of measurements under conditions when the controlled parameter has different deviations from its average value, a technique for integrating time measurement intervals was proposed. That has made it possible to generalize parameter fluctuations, providing more stable measurement results. This paper reports the simulation of the process of measuring torques of electric motors under transient operating modes and under vibration conditions. That has made it possible to test the proposed technique for estimating the variance of the methodological error, which includes the integration of measurement time intervals and makes it possible to increase the accuracy of the measurement under the conditions of transient modes in electric motor operation. An algorithm for correcting the error of the dynamic torque of the electric motor has been proposed, which allows it to be corrected. This becomes possible owing to the use of a reference measure and the proposed technique for determining the deviations of the controlled parameter of the measured quantity, as well as the automatic calibration of measuring transducers. The algorithm allows for flexible settings of the corrective action, expanding the potential of electric motor control systems. It can complement soft measurement methods, as well as adjust the threshold values of deviations under different operating modes of electric motors. This allows the measured systems to better adapt to changes in operating conditions, to adjust the specified measurement accuracy under conditions of uncertainty

Responsible composition and optimization of integration processes under correctness preserving guarantees

Enterprise Application Integration deals with the problem of connecting heterogeneous applications, and is the centerpiece of current on-premise, cloud and device integration scenarios. For integration scenarios, structurally correct composition of patterns into processes and improvements of integration processes are crucial. In order to achieve this, we formalize compositions of integration patterns based on their characteristics, and describe optimization strategies that help to reduce the model complexity, and improve the process execution efficiency using design time techniques. Using the formalism of timed DB-nets – a refinement of Petri nets – we model integration logic features such as control- and data flow, transactional data storage, compensation and exception handling, and time aspects that are present in reoccurring solutions as separate integration patterns. We then propose a realization of optimization strategies using graph rewriting, and prove that the optimizations we consider preserve both structural and functional correctness. We evaluate the improvements on a real-world catalog of pattern compositions, containing over 900 integration processes, and illustrate the correctness properties in case studies based on two of these processes.

Cross-industry frameworks for business process reengineering: Conceptual models and practical executions

Cross-industry frameworks for business process reengineering (BPR) have emerged as pivotal tools in enhancing organizational efficiency, agility, and competitiveness across diverse sectors. These frameworks amalgamate conceptual models with practical executions to streamline operations, optimize resource allocation, and foster innovation. This review delves into the essence of cross-industry frameworks for BPR, elucidating their conceptual underpinnings and real-world applications. At the core of cross-industry frameworks lies the recognition that business processes transcend sector boundaries, encompassing common elements such as customer interactions, supply chain management, and operational workflows. Conceptual models form the foundational framework by articulating key principles, methodologies, and best practices for BPR initiatives. One prominent conceptual model is the Business Process Reengineering (BPR) methodology, which advocates for radical redesign rather than incremental improvement of processes. This approach emphasizes fundamental questioning of existing practices, aiming to achieve dramatic enhancements in efficiency, quality, and customer satisfaction. Another influential model is the Capability Maturity Model Integration (CMMI), which provides a roadmap for organizations to systematically improve their processes by advancing through defined maturity levels. Practical executions of cross-industry frameworks entail the translation of conceptual models into actionable strategies tailored to specific organizational contexts. This involves a multifaceted approach encompassing process analysis, stakeholder engagement, technology integration, and change management. Process analysis entails mapping current workflows, identifying bottlenecks, and pinpointing areas for optimization. Stakeholder engagement is crucial for garnering buy-in and fostering a culture of continuous improvement. Technology integration plays a pivotal role in modern BPR initiatives, leveraging digital tools such as business process management (BPM) software, data analytics, and robotic process automation (RPA) to streamline operations and enhance decision-making. Moreover, emerging technologies like artificial intelligence (AI) and blockchain offer new avenues for process innovation and optimization. Change management constitutes a critical component of practical executions, as BPR initiatives often entail significant organizational transformation. Effective change management involves communication, training, and leadership support to mitigate resistance and facilitate smooth transition. Real-world applications exemplify the effectiveness of cross-industry frameworks in driving tangible business outcomes. Case studies spanning diverse sectors, including manufacturing, healthcare, finance, and retail, demonstrate how organizations have leveraged BPR to achieve breakthrough improvements in efficiency, cost reduction, and customer satisfaction. In the manufacturing sector, for instance, companies have adopted lean manufacturing principles to streamline production processes, minimize waste, and enhance flexibility. In healthcare, BPR initiatives have led to streamlined patient care pathways, reduced administrative burdens, and improved clinical outcomes. Financial institutions have leveraged BPR to optimize loan approval processes, mitigate risk, and enhance regulatory compliance. Similarly, retailers have utilized BPR to optimize supply chain management, enhance omnichannel capabilities, and personalize customer experiences. Cross-industry frameworks for business process reengineering represent a potent paradigm for organizational transformation in today's dynamic business landscape. By integrating conceptual models with practical executions, these frameworks empower organizations to enhance operational efficiency, drive innovation, and maintain competitive advantage across diverse sectors.

Rapid conversion of heterotrophic denitrification to autotrophic denitrification in mariculture wastewater treatment: Denitrification performance and microbial communities under antibiotic stress

Mariculture wastewater, characterized by a low COD/Nitrogen (C/N) ratio and the occurrence of antibiotics, is commonly treated by a heterotrophic denitrification (HD) process with supplying substantial carbon sources. Compared to HD, sulfur-based autotrophic denitrification (AD) requires less external carbon sources and is more favorable for low-carbon wastewater treatment. However, the AD process often consumes more startup time. Thus, the present study was designed to explore a rapid startup strategy for the AD process by switching from HD to AD, treating mariculture wastewater. A rapid transformation from HD to AD was achieved by inoculating mixotrophic denitrifying sludge, reducing carbon sources and adding sulfur sources under the antibiotic sulfamethoxazole (SMX). From the functional microbial community point of view, our results showed that autotrophic bacteria exhibited greater adaptability to sulfamethoxazole than heterotrophic bacteria. During the transition from HD to AD, nitrate removal improved from 53.13 % to 68.57 %, and the secretion of tightly bound extracellular polymeric substances (TB-EPS) increased by 29.94 mg/g VSS. Meanwhile, in the heterotrophic phase, the presence of sulfate in mariculture wastewater maintained a high abundance of sulfate-reducing bacteria such as Desulfuromusa (0.8 %) and sulfur-based autotrophic denitrifying bacteria such as Sedimenticola (36.7 %) and Thiogranum (15.2 %). This increases the activity of sulfur metabolism during the heterotrophic phase and ensures a rapid transition from HD to AD. The rapid shift from HD to AD in seawater under antibiotic stress provides theoretical support for the improvement of mariculture wastewater treatment processes.

The impact of procurement strategies on supply chain sustainability in the pharmaceutical industry

In today's society, there is a major role that procurement is playing in sustainability because of great requirements and demand for improvement in some supply chain processes and procurement practices. It helps in making rational decisions that encompass economic, social, and environmental parts of society. Corporate sustainability requires such abilities to impact external firms in the process of supply chain. In the Economic advancement markers worldwide, public and neighbourhood levels advance sustainability approaches are advised, as they represent the advancement in the supply chain process. By implementing procurement strategies in the pharmaceutical industry elements of supply chain sustainability can improve environmental, social a financial impact on society. It is a cross-sectional study. The present study was conducted in the urban areas of Karachi, Pakistan. Data collection will be through questionnaires and surveys. It is designed for information collection so it can be used to determine the improvement and impact of sustainability on procurement strategies in supply chain sustainability.

Unlocking the potential: a study on the role of operational excellence in Oman’s energy sector

PurposeOperational excellence (OpEx) is a proven philosophy focusing on continuous improvement in processes and systems for superior performance and efficiency. It plays a crucial role in the energy sector, acting as a catalyst for safety, customer satisfaction, sustainability and competitiveness. This research aims to assess OpEx methodologies in Oman’s energy sector, examining methods, approaches, motivations and sustainability.Design/methodology/approachThis study applies qualitative analysis methodology, involving interviews with 18 industry experts, from the energy sector in a sizeable energy country.FindingsThe analysis revealed a growing demand, particularly, in the oil and gas industry, driven by emerging business needs. Qualitative data analysis has identified 10 themes such as implemented methodologies, motivation drivers, deployment approaches, sustainability factors, benefits and challenges. Additionally, new themes emerged, including influencers to start OpEx, resource requirements, enablers for successful OpEx and systems.Research limitations/implicationsThis research was limited to Oman and the findings drawn from Omani energy companies may have limited applicability to energy companies in other regions. Therefore, if these findings were to be used, the validation of the findings in relation to other countries should be conducted, to ensure the validity of the context and outcome.Practical implicationsThese findings contribute to understanding OpEx dynamics in the Omani energy sector, offering valuable insights for effective utilisation and organisational goal achievement. Furthermore, the study offers valuable insights on how to effectively employ OpEx initiatives in the energy sector to achieve their goals and create value. It addresses the lack of knowledge, offers a framework for successful OpEx implementation, bridges the theory-practice gap and provides insights for optimal utilisation.Originality/valueTo the best of the authors’ knowledge, this is the first empirical study on assessing OpEx methodologies in the energy sector, and therefore it serves as a foundation for many future studies. The study provides a theoretical foundation for the OpEx methodologies in terms of organisational readiness for successful OpEx implementation.

Науково-методичні аспекти аналітики сучасних бізнес-моделей інфраструктурних рішень

Modern infrastructure is a complex of systems, networks, objects and technologies that ensure the effective functioning of society and the economy in the conditions of modern challenges and technological progress. The creation and maintenance of such infrastructure is a critically important aspect for the development of the country, its competitiveness and ability to adapt to new conditions. The introduction of innovative methods, such as the business process approach, allows creating efficient and adaptive infrastructure systems. At the same time, business practices have not become sufficiently widespread in infrastructure enterprises, which is an important problem in the conditions of directing significant funds to restore damaged and create new infrastructure. The purpose of the research is to determine the features of the business model of infrastructural solutions and to develop proposals for evaluating its effectiveness. The study identifies the key elements of the infrastructure services business model. The main directions of transformation of business models in the infrastructural sphere are considered. In accordance with modern management standards, the key principles of the concept of continuous improvement of business processes in the field of service enterprises have been defined. DEA analysis was used for the comparative assessment of the effectiveness of the business model of business structures based on the results.