Lack of maintenance on machines and equipment

Oct 13, 2025 by miodeya.com 93 views

Analysis of Improvement of the Ingot G1 Aluminum Production Process Using Taguchi’s Loss Function and Fault Tree Analysis (FTA) at PT Inalum (Persero)

Introduction

The global demand for aluminum has been increasing significantly over the years, with production levels rising from 59,890,000 MT in 2016 to 65,296,000 MT in 2020. As a result, the aluminum industry is under pressure to produce high-quality products, including aluminum ingot G1 products produced by PT Inalum (Persero). However, the challenge faced by PT Inalum is a variation of aluminum levels from the established standards, which has the potential to cause significant quality losses. This study aims to identify quality losses and causes and provide suggestions for improving the aluminum ingot G1 production process using the taguchi loss function and analysis of error trees (FTA).

Background

Aluminum production is a complex process that involves several stages, including smelting, refining, and casting. The quality of the final product depends on various factors, including the quality of raw materials, equipment maintenance, and operator skills. In the case of PT Inalum, the company produces aluminum ingot G1 products that meet the Japanese Industrial Standards H2-102, which requires a minimum aluminum level of 99.70%. However, the company has been experiencing variations in aluminum levels, which has resulted in significant quality losses.

Methodology

This study used the taguchi loss function and analysis of error trees (FTA) to identify quality losses and causes. The taguchi loss function is a mathematical model that calculates the economic loss due to quality defects. The analysis of error trees (FTA) is a systematic approach that identifies the root causes of quality problems. The study used a control map to analyze the aluminum level data and calculate the process capability index (CP). The results of the analysis showed that the aluminum level was within control limits, but the CP value was low, indicating that the production process had not fully met the specified quality standards.

Results

The calculation results showed that the quality loss reached Rp277,915,546.80 per month. This loss was mainly caused by two main factors: the mass of aluminum from excess alumina and the addition of aluminum mass from the alloy metal. Through the analysis of the Error Tree (FTA), the root causes of the two factors were identified.

Root Causes of Excessive Aluminum Mass from Alumina

The root causes of excessive aluminum mass from alumina include:

Poor alumina quality: The quality of alumina is critical in determining the final product quality. Poor alumina quality can lead to variations in aluminum levels.
Lack of maintenance on machines and equipment: Regular maintenance is essential to ensure that equipment is functioning properly and efficiently.
Lack of operator experience: New operators may not have the necessary skills and experience to produce high-quality products.
Operator attitude that is not disciplined: Operators who are not disciplined may not follow standard operating procedures, leading to quality defects.

Root Causes of Addition of Aluminum Mass from Alloy Metal

The root causes of the addition of aluminum mass from alloy metal include:

Operators' disconnection: Operators who are disconnected from the production process may not be aware of the quality requirements.
Pressure caused by changes in temperature (thermal shock): Changes in temperature can affect the quality of the final product.
Increased volume of aluminum fluid (molten): An increase in the volume of aluminum fluid can lead to variations in aluminum levels.

Improvement Strategy

Based on the analysis, some actions are recommended to overcome each root cause. For aluminum mass problems from excess alumina, the steps that can be taken include:

Maintaining the condition of alumina with a density of 3.95 g/cm³: Regularly checking the density of alumina to ensure that it meets the required standards.
Carry out preventive maintenance regularly on machines and equipment: Regular maintenance is essential to ensure that equipment is functioning properly and efficiently.
Provide training to new operators with a focus on improving skills: New operators need to be trained to produce high-quality products.
Give strict sanctions on unprotected operators: Operators who do not follow standard operating procedures should be held accountable.

On the other hand, to deal with the addition of aluminum mass from the alloy metal, steps need to be applied such as:

Analyze and determine the standard time and workload of the operator: Operators need to be aware of the quality requirements and the standard time and workload.
Ensure the temperature of the machine and the equipment fixed at 960 ° C: Regularly checking the temperature of equipment to ensure that it meets the required standards.
Performing aluminum fluid (metal tapping) periodically at a volume of 11 m³: Regularly checking the volume of aluminum fluid to ensure that it meets the required standards.

Conclusion

This study aimed to identify quality losses and causes and provide suggestions for improving the aluminum ingot G1 production process using the taguchi loss function and analysis of error trees (FTA). The results showed that the quality loss reached Rp277,915,546.80 per month, mainly caused by two main factors: the mass of aluminum from excess alumina and the addition of aluminum mass from the alloy metal. Through the analysis of the Error Tree (FTA), the root causes of the two factors were identified. Based on the analysis, some actions are recommended to overcome each root cause. By implementing this improvement strategy, it is expected that PT Inalum (Persero) can improve the quality of aluminum ingot G1 products and minimize losses due to aluminum levels.
Frequently Asked Questions (FAQs) on Analysis of Improvement of the Ingot G1 Aluminum Production Process Using Taguchi’s Loss Function and Fault Tree Analysis (FTA) at PT Inalum (Persero)

Q: What is the purpose of this study? A: The purpose of this study is to identify quality losses and causes and provide suggestions for improving the aluminum ingot G1 production process using the taguchi loss function and analysis of error trees (FTA) at PT Inalum (Persero).

Q: What are the main factors that cause quality losses in the aluminum ingot G1 production process? A: The main factors that cause quality losses in the aluminum ingot G1 production process are the mass of aluminum from excess alumina and the addition of aluminum mass from the alloy metal.

Q: What is the root cause of excessive aluminum mass from alumina? A: The root causes of excessive aluminum mass from alumina include poor alumina quality, lack of maintenance on machines and equipment, lack of operator experience, and operator attitude that is not disciplined.

Q: What is the root cause of the addition of aluminum mass from alloy metal? A: The root causes of the addition of aluminum mass from alloy metal include operators' disconnection, pressure caused by changes in temperature (thermal shock), and increased volume of aluminum fluid (molten).

Q: What are the recommended actions to overcome each root cause of excessive aluminum mass from alumina? A: The recommended actions to overcome each root cause of excessive aluminum mass from alumina include maintaining the condition of alumina with a density of 3.95 g/cm³, carrying out preventive maintenance regularly on machines and equipment, providing training to new operators with a focus on improving skills, and giving strict sanctions on unprotected operators.

Q: What are the recommended actions to overcome each root cause of the addition of aluminum mass from alloy metal? A: The recommended actions to overcome each root cause of the addition of aluminum mass from alloy metal include analyzing and determining the standard time and workload of the operator, ensuring the temperature of the machine and the equipment fixed at 960 ° C, and performing aluminum fluid (metal tapping) periodically at a volume of 11 m³.

Q: What is the expected outcome of implementing this improvement strategy? A: The expected outcome of implementing this improvement strategy is to improve the quality of aluminum ingot G1 products and minimize losses due to aluminum levels.

Q: How can the taguchi loss function and analysis of error trees (FTA) be used in other industries? A: The taguchi loss function and analysis of error trees (FTA) can be used in other industries to identify quality losses and causes and provide suggestions for improving the production process.

Q: What are the benefits of using the taguchi loss function and analysis of error trees (FTA) in quality improvement? A: The benefits of using the taguchi loss function and analysis of error trees (FTA) in quality improvement include identifying quality losses and causes, providing suggestions for improving the production process, and improving product quality and reducing losses.

Q: How can the results of this study be applied in real-world scenarios? A: The results of this study can be applied in real-world scenarios by identifying quality losses and causes, providing suggestions for improving the production process, and implementing improvement strategies to improve product quality and reduce losses.

Q: What are the limitations of this study? A: The limitations of this study include the use of a single case study, the limited scope of the study, and the potential for bias in the data collection and analysis.

Q: What are the future research directions for this study? A: The future research directions for this study include conducting a larger-scale study, exploring the use of other quality improvement tools, and investigating the application of the taguchi loss function and analysis of error trees (FTA) in other industries.