Planning For Critical Component Prevention Sheeter Machine Using Monte Carlo Simulation At PT. Perkebunan Nusantara III Kebun Rantau Prapat

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Planning for Critical Component Prevention Sheeter Machine using Monte Carlo Simulation at PT. Perkebunan Nusantara III Kebun Rantau Prapat

Introduction

In today's competitive business landscape, companies in various industries are constantly seeking ways to improve their operational efficiency and reduce costs. One such company is PT Perkebunan Nusantara III Kebun Rantau Prapat, a leading player in the plantation and industry sector, particularly in processing sheets or RSS (Ribbed Smoke Sheet). To maintain optimal production machine function, the company requires good maintenance of all the machines used. However, the company is currently implementing corrective maintenance, where machine maintenance is carried out after damage. This approach causes low engine reliability, where sudden damage cannot be avoided, which in turn causes high maintenance costs.

The Problem of Corrective Maintenance

Corrective maintenance is a common approach used by many companies, where machine maintenance is carried out after damage. However, this approach has several drawbacks. Firstly, it causes low engine reliability, where sudden damage cannot be avoided. Secondly, it leads to high maintenance costs, as the company has to spend more time and resources on repairing damaged machines. Finally, it can also lead to unplanned production time, which can have a negative impact on the company's overall productivity and profitability.

The Need for Preventive Maintenance

To overcome the problems associated with corrective maintenance, companies need to adopt a preventive maintenance approach. Preventive maintenance involves carrying out regular maintenance tasks to prevent machine damage and extend its lifespan. By planning the optimal prevention maintenance schedule, companies can reduce maintenance costs while increasing the reliability of machine components. One method used to determine this schedule is the Monte Carlo simulation, which is able to analyze various variables and uncertainty in the treatment system.

The Monte Carlo Simulation Method

The Monte Carlo simulation is a statistical method used to analyze complex systems and make predictions about their behavior. It involves generating random numbers and using them to simulate the behavior of the system. In the context of preventive maintenance, the Monte Carlo simulation can be used to determine the optimal maintenance schedule for critical components. By analyzing various variables and uncertainty in the treatment system, the simulation can provide a systematic approach to identifying and scheduling critical component maintenance.

Analysis of Critical Components

Based on Pareto 80/20 analysis conducted on the sheeter engine, it was found that the critical components that needed to be considered were the bearing 22208 C3, Rounded Gear, and Chain Clutch. For each of these critical components, the results of the analysis show an optimal prevention treatment schedule, which is every 24 days for the bearing 22208 C3, 31 days for rounded gear, and 41 days for clutch chain.

Results of the Study

The results of this study were very significant, showing that with the planning of prevention care, the maintenance cost rate could be reduced by 16.4%, equivalent to savings of Rp 181,592 per day. In addition, the reliability of critical components also increased, with the reliability level of bearing 22208 C3 to 74.17%, rounded gear to 64.76%, and clutch chain of 62.53%.

Analysis and Implications

Through the application of the Monte Carlo simulation, PT Perkebunan Nusantara III can plan machine maintenance more effectively. This method not only provides a systematic approach in identifying and scheduling critical component maintenance but also allows companies to make decisions based on accurate data. This is very important in the industry where the operational time of the machine and cost efficiency are the main factors of success.

Increasing Reliability and Productivity

Increasing the reliability of the machine not only reduces maintenance costs, but also increases overall productivity. With a more reliable machine, the company can avoid unplanned production time, thus maximizing output and profitability. On the other hand, preventive maintenance that is well scheduled can extend the life of the engine, which will provide a better long-term investment return.

Conclusion

Overall, the application of preventive care planning using Monte Carlo simulation at PT Perkebunan Nusantara III Kebun Rantau Prapat shows how modern technology can be applied in traditional industries to achieve higher operational efficiency. This is not only relevant for the company, but can also be a reference for other industries that face similar challenges in terms of machine maintenance and operational costs.

Recommendations

Based on the results of this study, the following recommendations can be made:

  1. Implement preventive maintenance: Companies should adopt a preventive maintenance approach to reduce maintenance costs and increase the reliability of machine components.
  2. Use Monte Carlo simulation: The Monte Carlo simulation can be used to determine the optimal maintenance schedule for critical components.
  3. Monitor and analyze machine performance: Companies should regularly monitor and analyze machine performance to identify areas for improvement.
  4. Invest in maintenance training: Companies should invest in maintenance training to ensure that maintenance personnel have the necessary skills and knowledge to perform maintenance tasks effectively.

Future Research Directions

Future research can focus on the following areas:

  1. Application of Monte Carlo simulation in other industries: The Monte Carlo simulation can be applied in other industries to determine the optimal maintenance schedule for critical components.
  2. Development of predictive maintenance models: Predictive maintenance models can be developed to predict machine failure and reduce maintenance costs.
  3. Investigation of the impact of maintenance on machine performance: The impact of maintenance on machine performance can be investigated to identify areas for improvement.

Limitations of the Study

This study has several limitations. Firstly, the study was conducted on a single company, and the results may not be generalizable to other companies. Secondly, the study only focused on the application of Monte Carlo simulation in preventive maintenance, and did not consider other factors that may affect machine performance. Finally, the study did not investigate the impact of maintenance on machine performance, which is an important area for future research.
Q&A: Planning for Critical Component Prevention Sheeter Machine using Monte Carlo Simulation at PT. Perkebunan Nusantara III Kebun Rantau Prapat

Q: What is the main problem faced by PT. Perkebunan Nusantara III Kebun Rantau Prapat in terms of machine maintenance?

A: The main problem faced by PT. Perkebunan Nusantara III Kebun Rantau Prapat is the implementation of corrective maintenance, where machine maintenance is carried out after damage. This approach causes low engine reliability, where sudden damage cannot be avoided, which in turn causes high maintenance costs.

Q: What is the benefit of adopting a preventive maintenance approach?

A: The benefit of adopting a preventive maintenance approach is that it can reduce maintenance costs while increasing the reliability of machine components. By planning the optimal prevention maintenance schedule, companies can avoid unplanned production time, thus maximizing output and profitability.

Q: How does the Monte Carlo simulation method work?

A: The Monte Carlo simulation method involves generating random numbers and using them to simulate the behavior of the system. In the context of preventive maintenance, the Monte Carlo simulation can be used to determine the optimal maintenance schedule for critical components by analyzing various variables and uncertainty in the treatment system.

Q: What are the critical components that need to be considered in the sheeter engine?

A: Based on Pareto 80/20 analysis conducted on the sheeter engine, it was found that the critical components that needed to be considered were the bearing 22208 C3, Rounded Gear, and Chain Clutch.

Q: What are the optimal prevention treatment schedules for the critical components?

A: The optimal prevention treatment schedules for the critical components are as follows:

  • Bearing 22208 C3: every 24 days
  • Rounded Gear: every 31 days
  • Chain Clutch: every 41 days

Q: What are the results of the study in terms of maintenance cost reduction and reliability increase?

A: The results of the study show that with the planning of prevention care, the maintenance cost rate could be reduced by 16.4%, equivalent to savings of Rp 181,592 per day. In addition, the reliability of critical components also increased, with the reliability level of bearing 22208 C3 to 74.17%, rounded gear to 64.76%, and clutch chain of 62.53%.

Q: What are the implications of the study for PT. Perkebunan Nusantara III Kebun Rantau Prapat?

A: The implications of the study for PT. Perkebunan Nusantara III Kebun Rantau Prapat are that the company can plan machine maintenance more effectively using the Monte Carlo simulation method. This can lead to increased productivity and profitability, as well as reduced maintenance costs.

Q: What are the recommendations for other companies that face similar challenges in terms of machine maintenance and operational costs?

A: The recommendations for other companies that face similar challenges in terms of machine maintenance and operational costs are:

  1. Implement preventive maintenance: Companies should adopt a preventive maintenance approach to reduce maintenance costs and increase the reliability of machine components.
  2. Use Monte Carlo simulation: The Monte Carlo simulation can be used to determine the optimal maintenance schedule for critical components.
  3. Monitor and analyze machine performance: Companies should regularly monitor and analyze machine performance to identify areas for improvement.
  4. Invest in maintenance training: Companies should invest in maintenance training to ensure that maintenance personnel have the necessary skills and knowledge to perform maintenance tasks effectively.

Q: What are the future research directions for this study?

A: The future research directions for this study are:

  1. Application of Monte Carlo simulation in other industries: The Monte Carlo simulation can be applied in other industries to determine the optimal maintenance schedule for critical components.
  2. Development of predictive maintenance models: Predictive maintenance models can be developed to predict machine failure and reduce maintenance costs.
  3. Investigation of the impact of maintenance on machine performance: The impact of maintenance on machine performance can be investigated to identify areas for improvement.