cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Taufik Hidayat
Contact Email
ijecsultan@gmail.com
Phone
-
Journal Mail Official
ijecsultan@gmail.com
Editorial Address
Jl. Nyi Ageng Serang, Kota Baru Keandra, Cirebon, Indonesia
Location
Kab. cirebon,
Jawa barat
INDONESIA
International Journal of Engineering Continuity
Published by Sultan Publisher
ISSN : -     EISSN : 29632390     DOI : https://doi.org/10.58291/ijec
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering
The International Journal of Engineering Continuity is peer-reviewed, open access, and published twice a year online with coverage covering engineering and technology. It aims to promote novelty and contribution followed by the theory and practice of technology and engineering. The expansion of these concerns includes solutions to specific challenges of developing countries and addresses science and technology problems from a multidisciplinary perspective. Published papers will continue to have a high standard of excellence. This is ensured by having every papers examined through strict procedures by members of the international editorial board. The aim is to establish that the submitted paper meets the requirements, especially in the context of proven application-based research work.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2023): ijec" : 5 Documents clear
Thermo Valve Air Compressor Maintenance and Repair Using the Overall Equipment Effectiveness (OEE) Method in Maintenance Amalia Ma'rifatul Maghfiroh; Alfian Bima Chandra
International Journal of Engineering Continuity Vol. 2 No. 1 (2023): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v2i1.59

Abstract

Production activities carried out every day can interfere with the effectiveness of the machine, one of which is the compressor, so that sometimes problems in the field are still often encountered, such as the piston drive motor not rotating, the compressor does not turn on and off automatically, corrosion (rust), melted capacitors, and many more. things that can happen beyond the operator's control. Due to these constraints, the authors decided to find out more and made direct observations at PT. INKA Multi Solusi Service, as well as studying good and proper machine maintenance so that the company's productivity does not experience a significant decrease. The research was conducted by direct observation and direct interviews with the maintenance department to find out the steps that are usually taken in solving problems. To determine the value of machine effectiveness based on the measurement of three main ratios, namely: availability, performance efficiency, and rate of quality, is carried out using the Overall Equipment Effectiveness (OEE) method. The conclusion that can be drawn from this study is that maintenance on the Ingersoll Rand MM160 type screw air compressor is carried out to maintain the condition of the compressor in a ready state for use in measuring the level of machine effectiveness using the Overall Equipment Effectiveness (OEE) method at PT. IMSS, starting from May – July 2022, where the highest percentage in May 2022 is 94% and the lowest in June 2022 with a percentage is 90%.
Mobile Robot Object Detection Method Based on Deep Learning Yuhan, Guo
International Journal of Engineering Continuity Vol. 2 No. 1 (2023): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v2i1.80

Abstract

The task of object detection is to accurately and efficiently identify and locate a large number of predefined categories of object instances from images. With the wide application of deep learning, the accuracy and efficiency of target detection have been greatly improved. However, deep learning-based target detection still faces challenges from key technologies such as improving and optimizing the performance of mainstream target detection algorithms, improving the detection accuracy of small target objects, realizing multi-class object detection and lightweight detection model. In response to the above challenges, based on extensive literature research, this paper analyses methods for lightweight detection models and improved detection accuracy from the perspective of YOLOv5s network structure. The problems to be solved in target detection and the future research direction are predicted and prospected.
Improved Ant Colony Algorithm for AGV Path Planning Jia-ning, LI
International Journal of Engineering Continuity Vol. 2 No. 1 (2023): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v2i1.82

Abstract

Given the shortcomings of the ant colony algorithm in the path planning process, such as low convergence speed and easiness of falling into local optimization, an improved ant colony algorithm (ACO) suitable for AGV path planning was proposed. The initial pheromone concentration was differentiated on the grid map according to the distance, which avoided the blind search in the early stage of the ant colony and sped up the convergence speed of the algorithm. The distance between the current grid and the grid to be selected and the distance between the grid to be selected, and the target grid were synthesized to improve the heuristic function to increase the direction of ant colony pathfinding. The dynamic heuristic factor was introduced to avoid the phenomenon of prematurity and falling into local optimization. It was proposed to label the direction of the adjacent grid of each grid, which increased the distance between the optimal path and obstacles, enhanced the security of the optimal path, avoided the occurrence of the dead corner phenomenon, and improved the robustness of the algorithm. The simulation results show that in the same environment, the improved algorithm's search efficiency and iterative stability are better than that of basic ACO algorithms in AGV path planning.
Path Planning of Mobile Robots Based on Improved Genetic Algoritm Zhang Ke-qi
International Journal of Engineering Continuity Vol. 2 No. 1 (2023): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v2i1.84

Abstract

With the development of intelligent manufacturing, whether from the consideration of capacity, efficiency, or convenience, the requirements for mobile robots are increasing, reasonable regional path planning is one of the most critical needs, and a genetic algorithm is the best way to solve this problem, but in some complex working environments, traditional genetic algorithms will cause some problems, such as the path is not smooth, the steering angle is too large, the number of turns is large, etc. In this paper, an improved genetic algorithm is utilized to optimize the path-planning problem of mobile robots to circumvent the common issues arising from other approaches. The Improved Genetic Algorithm (IGA) has emerged as a significant advancement in the field of optimization techniques. By incorporating adaptive features, this refined approach yields enhanced performance and accuracy when compared to traditional genetic algorithms. Building on the foundational principles of evolutionary computation, the IGA employs innovative strategies, such as adaptive crossover and mutation operators, to navigate complex solution spaces effectively. It can also reduce computation time and increase efficiency by considering various considerations, such as environmental constraints and avoiding obstacle.
The Development of a Matlab-Based Fuzzy PID Controller and The Simulation Yunus Bakhtiar Arafat; HU Weiwei
International Journal of Engineering Continuity Vol. 2 No. 1 (2023): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v2i1.85

Abstract

Fuzzy PID control is a process control technique combining the advantages of fuzzy logic and PID control. It maintains precise control over processes by combining fuzzy logic and proportional-integral-derivative (PID) controllers. With this method, it is possible to achieve higher levels of accuracy and stability in controlling process variables such as temperature, pressure, flow rate, and position. This makes Fuzzy PID control an ideal cordial application requiring precise process control. Fuzzy PID control uses the PID parameter tuning experience to make the fuzzy controller automatically tune its parameters, giving PID control a better control effect. In this paper, a fuzzy PID controller is designed to control the temperature of an electric boiler. The control effects of PID control, fuzzy control, and fuzzy PID control are compared by simulation analysis. The simulation results show that the unclear PID control effect is ideal and has a good application prospect.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol. 4 No. 2 (2025): ijec Vol. 4 No. 1 (2025): ijec Vol. 3 No. 2 (2024): ijec Vol. 3 No. 1 (2024): ijec Vol. 2 No. 2 (2023): ijec Vol. 2 No. 1 (2023): ijec Vol. 1 No. 2 (2022): ijec Vol. 1 No. 1 (2022): ijec