Improve Process Efficiency Research Articles

A Post-Evaluation System for Smart Grids Based on Microservice Framework and Big Data Analysis

Wind energy, as a clean energy source, has been experiencing rapid development in recent years. However, there is often a significant difference between the designed electricity generation capacity and the actual electricity generation capacity during the construction of wind farms, making it difficult to assess the economic benefits of wind farms. Therefore, the development post-evaluation technology is required to support the renovation of old wind farms. In addition, traditional data analysis techniques are unable to handle and analyze massive data in a timely manner. Therefore, big data technology must be developed to improve processing efficiency. To address these issues and meet actual business needs, this paper designs an intelligent grid electricity generation post-evaluation platform for wind farms based on a microservice framework and big data analysis technology. The platform evaluates the operating status of wind farms by analyzing their operational and design data and visualizes relevant big data information. It provides technical support and improvement solutions for wind farm renovation and new wind farm construction. The platform has been tested and proven to meet the requirements for processing and analyzing massive data, post-evaluating electricity generation, and visualization.

Analysis of Standard Operational Procedure Submission of Special Ceiling For Sales Division

This study aims to analyze the standard operating procedure (SOP) for filing an exceptional ceiling for the sales division at PT. Semen Baturaja (Persero) Tbk. This study uses a qualitative research design with a case study approach. Data was collected through interviews, document analysis, and observation of the SOP submission process for the sales division at PT. Semen Baturaja (Persero) Tbk. This study's findings are whether the Standard Operational Procedure for Submission of Special Ceilings has been going well or not. Standard operating procedures that are running well are shown in the Special SOP for Ceiling Submission; this can happen because it is in the preparation process so that, in practice, SOPs can be easily understood and also efficiently implemented by distributors. While implementing the main things in the Standard Operating Procedures is good because it has been appropriately implemented in every job, there's just no workflow in the Sales Division. In addition, there are due distributor receivables, so it becomes an obstacle for distributors to apply for a Special Ceiling according to the Standard Operating Procedure (SOP). This research contributes to the literature on SOPs by highlighting the importance of well-defined and effectively implemented SOPs in the context of the sales division of PT. Semen Baturaja (Persero) Tbk. In addition, this study provides insight into the challenges and factors that may influence SOP implementation in this environment. Practical implications for the management of PT. Semen Baturaja (Persero) Tbk and sales division. The findings indicate the need for more detailed and simplified SOPs for special ceiling proposals to improve process efficiency. In addition, this study recommends that companies provide adequate training and support for employees involved in the process. This research is limited to one case study at PT. Semen Baturaja (Persero) Tbk and these findings may not be generalizable to other companies or industries. In addition, this study does not evaluate the impact of implementing improved SOPs on sales division performance. Future research can explore these areas and assess the effectiveness of various strategies to improve the unique ceiling application process in sales divisions in peer companies in Indonesia.

Controller Design and StabilityAnalysis of Intensification Process using Analytical Exact Gain-Phase Margin approach.

The controllable intensified process has received immense attention from researchers in order to deliver the benefit of process intensification to be operated in a desired way to provide a more sustainable process toward reduction of environmental impact and improvement of intrinsic safety and process efficiency. Despite numerous studies on gain and phase margin approach on conventional process systems, it is yet to be tested on intensified systems as evidenced by the lack of available literature, to improve the controller performance and robustness. Thus, this paper proposed the exact gain and phase margin (EGPM) through analytical method to develop suitable controller design for intensified system using Proportional-Integral-Derivative (PID) controller formulation, and it was compared to conventional Direct Synthesis methods (DS), Internal Model Control (IMC), and Industrial IMC method in terms of the performance and stability analysis. Simulation results showed that EGPM method provides good setpoint tracking and disturbance rejection as compared to DS, IMC, and Industrial IMC while retaining overall performance stability as time delay increases. The Bode Stability Criterion was used to determine the stability of the open-loop transfer function of each method and the result demonstrated decrease in stability as time delay increases for controllers designed using DS, IMC, and Industrial IMC, and hence control performance degrades. However, the proposed EGPM controller maintains the overall robustness and control performance throughout the increase of time delay and outperform other controller design methods at higher time delay with [Formula: see text] uncertainty test. Additionally, the proposed EGPM controller design method provides overall superior control performance with lower overshoot and shorter rise time compared to other controllers when process time constant is smaller in magnitude ([Formula: see text]) than the instrumentation element, which is one of the major concerns during the design of intensified controllers, resulting overall system with a higher order. The desired selection of gain margin and phase margin were suggested at 2.5 to 4 and 60 °-70[Formula: see text],respectively, for a wide range of control conditions for intensified processes where higher instrumentation dynamic would be possible to achieve robust control as well. The proposed EGPM method controller is thought to be a more reliable design strategy for maintaining the overall robustness and performance of higher order and complex systems that are highly affected by time delay and high dynamic response of intensified processes.

On the role of multifunctional ionic liquids for the oxidative carboxylation of olefins with carbon dioxide

Ionic liquids (ILs) are catalysts with profound effects on the activity and selectivity for the transformation of CO2. In particular, highly functionalisable and immobilisable imidazolium based ILs (ImILs) activate CO2 molecules and have demonstrated activity towards CO2 cycloaddition reactions. The addition of hydroxyl groups has also been reported to enhance the cycloaddition reaction. An ideal system would combine both functionalities for superior performance. In addition, integrating the cycloaddition with the epoxidation of olefins employing multifunctional catalysts in one-pot would improve process efficiency, reduce waste and costs. However, the interaction between the cation-anion and the hydroxyl groups needs to be elucidated to realize these advantages. Herein, the viability of using ILs as bifunctional catalyst for one-pot reaction is evaluated by combining theoretical and experimental studies. Density functional theory (DFT) simulations of both reactions using halogenated and hydroxyl functionalized ImLs are presented. The position of the hydroxyl group close to the imidazolium unit primarily influences the opening of the epoxide and its activation for the cycloaddition reaction, thus facilitating the catalysis. In addition, experimentally the selectivity increases considerable with the catalyst immobilization. For the epoxidation reaction the DFT calculations and experimental results demonstrated favoring hydrolysis reaction.

Effect of Salt Content on Biogas Production and Microbial Activity: Review Study

Over the years, biogas production technology has advanced with the goal of reducing process costs and greenhouse gas emissions, and increasing biogas production. Several design factors and operational aspects must be taken into account in order to produce a stable and efficient biogas. When the substrates contain high salts, anaerobic treatment will be ineffective due to the disadvantages of high energy input and operating cost, membrane contamination, and low efficiency. This indicates that the treatment of high salinity organic waste is a big challenge. High salinity levels had a negative effect on bacterial growth through bacterial osmotic pressure metabolism. For example, high salinity can alter the course of fermentation and the accumulation of volatile fatty acids at high concentrations, as well as cause a decrease in methane yield and maximum rate of methane production, prolonging the late-stage period. A low level of salt concentration encourages the growth of bacteria since sodium is essential for the growth and metabolism of microorganisms in AD systems. When the sodium salt concentration is less than 8 g/L, there is no significant inhibition in the generation of methane. Addition of >8 g/L NaCl, however, significantly reduced methane production (causing 17-80 percent inhibition). This paper focuses on understanding in detail how NaCl affects methane production and microbial activity, report salt concentrations that improve process efficiency and reduce inhibition, as well as review the modified kinetic model and demonstrate the effect of salt on methane production and delay in methanogenesis.

Efficient and low-damage machining of Ti6Al4V: laser-assisted CBN belt grinding

ABSTRACT This study introduces a new method for efficient and low-damage machining of Ti6Al4V: laser-assisted CBN belt grinding. The impact of laser power and grinding depth on the machining behavior of the material is investigated, the elemental distribution and chemical state of the ground surface are analyzed, and the removal mechanism of laser-assisted CBN belt grinding is described. The results show that increasing laser power will improve processing efficiency, enhance plastic material removal, and improve surface quality; the tangential grinding force is decreased by 63.5% and the normal grinding force is decreased by 72.6% at the maximum laser power; a large amount of Ti and N are present on the ground surface, and they are present in the form of TiN compounds. This study is a guide to the research on efficient and low-damage machining of hard-to-process materials like titanium alloys.

Integrating BIM and Blockchain across construction lifecycle and supply chains

The Construction industry has a complex structure with multiple parties involved, which often leads to “adversarial relationships”, “risk avoidance”, and a “lack of trust” among the different actors. This culture is further compounded by a “linear workflow” that often results in low efficiency, delays, rework and unnecessary waste. Blockchain technology can help to mitigate these issues by creating a decentralised and transparent system, where all the actors can have access to a shared database, it allows tracking and monitors the different stages of the project, and even automate some processes increasing efficiency and reducing delays and rework.This study highlights the advantages of Blockchain technology, particularly how it can provide a single source of truth for project data while allowing multiple parties to access and share data in a secure and transparent way, improving the workflow of BIM projects and decreasing the likelihood of errors, mistakes, or fraudulent activities. The paper explores the integration of BIM and Blockchain across life cycle and supply chains based on the RIBA plan of work, with the objective to streamline collaboration while improving process efficiency and resource traceability in projects. The study proposes a roadmap performing a detailed literature survey for Blockchain adoption in the construction industry, and validated on a real-world Bridge project. Furthermore, this study is innovative since it examines the integration of BIM and Blockchain throughout the entire project lifecycle by simulating the smart contract implementation based on the RIBA plan of work, thus providing an in-depth examination of the potential benefits of this integration.

Prediction of tool wear in milling process based on BP neural network optimized by firefly algorithm

Long-time discontinuous contact is easy to cause tool wear during milling. To decrease the impact of severe wear on workpiece quality and processing efficiency, cutting tools should be replaced timely. Therefore, tool wear prediction is an important aspect in improving process efficiency, ensuring machining precision and realizing intelligent manufacturing. To boost the precision of online prediction of tool wear, this paper suggests a novel approach to monitor tool wear by optimizing backpropagation (BP) neural network via firefly algorithm (FA). Specifically, the progressive semi-soft threshold function is applied to the process of cutting force signal noise reduction, which reduces redundant signals and noise interference in the signal. Time-domain analysis, frequency-domain analysis, and wavelet packet decomposition are utilized, cutting force features are extracted, and Pearson correlation coefficient is used to sift out signal features that are highly connected to tool wear. The FA is used to improve the BP neural network's weights and thresholds. Through learning nonlinear mapping, relationship between tool flank wear and signal features is realized. A prediction model of tool wear of FA-BP is constructed. Milling experiments validate the prediction model in the milling process. The experimental outcomes confirm the precision and reliability of the method. In comparison to BP neural network, genetic algorithm optimized BP neural network and particle swarm optimization algorithm optimized BP neural network prediction method, it has a greater prediction accuracy and a stronger training impact, and has superior performance. The research results can give a theoretical foundation and technological assistance for predicting tool wear, which is crucial for improving workpiece quality, processing efficiency, and promoting intelligent development.

Reduced processing efficiency impacts auditory detection of amplitude modulation in children: Evidence from an experimental and modelling study

Detection of amplitude modulations (AM) improves until 10 years of age. This development may not be explained only by sensory maturation but also by improvements in processing efficiency: the ability to make efficient use of available sensory information. This hypothesis was tested on 86 6-to-9-year-olds and 15 adults using AM-detection tasks assessing sensitivity, masking and response consistency. Sensitivity was estimated by the detection thresholds of a sinusoidal AM applied to a pure-tone carrier; AM masking was estimated as threshold elevation produced when replacing the pure-tone carrier by a narrowband noise; response consistency was estimated using a double-pass paradigm where the same set of stimuli was presented twice. Results showed that AM sensitivity improved from childhood to adulthood. AM masking did not change with age, indicating that the selectivity of AM filters was adult-like by 6 years. However, response consistency increased developmentally, suggesting reduced processing efficiency in childhood. At the group level, double-pass data were well simulated by a model of the auditory system assuming higher internal noise for children than adults. At the individual level, a sub-optimal decision strategy was added to better capture inter-individual variability. Thus, both systematic and stochastic inefficiencies may explain worse AM detection in childhood.

Hurdle effect of thermosonication and non‐thermal processing on the quality characteristics of fruit juices: An overview

AbstractTraditional thermal processing technologies are widely used to extend the shelf life of fruit juices. However, its detrimental effect on the nutritional and sensory properties of fruit juices paved the way for alternative food processing technologies. Non‐thermal processing methods can be a substitute for thermal methods because they have no/minimal effect on the nutritive and sensory qualities of fruit juices and improve their storage quality by deactivating enzymes and eliminating microorganisms. In this review article, combined use of thermosonication (TS) with other non‐thermal processing technologies in fruit juice processing has been detailed. Additionally, the impact of TS on the various qualities of fruit juices as well as the TS mechanism have been covered. TS, one of the emerging non‐thermal technologies have been preferred in fruit juice and beverage processing industries over the past few years, due to consumer's preference towards high quality and nutritious food products. When TS is employed in combination with other non‐thermal processing methods, it reduces processing time, improves process efficiency, and reduces power consumption. The content of this review paper might be beneficial for upcoming research and the commercialization of this hurdle‐based approach.Practical ApplicationsGenerally, fruit juices were treated using thermal methods (e.g., pasteurization) for extending the shelf life by inactivating microbial and enzymatic activities. But it shows negative impact on the nutritional and sensorial attributes of fruit juices. Non‐thermal technologies like, TS has been preferred as an alternative method for the processing of juices due to their less/no effect on the quality parameters of juices. The benefits of TS as compared with thermal treatments include less flavor loss, significant energy savings, and increased homogeneity. TS reduces the processing temperature and time required for pasteurization of juices and it can be used to make high‐quality fruit juices that are additive‐ and preservative‐free. In the review, the effect of TS on fruit juice quality as well as its combined effect with high pressure processing and pulse electric field processing has been summarized. The finding of this review paper might be helpful for the further exploration of these technologies in the large‐scale food industries.

Bioreactors and biophoton-driven biohydrogen production strategies

Given the current issues with global warming and rising greenhouse gas emissions, biohydrogen is a viable alternative fuel option. Technologies to produce biohydrogen include photo fermentation, dark fermentation, direct and indirect bio-photolysis, and two-stage fermentation. Biological hydrogen generation is a green and promising technique with mild reaction conditions and low energy consumption compared to thermochemical and electrochemical hydrogen generation. To optimize hydrogen gas output using this method, the activity of hydrogen-consuming bacteria should be restricted during the production stages of hydrogen and acetate to prevent or limit hydrogen consumption. Raw material costs, poor hydrogen evolution rates, and large-scale output are the main limitations in biological hydrogen generation systems. Organic wastes would be the most preferred target feedstock for hydrogen fermentation, aside from biodegradable wastes, due to their high amount and simultaneous waste treatment advantage. This study examined the three primary methods for converting waste into bio-hydrogen: microbial electrolysis cell, thermochemical gasification, and biological fermentation, from both a technological and environmental standpoint. The effectiveness and applicability of these bioprocesses in terms of aspects influencing processes and their constraints are discussed. Alternative options for improving process efficiency, like microbial electrolysis, bio-augmentation, and multiple process integration, are also considered for industrial-level applications. Biohydrogen generation might be further enhanced by optimization of operating conditions and adding vital nutrients and nanoparticles. Cost reduction and durability enhancement are the most significant hindrances to fuel-cell commercialization. This review summarizes the biohydrogen production pathways, the impact of used organic waste sources, and bacteria. The work also addresses the essential factors, benefits, and challenges.

SanMove: next location recommendation via self-attention network

PurposeThis paper aims to address the following issues: (1) most existing methods are based on recurrent network, which is time-consuming to train long sequences due to not allowing for full parallelism; (2) personalized preference generally are not considered reasonably; (3) existing methods rarely systematically studied how to efficiently utilize various auxiliary information (e.g. user ID and time stamp) in trajectory data and the spatiotemporal relations among nonconsecutive locations.Design/methodology/approachThe authors propose a novel self-attention network–based model named SanMove to predict the next location via capturing the long- and short-term mobility patterns of users. Specifically, SanMove uses a self-attention module to capture each user's long-term preference, which can represent her personalized location preference. Meanwhile, the authors use a spatial-temporal guided noninvasive self-attention (STNOVA) module to exploit auxiliary information in the trajectory data to learn the user's short-term preference.FindingsThe authors evaluate SanMove on two real-world datasets. The experimental results demonstrate that SanMove is not only faster than the state-of-the-art recurrent neural network (RNN) based predict model but also outperforms the baselines for next location prediction.Originality/valueThe authors propose a self-attention-based sequential model named SanMove to predict the user's trajectory, which comprised long-term and short-term preference learning modules. SanMove allows full parallel processing of trajectories to improve processing efficiency. They propose an STNOVA module to capture the sequential transitions of current trajectories. Moreover, the self-attention module is used to process historical trajectory sequences in order to capture the personalized location preference of each user. The authors conduct extensive experiments on two check-in datasets. The experimental results demonstrate that the model has a fast training speed and excellent performance compared with the existing RNN-based methods for next location prediction.

COMBINED NANOCHEMOTHERAPY USING DOXORUBICIN AND CURCUMIN AS AN EXAMPLE

The aim of the work was to review literature data on combined nanochemotherapy using the example of two drugs ̶doxorubicin and curcumin. Special attention was paid to the use of substances with synergistic properties in one nanoparticle, capable to penetrate into living cell. The method of combined chemotherapy of nanopreparations improves processing efficiency. The technique of using nanocontainers with synergistic drugs in combination with ligands reduces the side effects of chemotherapy drugs. Results. Literature data indicate that the use of nanopreparations contributes the rapid creation and use of synergistic combinations that were purposefully delivered to target cells, reducing dosage due to precise targeting. A promising direction of nanomedicine is the creation of multifunctional nanomaterials based on several active drugs having synergistic properties, with the simultaneous use of their enhancers and the strategy of active targeting. These structures enabled targeted and controlled penetration of medicinal compounds into the localization of pathological processes, reducing drugs toxicity for normal cells. Conclusions. Combined chemotherapy using polymers and nanoparticles with ligands, in which synergistic drugs are included, ensures to reduce side effects and doses of chemotherapy drugs, and helps to overcome multiple drug resistance as well.

Leveraging Technology to Improve Business during and after the Pandemic

The entire world came to a halt in 2020 because of Covid 19 pandemic. Businesses were closed and people from all over the world were quarantined. Some businesses, however, were able to continue operations through an existing pickup online program. Businesses that closed or were fearful of reopening may find that shifting to online marketing is the best solution. Understanding the significance of transitioning businesses from a physical location to an online one is an important goal to strive for. There are numerous short- and long-term benefits to moving businesses online through. Businesses can improve process efficiency, performance, and productivity by leveraging technological tools such as project management software (PMS), customer relationship management (CRM), task management tools (TMT), email marketing, Salesforce, and others. This article investigated how small businesses in the United States (US) benefited from technological tools and added value through their performance during the pandemic. It also aimed to educate business owners who still do not believe that technology can be used to automate their operations for effective performance and long-term customer relationships. The article seeks to encourage small-business owners to use their talents, competencies, and technology tools for the betterment of their organizations.
 
 Keywords: Technological Tools, Business Processes, COVID-19 pandemic, E-commerce

Improving Process Efficiency in Iraqi universities: a proposed management information system

This research paper aims to investigate the current state of process efficiency in Iraqi universities and propose a management information system (MIS) to improve it. A literature review was conducted to identify the challenges faced by universities in Iraq, as well as the solutions proposed in the literature. The findings showed that the main challenges in Iraqi universities include a lack of automation, poor data management, and inadequate communication between departments. A comparison was also made between the challenges faced by Iraqi universities and those faced by universities worldwide. To address these challenges, a survey was conducted to gather data from university staff and students. The survey results were analyzed, and the findings were used to design a MIS based on Oracle Application Express (APEX). The proposed system includes a student records management system, a staff management system, and an automated workflow system to improve communication and collaboration between departments. The proposed system was also found to be in line with the regulations and policies of the Ministry of Higher Education in Iraq. The system architecture and database design were also discussed in detail. The results of this research indicate that implementing a MIS using Oracle APEX can significantly improve the process efficiency in Iraqi universities. This can lead to an increase in the quality of education and a reduction in the administrative burden on staff and students.

Improving Process Efficiency at Pediatric Hospital Emergency Department Using an Integrated Six-Sigma Simulation Methodology

Inadequate staffing and long waiting times in hospital emergency rooms are key concerns that can have a negative impact on patient safety and health, as well as the hospital’s overall performance. The purpose of this paper is to investigate the scope of combining the DMAIC (define, measure, analyze, improve, and control) methodology with discrete event simulation and to explore its successful deployment in the Jordanian healthcare sector. The study discussed in this paper is based on a case study conducted utilizing the DMAIC and simulation technique and its application in reducing waiting time and enhancing overall system efficiency in Jordan’s Princess Rahma hospital’s pediatric emergency department. The study shows improvements in the performance of the process and thus productivity in the emergency department through adapting the combined Six Sigma DES methodology. The cycle time of the process was reduced by 73% of the present value, while simultaneously enhancing the total performance of the emergency department by 83%.

Power Apps pada Sistem Pemodelan Pengambilan Obat di Klinik Melia PT. POMI, Paiton

Digitalization is one of the important keys in increasing productivity, namely by building digital technology that improves process efficiency, product and service quality, and optimizes resource allocation, so as to reduce processing time for faster, streamlined operations, and greater customer satisfaction. as good as Power Apps. Power Apps is a service for building and deploying custom business applications that connect to your data and work across the web and mobile - without the time and expense of specialized software development. Power Apps are a number of applications, services, and connectors, as well as a data platform, that provide a fast development environment for building custom applications for business needs. Using Power Apps, users can quickly create custom business applications that connect to data stored on the base data platform (Microsoft Dataverse) or across various online and on-premises data sources (such as SharePoint, Microsoft 365, Dynamics 365, SQL Server, and so on). The purpose of this study is to implement and analyze the use of Power Apps in modeling drug retrieval at the Melia Clinic PT POMI, Paiton with the aim of improving the quality of Melia clinic services through acceleration and ease of drug taking. The output of this research is an accredited national journal.

An on-machine measuring method for inner dimension based on incoherent information fusion generated by double synergetic lasers

Rapid and automatic measurement of inner dimensions has taken its place in the field of precision measurement. On-machine measurement has the significant advantage of integration of processing and measurement, which can greatly improve processing efficiency and reduce costs. However, the measuring accuracy of existing on-machine measuring methods is easily affected by the intrinsic accuracy of machining or auxiliary equipment. As a consequence, these measuring methods cannot meet the demands of precision measurement. In this paper, an on-machine measuring approach based on incoherent information fusion is proposed to measure inner dimensions by using double synergetic lasers (DSLs). DSLs and the spindle of machine tools are taken as the measuring source and rotary power source respectively. Once the spindle rotates continuously, then a set of incoherent information pairs (IIPs) acquired by DSLs represent the whole feature of measured inner section. The IIPs can be correlated and utilized on the principle of the invariance of measured section. In practical measurement, neither specific measuring position as geometric center nor auxiliary equipment as angle encoder is necessary, and the final measuring accuracy is independent of the influence of machine tools. Inner diameter and roundness measurements are taken as examples to showcase the effectiveness of the proposed approach.

AERF: Adaptive ensemble random fuzzy algorithm for anomaly detection in cloud computing

The abnormality of system behavior is inevitable in cloud computing because of its complexity and scale. How to perform anomaly detection on the system’s operating data to discover abnormal behavior has become a popular research field. However, anomaly detection is a challenging research problem because data in cloud computing scenarios is continuous, imbalanced, and cannot be acquired at once. In this work, an adaptive ensemble random fuzzy (AERF) algorithm is proposed for anomaly detection in cloud computing systems. The random fuzzy rule-based method in the AERF selects samples randomly to enhance the diversity of base classifiers for dealing with disturbances caused by abnormal sample distribution effectively. A dynamic weighting strategy is used for fuzzy classifier ensembles to improve processing efficiency and anomaly detection accuracy. Experimental results show that the AERF yields 10% higher AUC and G-mean than existing methods on SMD and EMOSCloud datasets and 20% higher AUC and G-mean on five benchmarking datasets. The AERF yields 20% higher F1 than existing methods on EMOSCloud dataset. For all datasets, the AERF yields 50% faster training time than other methods.

An E-Collaboration Application for Final-Year Project Management

The advent of digital technologies has contributed to collaboration in many areas of life, including academia. This paper examines student final year projects (FYPs) and proposes a collaborative system that provides tools in response to various needs such as communication, coordination, production, and resource sharing. The application is designed for multiple users: students, advisors, and administrative staff. It provides a personal workspace for each user. The novelty of the proposed system is that it covers all the collaborative aspects mentioned throughout the FYP process, including proposal processing, project assignment, project completion, and evaluation. The new system is based on the proposed layered collaborative architecture. The results indicate good scores in improving collaborative aspects, improved process efficiency, and that users are positively inclined to use the system as their FYP management system.