Proceedings of The Conference on Management and Engineering in Industry

Optimization Moisture Content Using Fuzzy Logic Based on Programmable Logic Controller (PLC) for Soap Drying Process

Achmad Fathoni — 2023-10-19

Traditional processes are still employed in the now-operational soap drying process factory. Temperature monitoring is done separately from other operations, and valve operation is done manually rather than connected to the primary controller. The operators are in charge of all monitoring and synchronization between temperature and valve opening action, which they do manually based on their knowledge. In order to offer good work that is both trustworthy and consistent, dependable process control is required. One method of process control is fuzzy logic control.

Design and Develop Automatic Light Vehicles (LV) Unit Number Identification by Image Recognition Using Computer Vision Artificial Intelligent

Yudhi Afandi — 2023-10-19

This thesis presents the development of an AI-driven system to automate refueling data recording, improving accuracy, efficiency, and cost-effectiveness. The research aims to identify the LV unit and driver's name, verify custodianship cost centers, and record refueling volumes. A comprehensive and accessible refueling database is established for immediate data availability. The study employs the V model for Mechatronics System Design, utilizing the Raspberry Pi 4 model B 8 GB, a 5-inch HDMI screen, and a webcam for capturing LV unit numbers and ID badges. The EAST algorithm locates text, while OCR Tesseract extracts information. The data is stored in a SQLite database using Python. Error rate and OCR accuracy are analyzed, and system duration time is compared with the existing system. Results show that computer vision and AI effectively identify LV unit numbers and driver's names at fuel stations. The proposed system offers cost-effective, accurate refueling data, including date, time, LV number, custodian cost center, and driver. Implementation streamlines operations and provides comprehensive data for decision-making.

Monitoring Engine Oil Pressure with IoT System in Multinational Heavy Equipment Company

Sygit Irawan — 2023-10-19

Komatsu Bulldozer D85ESS-2 is inseparable from problems, including the rising heat and pressure due to the reduced lubrication and increased friction. However, operators often ignore or miss this condition which may cause heavy damage to the equipment. The objective of this research is to develop a tool that can be installed on the bulldozer that can detect changes in engine oil pressure in the engine to prevent further damage by providing information through the operator dashboard with the IOT system. ESP32 will be used with the Google Sheets application as an IoT platform to be able to send information from sensors to Google Sheets and then the data is sent to the LookerStudio to display the data to prevent damage to engine components due to the absence of lubrication. The result of the implementation shows that the pressure, temperature, and RPM sensors respectively received 2%, 1%, and 1% mean absolute errors scores with high accuracies of 98%, 99%, and 99%. T-test analyses indicate statistically significant errors from mean values between the sensor readings and reference instruments: 0.05 bar for Pressure, 0.28°C for Temperature, and 6.41 rpm for RPM. Standard deviations for sensor readings are 0.32 bar, 3.03°C, and 198 rpm, while for reference instrument readings, they are 0.3 bar, 3.15°C, and 196 rpm.

Tilt Level Monitoring and Switch Information System for Heavy Equipment of BOMAG BW 211D-40SL Series

Rachmat Mulyana — 2023-10-19

Bomag BW 211D-40 SL is a long-term investment capital in the field of heavy equipment. This unit is used for soil compaction in the construction process or others. One of the main components in this unit is the final drive. In this section, it consists of a planetary gear arrangement. The final drive component is one of the components that often experience damage, one of the causes of the damage of this component is due to errors when operating on tilt conditions. This research uses experimental methods to design a tilt monitoring tool for the unit during operation that can send notifications in real-time (using the internet of things). The device uses an MPU 6050 sensor to detect the tilt of the unit and is combined with the GSM Module SIM800L as a data sender to the internet. The vehicle owner or foreman mechanic can monitor through Blynk. This notification is in the form of a condition of the unit’s slope that is working normally, warning with slope conditions above. This data will be used as a basis for assessing the work competence of correct or incorrect operators.

Optimizing Spare Parts by Using Criticality Level and Replenishment Policy in Oil and Gas Industry

Oma Budi Herawan — 2023-10-19

Spare part management is a crucial activity in many industries due to the high production loss during downtime caused by a shortage of spare parts. Conversely, a high stock level results in a high value of unproductive capital. In the oil and gas business, the choice of spare parts inventory is the most critical factor. Spare parts for oil drilling and production are costly and challenging to manage. In some companies, spare parts analysis only considers the maintenance point of view. This study was conducted to reduce spare parts inventory without compromising plant downtime caused by a shortage of spare parts. In this study, the criticality criteria include the maintenance (production loss impact and annual demand/turnover) and procurement (spare parts delivery time and quantity of vendor) point of view. The Analytic Hierarchy Process (AHP) will analyze the criticality level based on the above four criteria. Furthermore, the replenishment policy for each spare part is determined based on the results of the AHP simulation (criticality level). There is an opportunity to reduce the spare part inventory using the proposed criticality level. However, a new study should be performed, especially for project surplus material that cannot be utilized during regular operation (drilling casing and tubing).

IoT/GSM Monitoring and Pollutant Detection of Heavy Equipment Fuel System

Firman Raharjo — 2023-10-19

This thesis presents an automation system that can be used in the monitoring process of diesel fuel, especially fuel from the beginning of heavy equipment with a tiered transportation process. This may cause pollutants in fuels, especially biodiesel/biofuel because of their solvency and hydroscopic properties that make it easy to absorb water to form mud and gel. Fuel available in heavy equipment sometimes has many impurities due to its complex distribution. The study began by scanning the properties of fuel ranging from B0 to B30 compared to water with a moisture sensor scanner and measuring pollutants using TDS sensors on clean B0, clean B30, and clean B100 compared to dirty fuel taken from a real job site. Using Arduino Mega, SIM 800, Nextion LCD, Relay, power supply, and Buzzer, it can be used to create an automatic system that can activate pumps and valves automatically if there are pollutants and water can be monitored. Using Blynk IoT, fuel conditions can be monitored online. Furthermore, if water or pollutants are in the fuel, then the developed tool can suck up using a valve and proceed to the filtering process with a filter to hold the pollutant and return the fuel to the tank. If there is water detected from the sensor, the pump will suck water and then continue to be accommodated in the reservoir. By using IoT, every sensing activity in the fuel tank, whether there is water or a pollutant, can be monitored in real time using Blynk. For commercial implementation, a robust design with powerful sensors and actuators is needed in accordance with the operational conditions of the fuel tank.

Accuracy Optimization of Liquid Ink Automatic Filling Machine Using Fuzzy Control

Rian Wiranto — 2023-10-19

In ink manufacturing, the important last step of the production is the filling of the packaging. This filling process has to consider some factors such as accuracy, speed, compatibility with hazardous area and cleanliness, because this relates to productivity, product loss and safety. The manual process can't cover most of those situations. Implementation of an auto-filling machine as a form of transition from manual has to consider many factors because most ink industries use flammable materials, which the machine on there should compatible with hazardous areas. This research came out with a proposed model of a filling liquid machine by using a pneumatic system which compatible for hazardous area and applying fuzzy logic as the control. Evaluate and compare the fuzzy logic performance with On/Off and PID is done in research as well.

Design Improvements to reduce Chili Paste Production Time Using an Automatic Transfer System

Angga Widi Fitriyanto — 2023-10-19

In Indonesia, a well-known American food and beverage corporation is expanding. A new product will be introduced, and production will expand. The production process still employed a manual approach and reported takes time. According to the actual data, the manual technique takes 29 – 46 minutes, depending on the amount and condition of human resources. As a result, the manufacturing process requires an automation solution to boost capacity for newer and existing items. In today's industrial world, PLC and HMI controllers are widely used. Flowmeters will operate as sensors to speed up and control the automatic transfer process, while automatic valves and pumps with variable speed controllers (VSD) will act as actuators. This system's sensor and actuator can also be coupled with coarse and fine-dosing methods to ensure precise transfer. To reduce manual handling and thus increase transfer capacity, all transfers are integrated into sanitary pipelines. Testing was conducted and the new automatic transfer system can cut the production processing time by 8 – 25 minutes.

Optimize Nitric Acid Injection PID Control Loop in Ammonium Nitrate - Scrubber System to Reduce Environmental and Human Risk of NH3 and HNO3 Fume

Irsyad Razaqi — 2023-10-19

In Ammonium Nitrate (AN) production, controlling the pH value is one of the most important factors. In addition to posing a variety of environmental and human risks, uncontrolled pH levels during the production of AN can also contribute to a number of hazardous situations. The purpose of this research is to control the pH of Final Scrubber System in Ammonium Nitrate solutions using PID control in order to prevent environmental and human risk. In this research, several settings utilizing Ziegler Nichols, Cohen-Coon, and Auto-Tune with Siemens PCS 7 DCS are implemented. Researchers discovered that the Final Scrubber System pH Control introduced a lengthy dead time. Four out of six PID settings maintain the pH of the Final Scrubber System effectively. The system's final PID setting is derived from Cohen-Coon with PI only.

Implementation of Artificial Neural Networks for Analyzing the Influence of Force on Accuracy Projectiole Range of 76 mm Munion/TRK

Armando Hasudungan Hutagalung — 2023-10-19

This study explains how to determine the reach of a 76 mm ammunition projectile against the effect of the drag force received by a 76 mm cannon ammunition projectile when fired which is for accuracy in hitting targets. In carrying out the 76 mm cannon shooting at the target, it is always preceded by a reconnaissance shot. This shot aims to determine whether there is a deviation in direction and distance and target. This deviation always occurs at every firing of the 76 mm cannon even though it has used the firing data table from the cannon. This happens because there are several factors that affect the speed of the projectile while in the air, one of which is drag. The method used to analyze the effect of drag on the firing of a 76 mm cannon projectile is a forecasting method using an artificial neural network with a ballistic calculation approach.

Vacuum Distillation Turbine Lube Oil Purification System in Steam Power Generation Plants

Samuel Onasis Keliat — 2023-10-19

Steam power generation plants are equipped with turbine lubrication systems. Turbine lubrication systems are to lubricate tribological components to reduce friction and wear between rotating parts. Turbine lube oils are used as lubricants used to wet journal and thrust bearings of turbines and generators during in service. Quality of turbines lube oils are defined by chemical and physical properties, additives concentrations and contaminations level. Chemical and physical properties of turbine lube oils are to serve their function and performance. Contamination in turbine lube oils are particle or solid contaminants, moisture, and varnish. Varnish is oxidation products that are produced long run turbine operation. Oil cleanliness or particle contaminants distribution and moisture content in turbine lube oils are monitored before starting and during power plant operation. Oil cleanliness and moisture content are measured by International Standard Organization-ISO 4406 and % saturation. Particle contaminants and moisture content are increased during power plant operation. As a preventive maintenance strategy and power generation plant reliability, Particle contaminants and moisture levels are maintained low. Particle contaminants could be removed by filter units and the moisture could be removed from turbine lube oil by a vacuum distillation method. Vacuum distillation method is to separate moisture from turbine oil based on the differences in their boiling point performed under pressure. This paper is to study turbine lube oil purification system which it integrates oil filter integrated with Vacuum distillation.