Journal of Advanced Research Design

Comparative analysis of Machine Learning Models for Predicting Particle Size Parameters from Drilling Data

Md. Aumio Tajrian — Wed, 03 Sep 2025 00:00:00 +0700

The efficiency of drilling operations is determined by numerous aspects, including the particle size of the material being drilled. To achieve efficiency, drilling engineers must take into consideration the size, shape, and density of the cuttings generated during the drilling process. Ineffective drilling can result in increasing expenses and delays for projects involving the extraction of natural resources. The objective of this study is to enhance drilling efficiency by investigating the correlation between drilling parameters such as weight on bit, revolutions per minute, torque, and rate of penetration and features of particle size distribution such as mean particle size and coarseness index as well as mechanical specific energy (MSE). The influence of particle size on drilling has been evaluated through the application of machine learning techniques and comprehensive datasets. The study highlighted relationships between particle size characteristics and the effectiveness of drilling, offering valuable insights into the optimal particle size for tonalite formations that are bordered by mica gneiss. Three machine learning techniques were employed to determine the closest relationship between drilling characteristics and particle size, with the Random Forest approach exhibiting the strongest correlation. This technique may be employed to forecast the size attributes of particles for data points that are not available within the usual range of drilling parameters. This work successfully emphasizes the significance of particle size in drilling operations and showcases the practical use of machine learning in enhanced drilling efficiency.

Aesthetic Experience of Local Cultural Tourism Meron to Encourages Creativity Among Early Childhood in Indonesia

Nur Fajrie — Wed, 03 Sep 2025 00:00:00 +0700

This study explores the integration of local cultural elements and environmental materials (loose parts) in fostering aesthetic development in early childhood education. The research aims to analyze aesthetic experiences of early childhood in Sukolilo related to the Meron cultural tradition, assess how culture-based learning enhances these experiences, and identify supporting factors. Using a mixed-methods approach, the study includes Playgroup students aged 4-5 years from Sukolilo, with data collected through surveys, interviews, observations, and document analysis. Results indicate moderate aesthetic experiences, with children successfully recreating Meron shapes, highlighting the effectiveness of integrating culture and loose parts in promoting creativity.

Representative Volume Element in Photopolymerization Additive Manufacturing Techniques for Mold Production: A Comprehensive Structured Review

Syah Mohd Amin Omar — Wed, 03 Sep 2025 00:00:00 +0700

In recent years, the use of Representative Volume Elements (RVE) in photopolymerization additive manufacturing (AM) for mold production has attracted significant attention for its potential to enhance material performance and structural reliability. This systematic literature review (SLR) provides a structured analysis of recent developments in RVE applications within photopolymerization techniques. It focuses on their effectiveness in addressing the challenges of dimensional precision, mechanical strength, and thermal stability in AM molds. The review addresses the need for a consolidated understanding of RVE’s role in optimizing photopolymerization processes to achieve superior mold quality for industrial applications. A comprehensive search was performed following the PRISMA guidelines across established databases, for instance, Scopus as well as Web of Science (WoS), emphasizing research published from the year 2022 to 2024. A total of 26 relevant articles were analyzed, categorizing findings into three key themes: (1) hybrid and multi-material manufacturing techniques, (2) material-specific AM and characterization, and (3) applications and performance enhancements in AM. Results indicate that RVE integration in photopolymerization AM techniques can improve mold properties by up to 30%, with advancements in fiber orientation and controlled curing processes contributing significantly to performance. This review highlights RVE’s critical role in advancing photopolymerization AM for mold production and suggests further research into standardized RVE methodologies for scalable and high-performance mold applications. The findings offer valuable insights for industries seeking reliable and efficient manufacturing solutions through AM innovations.

Assessing Ergonomic Risks in Laser Cutting Sheet Metal Operations Using REBA Method: A Case Study

Muhammad Izzuan Abd Rahman, Shahrul Azmir Osman, Saliza Azlina Osman — Tue, 02 Sep 2025 00:00:00 +0700

The laser cutting of sheet metal, which requires human participation, frequently introduces ergonomic challenges that can negatively impact both worker health and manufacturing productivity. Thus, conducting ergonomic assessments is crucial to identifying and addressing risks associated with workplace design and practices, particularly those related to lifting sheet metal and the potential for musculoskeletal disorders (MSDs). This study uses the Rapid Entire Body Assessment (REBA) method and the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) to investigate ergonomic risk assessment in laser cutting operations. Data were collected from participants familiar with the tasks through questionnaires and observations, focusing on lower and upper back disorders. The REBA analysis revealed that lifting sheet metal is linked to poor posture and a high risk of lower and upper back disorders, highlighting the need for improvements. Concurrently, CMDQ results highlighted issues related to lower back discomfort and upper back and forearm discomfort, which can detrimentally affect process efficiency. Integrating ergonomic principles into the design process can enhance worker safety and health, increasing productivity and fostering a more sustainable work environment that benefits both employees and the organization.

Architecting Robust Connectivity: Unveiling The Blueprint for A Resilient Telecommunication Network Design

Sabiroh Md Sabri, Haryani Haron, Mohd Idhamm Ibrahim, Saleh A. Alkhabra — Tue, 02 Sep 2025 00:00:00 +0700

The telecommunication industry has seen rapid growth over the years. This phenomenon is a result of changes in people’s lifestyle, an increase in governmental defence needs as well as in the banking sector and transport control. To ensure all aspects from business to people’s lives run smoothly without any disruptions, the communication network must stay efficient at all times. Network designers are continuously faced with the challenge of keeping a communication network running smoothly. The diffusive nature of design knowledge, such that it is scattered among organizations and individual designers because of project-specific variances, makes the task at hand difficult. This distribution creates knowledge silos that pose barriers to access and reuse, therefore the repeated initiation of projects and escalation of costs. These concerns are captured by this study’s ambition to systematize and document the knowledge regarding network design in a systematic, easily accessible format, increasing reusability and reducing project duration. The research follows a qualitative approach and focuses on the processes and activities involved in network design. Data gathering included interviews and observations that were interpreted through thematic analysis. The research identifies three knowledge types: definitions of “telecommunication network resilient”, “resilient network design knowledge” and “resilient network design process knowledge”. This study concludes with a proposed process model for developing a resilient telecommunication network and advice to future users.

Trend In Publication in Chemical Engineering in Indonesia: A Bibliometric Analysis Perspective Relating to Particle Technology

Asep Bayu Dani Nandiyanto, Dwi Novia Al Husaeni — Tue, 02 Sep 2025 00:00:00 +0700

This research analyzed publication trends in the field of Chemical Engineering in Indonesia from a bibliometric perspective. Using data from the Scopus database, this research explored various aspects such as the number of publications, annual distribution, most popular topics, most productive authors, as well as document types and publication sources. The analysis results showed fluctuations in the number of publications over the last five years, with the highest peak in 2020 with a total of 18 documents. Journal articles were the type of document and source most often chosen by researchers. In addition, international collaboration was confirmed to be very important because it increased the chances of producing articles that were highly cited by other researchers. Therefore, chemical engineering was a topic of great interest to researchers in Indonesia. It is hoped that the findings from this study can contribute to the development of research strategies and academic policies in the field of Chemical Engineering in Indonesia, especially relating to particle technology.

Tin/Indium Electrodes for Liquid Ethanol Sensing at Various Concentrations

Tue, 02 Sep 2025 00:00:00 +0700

Ethanol is widely used in medical, industrial and environmental sectors, prompting a growing demand for accurate and real-time detection technologies. However, conventional tin (Sn)-based ethanol sensors face major limitations, including low selectivity, poor stability and delayed response times, especially at higher ethanol concentrations. To address these challenges, this study aims to enhance the sensing performance of Sn electrodes by modifying them with indium (In) through an electrodeposition method at three concentrations: 0.01 M, 0.03 M and 0.05 M. The fabricated Sn/In electrodes were characterized and evaluated using chronoamperometry under different ethanol concentrations (25%, 50% and 95% v/v). Results revealed that the 0.05 M In-modified electrode achieved the highest current response (~0.75 mA) and response ratio (~600 Rt/Ro) at 95% ethanol. In comparison, the 0.03 M In electrode exhibited superior sensitivity at lower concentrations. All electrodes demonstrated rapid response times within two minutes of exposure. These findings suggest that indium-modified Sn electrodes are highly promising for liquid-phase ethanol sensing applications, offering enhanced sensitivity and tunability based on dopant concentration.