Operation Process Research Articles (Page 1)

This study aims to describe and analyze the communication strategy of the General Affairs (GA) Division of PT The UNV Serang in managing work relationships with outsourced workers from PT Tri Karya Cemerlang (TKC). Using a qualitative approach and in-depth interview methods, this study found that the GA Division implemented a structured and effective communication strategy, reflecting a deep understanding of Communication Strategy Theory, Organizational Communication, and Communication Management. The strategy involved thorough planning, flexible implementation, and continuous evaluation. The GA Division used various communication channels such as WhatsApp groups, weekly face-to-face meetings, and the use of visual media (photos/videos) to ensure clear and directed communication. This multi-channel approach facilitated timely and accurate information flow between departments and outsourced workers. Additionally, the GA Division positioned itself as a "communication bridge," centralizing coordination for all departments and ensuring smooth operational processes. The communication pattern employed was an effective combination of formal, hierarchical communication and informal, personal communication. This combination served to strengthen relationships, foster mutual understanding, and promote a collaborative work environment. The study highlights the importance of a strategic and adaptable communication framework that ensures seamless coordination, promotes positive work relationships, and contributes to organizational success. This research can serve as a reference for improving communication strategies in similar organizational settings.

The oil layers in the Dongying Formation offshore oilfield are severely contaminated. The near-wellbore reservoir pore throats are blocked, which seriously affects the development effect. It has become urgent to implement acidizing stimulation measures. However, the target reservoir is deeply buried, has high reservoir pressure, and is highly sensitive. These factors result in high pressure during acidizing operations, a long single-trip time for raising and lowering the tubing string, and high costs. Moreover, acid that is not promptly returned to the surface after acidizing can cause secondary pollution to the reservoir. This work proposes an integrated tubing string to perform reverse displacement and reverse squeeze. With this, acid can be injected into the formation through the annulus between the casing and tubing. The residual acid and its post-acidizing derivative residues are rapidly lifted to the surface by the reciprocating suction action of the return pump. Based on this, the structure and specifications of the acidizing-flowback tubing string are designed through the flow rate analysis method. The tubing string is mainly affected by mechanical effects, including buoyancy, piston effect, flow viscosity effect, helical bending effect, temperature difference effect, and expansion effect. The maximum deformations are 1.4 m, 1.9 m, 0.18 m, 2.7 m, 1.8 m, and 2.5 m, respectively. The total deformation is less than 3 m. Simulation results from three groups of oil wells at different depths indicate that the axial force of the tubing string ranges from 400 to 600 kN. The stress ranges from 260 to 350 MPa, deformation is 1.1–2.4 mm, and the safety factor exceeds 3.0. This can effectively ensure the safety of on-site operations. Based on the actual field conditions, the acidizing-flowback tubing string is evaluated. This verifies the effectiveness of the acidizing-flowback tubing string. This research provides an economical and efficient operation process for acidizing operations in the Dongying Formation offshore oilfield. It achieves the goal of removing reservoir contamination and provides guidance for the unblocking and stimulation of low-permeability and sensitive reservoirs in the middle and deep layers of offshore oilfields.

Aim. The work aimed to develop a target model of a mature marketplace capable of functioning as the core of a digital ecosystem. Objectives. The work seeks to characterize the current state of marketplaces; identify areas for their transformation; highlight key elements of operational and infrastructural maturity; and propose a structural model reflecting the relationship between the brand, infrastructure, and management frameworks. Methods. The study employed systemic and structural-functional analysis, a comparative analysis of theoretical sources on platform economics, and conceptual modeling which can be used to construct a three-tier marketplace architecture and characterize the mechanisms of value creation in the ecosystem. Results. The paper presents the author’s acceptation of a marketplace as an evolving multi-sided platform that forms an ecosystem based on a three-tier architecture. It also defines the roles of brand and users in creating trust and network effects, and demonstrates the importance of financial, logistics, and IT infrastructures in ensuring the scalability and reliability of services. A closed-loop value creation mechanism is presented, combining internal departments, infrastructure, and users into a single manageable loop. Conclusions. A mature marketplace forms a sustainable digital ecosystem where the audience growth and product range increase are based on reproducible operational processes and shared data. The proposed model can be used for strategic planning, maturity assessment, and management decision-making in the field of digital platforms.

Simultaneous optimization of measurement system and operational process: an additive manufacturing application

The study aimed to understand the role of agile leadership in enhancing the effectiveness of digital transformation and its impact on improving performance and increasing efficiency in higher education institutions in Palestine. This was achieved by presenting theoretical frameworks for the role of agile leadership in digital transformation at universities. This was achieved by developing Palestinian universities to keep pace with digital transformation by applying the dimensions of agile leadership. This was achieved by providing a digital information network that supports digital transformation and is connected to global networks. This network provides university employees with the mechanisms and culture of e-management, as well as psychological, behavioral, technical, and material readiness, among other requirements for adapting to e-management. The study hypotheses included the existence of a relationship between agile leadership management and improving performance and increasing the effectiveness of digital transformation at universities. It also emphasized the existence of specific agile leadership methods that lead to improved both job performance and development effectiveness. The study used a descriptive and analytical approach to develop and monitor theoretical frameworks based on previous scientific studies and a scientific approach to analyze the research problem. The study concluded that agile leadership at universities focuses on preparing human resources to implement digital transformation, providing qualified personnel capable of using and analyzing data to make effective decisions, and being able to select human competencies and scientific expertise. It bears the burdens and efforts of data management and monitoring, as well as providing appropriate tools for statistical analysis and future forecasting, and reconciling internal resistance from employees and conflicting opinions. Flexibility and calm agile leadership helps establish an effective framework that ensures optimal implementation of digital transformation. This includes internal and external alignment in operational processes, and improves and develops the professional performance of faculty members through the provision of information. The use of self-critical thinking skills in analyzing problems and issues has a positive impact on improving performance. The study recommended the need to save time and accelerate the learning process to reduce the burden on faculty in traditional education for exams, marking, and results so that they are completed electronically. The quality of education should be improved by enhancing the quality of curricula and educational programs, and equal educational opportunities for all students to participate in the learning process, discuss, dialogue, and freely express their opinions on educational topics. Bridging the digital gap between urban and rural cultures among staff, and providing adequate professional training on the use of digital education tools and artificial intelligence in Palestinian universities.

The perfect combination of internet technology and the cultural and creative industry has created a new trend in the pop culture economy. Beijing Pop Mart Cultural and Creative Co., Ltd. (hereinafter referred to as Pop Mart) as a typical enterprise of IP + e-commerce has rapidly expanded. Its unique business model has created huge value while also facing financial risks such as fluctuations in IP value, high inventory, rapid market expansion, and a single profit model. This paper takes Pop Mart as the research object and employs case analysis method, financial ratio analysis method. Based on the financial data of the past 3 to 5 years, it systematically identifies the three major types of main financial risks, namely, its business operations, investment and financing, and capital flow. It also analyzed the management issues and causes of its main risks during the operation process. And based on the comprehensive risk perspective and financial early warning theory, it proposed countermeasures such as improving inventory levels, enriching IP operations, and dynamically constructing financial early warning models. The aim of this paper is to provide decision support for Pop Mart to avoid financial risks and offer references for the future better development of cultural and creative enterprises.

The mining industry consumes about 1.7% of the energy generated worldwide, which is expected to increase in the coming decades. Milling is the most energy-intensive process of a typical mining operation. Many variables (e.g., rock characteristics, mineral matrix, and equipment properties) affect energy consumption. This paper proposes that Random Forests and the Generalised Linear Model (GLM) be used to predict the energy consumption of the SAG mill, which significantly contributes to the energy consumption of mining operations. To show the performance of the proposed approach, a case study was applied to a copper mine dataset from South America. The proposed approaches were applied to forecast the SAG mill energy consumption. The outcomes demonstrated that these methods could be used to predict energy consumption. Random Forest can have a high prediction accuracy of 95% but lacks explanatory ability, as shown in R2 at 50%. GLM provided additional insights by showing the feature importances and their relationships with SAG mill energy consumption, along with considering the potential uncertainties and generating posterior probability distributions for the model outcomes. Both models identified key variables as significant predictors identically, with the GLM offering a more comprehensive view of best-case and worst-case energy consumption scenarios.

The development of digital technologies can significantly contribute to improving building management and maintenance processes, bringing revolutionary changes in the field of facility management. The digitization of recorded data allows for more efficient management of operational and maintenance processes throughout the entire life cycle of a building, which leads to cost reduction, optimization of workflows and extension of the service life of technical equipment. A key tool in this transformation is the concept of a digital twin, which allows the creation of accurate virtual models of buildings not only for new projects, but also for existing buildings. These digital models provide comprehensive information about building elements, technical equipment and operational parameters, which supports more effective decision - making in the field of management and maintenance. However, with the development of digitalization, there is also a need to identify and address potential risks associated with the implementation of these technologies. The main challenges include cybersecurity, personal data protection, system interoperability and the need to standardize digital solutions. For the successful implementation of a digital twin, not only technological security is essential, but also legislative and organizational readiness of entities managing buildings. Digitalization in building management and maintenance thus represents a significant step towards smarter, more efficient and more sustainable real estate management, while its full potential can be utilized through properly designed strategies and technological solutions.

The handover of patients arriving by ambulance at emergency departments (EDs) represents a time-critical event. Having a well understood assessment method supported by responsive operational processes, can improve outcomes for patients and regional safety.

This study investigates the constraints faced by Micro, Small, and Medium Enterprises (MSMEs) in accessing and utilizing financial assistance across Punjab, Haryana, Himachal Pradesh, and Chandigarh. Utilizing a primary data-based approach and a structured Likert-scale ‎questionnaire, the research employed Exploratory Factor Analysis (EFA) to uncover the underlying dimensions of these constraints. Pre-‎estimation tests confirmed the suitability of the data, and EFA revealed two distinct factors: Procedural and Operational Barriers, and Financial Systemic and Institutional Constraints. The findings indicate that MSMEs struggle not only with complex documentation and collateral ‎requirements but also with limited awareness, digital inaccessibility, and trust deficits in formal financial institutions. These constraints are ‎compounded by regional and demographic disparities, requiring differentiated policy responses. The study concludes that addressing ‎MSME challenges demands an integrated reform framework combining simplified operational processes with system-level institutional ‎transformation. The results contribute meaningfully to policy discourse on inclusive financial access and MSME development in regional ‎economies‎.

The thermal coal supply chain serves as core infrastructure for ensuring the safe and stable supply of electricity in China. Effective risk management and control of this supply chain are therefore critical to national energy security and socio-economic development. However, the thermal coal supply chain involves multiple complex risk dimensions, including cross-regional multi-entity coordination, a complex network structure, and a dynamic policy environment. Traditional risk analysis methods often fall short in depicting the concurrent events and dynamic propagation characteristics inherent to such a system. This necessitates systematically investigating the thermal coal supply chain within the Coal–Electricity Joint Venture (CEJV) operational framework, which primarily involves equity-based consolidation and long-term contractual coordination between coal producers and power generators, to comprehensively analyze its critical risk factors and transmission mechanisms. Initially, based on the integration of coal-fired power joint operation policy evolution and industry characteristics, 28 risk factors were identified across three dimensions: internal enterprise, external environment, and overall structure. These encompassed production fluctuation risks, thermal coal transport process risks, and insufficient supply chain flexibility. A dynamic behavior model for the thermal coal supply chain was constructed by analyzing the causal relationships among these risk factors, based on the operational processes of each link. Utilizing Petri net simulation technology enables a quantitative analysis of supply chain risks, facilitating the identification of bottleneck links and potential risk points. Through model simulation, 18 key risk factors were determined, providing a theoretical basis for optimizing supply chain resilience within CEJV enterprises. The limitations of traditional methods in dynamic process modeling and industrial applicability were addressed through a Petri net-based methodology, thereby establishing a novel analytical paradigm for risk management in complex energy supply chains.

Poor operational agility has been recognised as a factor affecting employees' performance. Adequate technological infrastructures, innovative capabilities, and digital transformation systems are reported to enhance workers' performance. This study examined the influence of operational agility on employees’ performance. A descriptive survey was used. The population was 435 staff of Tuyil Pharmaceutical, Ilorin. The sample was 208 employees, calculated using Taro Yamane's formula for sample size determination. A structured "Operational Agility and Employee Performance Questionnaire (OAEPQ)” was used for data collection. The reliability of the adopted questionnaire was assessed at Cronbach’s Alpha (α) with a reliability score of 0.86. Data analysis was conducted using frequency and percentage to present the answer to the research question. Regression Analysis was used to test the research Hypothesis at a 0.05 significance level. Findings showed that adaptation to technological infrastructures. Innovative capabilities and deployment of product delivery systems exert little influence on employee performance. Adopting modern IT applications for dynamic business operation processes increased employee activity efficiency. Digital transformation of systems improved employees’ efficiency, showing a greater influence on employees’ performance. Based on the findings, the study concluded that digital transformation and adopting modern IT applications for dynamic business operation processes strongly influence employees’ performance. The study recommends that employers ensure more adaptation to technological infrastructures, enhance the innovative capabilities of employees and implement massive deployment of product delivery systems to customers.

Artificial intelligence (AI) has emerged as a transformative force across various sectors, providing innovative solutions and enhancing operational processes. In the e-commerce domain, AI has significantly contributed to customer-centric approaches and strategic decision-making, fostering superior customer experiences. This study investigates the role and impact of AI in the Saudi e-commerce sector, focusing on the perspectives of female customers and retailers. Grounded in sociotechnical theory, the research employs a mixed-methods approach, combining quantitative surveys and semi-structured interviews. The quantitative findings demonstrate that AI-enabled e-commerce positively influences customer experience, customer satisfaction, and operational efficiency. Key AI capabilities, such as task automation, personalized recommendations, and predictive analytics, enhance online retail systems’ performance. The qualitative analysis highlights both the opportunities and challenges associated with AI adoption, emphasizing the need for specialized infrastructure and skilled professionals. Participants recommend addressing the skill gap and adopting phased implementation strategies to optimize AI integration. This study provides actionable insights and strategic recommendations for policymakers and stakeholders in the Saudi e-commerce sector.

The development of a web-based management system that integrates descriptive analytics and scheduling algorithms helps overcome the limitations of manual processes such as inefficiency, data inaccuracy, and lack of real-time updates. Through automation and data analysis, the system enhances productivity, minimizes human error, and enables informed decision-making. By centralizing operations, it ensures improved accuracy, accessibility, and overall business performance. The combination of descriptive analytics and scheduling algorithms strengthens operational efficiency and organizational intelligence. Descriptive analytics reveals patterns and performance insights, while scheduling algorithms automate and optimize resource allocation in real time. Together, they create an adaptive, intelligent, and reliable management solution that continuously improves business operations. SJOE Pet Supply, established in 2018, struggles with managing appointments, inventory, and customer records due to its manual system. To address these challenges, the proposed PetStreet system aims to automate core business processes and enhance operational efficiency. It incorporates descriptive analytics for data-driven insights and a scheduling algorithm to optimize appointments and staff workload management. Applied Developmental Research, focusing on designing and implementing a Web-Based Management System for SJOE Pet Supply, evaluated through the ISO/IEC 25010 software quality model. The evaluation centered on Functionality, Reliability, Efficiency, Usability, and Security to ensure the system performs accurately, operates smoothly, and safeguards sensitive business data. Data collection was conducted before and after system development, using interviews, surveys, and a Likert-scale questionnaire based on ISO 25010 criteria to measure user satisfaction and system performance. The Agile Methodology served as the development framework, emphasizing iterative development, continuous testing, and feedback integration to rapidly adapt to changes and refine features. Each phase aligned with ISO 25010 standards, ensuring that the system was functional, reliable, efficient, user-friendly, and secure to meet the operational needs of SJOE Pet Supply. PetStreet is a web-based management system developed for SJOE Pet Supply to automate grooming appointments, manage client and pet records, and control inventory efficiently. Based on the ISO/IEC 25010 evaluation, both users and technical experts strongly agreed that the system is highly functional, reliable, efficient, user-friendly, and secure. The study successfully developed and evaluated the PetStreet system, meeting all ISO/IEC 25010 quality standards. It proved to be an effective, secure, and user-centered solution for improving operational processes in the pet care industry. Future enhancements for PetStreet include developing a mobile version, strengthening security features, and enabling offline functionality. It is also recommended to integrate advanced analytics, payment options, and scalability features to support business growth and wider adoption.

Suppression of the temperature fluctuation using metal foam insert in the pressure vessel during the transient operation process

In the era of globalization and technology today, computer technology has become one of the most essential technologies in every aspect of human life. Mitra Sejahtera is one of the companies operating in the field of land sales in Pontianak. In the process of recording sales, it is still manually, which means transactions are recorded in a book as a record of sales or transactions. The transaction receipts that are issued are still manually, which causes issues during operations. A common issue is when sales are made, buyers experience long waits as the cashier records the sales, leading to a buildup of customers waiting during the transaction process, whether paid in cash or make a installments. The same thing happens in the company's accounting records, where errors often occur due to discrepancies between the accounting records and the transactions carried out. In system development using the waterfall method, object-oriented system analysis is conducted with UML modeling. Website development utilizes programming languages HTML, CSS, and PHP, along with a MySQL database. The result is that the point of sale information system with integrated accounting recording is designed to address the time required for transaction recording, namely by using a sales receipt printing system and directly scanning the accounting recording process. This aims to expedite the company's operational processes and reduce the likelihood of errors in transaction recording

This study’s object is the process of managing (balancing) the load on the computing nodes in a server cluster of information systems. The task addressed is to enable optimal (even) distribution of server resources within a cluster system. A simulation model of the process that distributes the load on computing nodes of a server cluster has been built, based on an improved model of the optimal use of server resources in a cluster based on Nash equilibrium and an improved method of adaptive load balancing in cluster systems according to Nash equilibrium. The simulation model has been constructed on the basis of fuzzy logic theory to determine the feasibility of decomposing tasks into subtasks, as well as game theory, in particular Nash equilibrium, to determine the optimal distribution of tasks/subtasks across cluster system servers for their parallel processing. The model built makes it possible to improve the efficiency (uniformity) of server resource distribution by an average of 13% compared to the classical load management method based on Nash equilibrium, by 61% with the Round Robin method, and by 63% with the Least Connection method throughout the entire process of cluster operation. This, in turn, allows for a more than 2-fold increase in the number of processed tasks from client requests compared to the above load balancing methods. In addition, the impact of the load balancing process on the processing time of tasks/subtasks by the cluster system servers was estimated. Based on the results of simulation modeling, it can be concluded that the application of the devised model does not exceed the total allowable processing time (no more than 315 ms) of tasks/subtasks from client requests compared to existing load balancing methods

Equipment failure caused by corrosion remains a critical challenge in ensuring the reliability and refinery asset integrity in the oil and gas industry. This study aims to develop a Corrosion Assessment Information System (CAIS), designed to assess and visualize corrosion severity through a color-coded Process Flow Diagram (PFD). The CAIS methodology consists of four key stages: analysis of design and operational data, process simulation and validation, compilation of contaminant data for each Crude Distillation Unit (CDU), and identification of corrosion mechanisms according to API 581 and API 571 standards. The system produces a corrosion risk map with four color indicators i.e. green (low), blue (moderate), yellow (high), and red (very high) which assists in prioritizing inspection and maintenance activities based on corrosion severity. Implementation results demonstrate that CAIS improves analytical efficiency, data accessibility, and collaboration between engineering and maintenance teams. Furthermore, it supports predictive monitoring and enables faster decision-making to reduce corrosion-related failures. External validation and integration into refinery workflows confirm CAIS as a strategic digital solution that strengthens risk-based inspection and predictive maintenance practices. Overall, CAIS provides a reliable platform for enhancing digital corrosion monitoring and asset integrity management at PT Kilang Pertamina Internasional, Refinery Unit VI Balongan, Indonesia.

This study aims to analyse the benefits of implementing the Lean Manufacturing concept in improving the performance and competitiveness of the manufacturing industry, as well as to propose strategies for its effective implementation. The research method used is a qualitative literature review, by collecting, analysing, and synthesising findings from 20 journal articles published between 2020 and 2025 that discuss Lean Manufacturing practices in various industrial sectors. The research results show that the application of Lean Manufacturing provides significant benefits, including reducing waste (muda), increasing production efficiency, improving product quality, and enhancing customer satisfaction. In addition, the integration of Lean principles with digital technologies in the Industry 4.0 era—known as Lean 4.0—has been shown to increase operational flexibility, process automation, and real-time decision-making capabilities. However, several challenges such as limited lean culture, lack of management commitment, and employee resistance remain obstacles to sustainable implementation. The conclusion of this study states that Lean Manufacturing is an effective strategic approach for improving industrial performance and competitiveness when supported by strong organizational commitment and continuous improvement culture.

Supervisory Control and Data Acquisition (SCADA) Systems are critical for industrial infrastructures, especially to ensure the ability to seamlessly monitor and control assets remotely. However, the significant threats of cybersecurity breaches and operational faults stand in the way of complete reliance on SCADA systems. This review paper investigates the recent advancements in artificial intelligence (AI) and its ability to serve as an effective tool to detect anomalies which traditional rule-based systems often miss. AI-Driven anomaly detection is examined from two perspectives: operational anomalies-including process deviations, abnormal readings and equipment malfunctions-and cybersecurity anomalies such as intrusions and network attacks. Various modern AI methodologies are evaluated, alongside potential challenges like real-time processing demands and explainability.