Four Scenarios Optimizing Production

Oct 13, 2025 by pinkandtrash.com 86 views

Introduction

PT. Agrosari Sentraprima, a leading processing company of various types of concentrates and fruit puree, faces significant challenges in maintaining the stability of Puree Mangosteen production. The company's daily demand reaches 8-10 tons of mangosteen fruit, which is supplied from Aceh and Padang. However, the availability of fluctuating mangosteen fruit in North Sumatra is the main obstacle in achieving production targets. This research aims to address this problem by designing a dynamic system simulation model to determine the optimal daily production of Puree Manggis, in accordance with the availability of raw materials in North Sumatra.

Background

The production of Puree Mangosteen at PT. Agrosari Sentraprima is a complex process that involves various factors, including the availability of raw materials, labor, and production capacity. The company's daily demand for mangosteen fruit is high, and the supply from Aceh and Padang is not always consistent. This has resulted in production targets not being met, leading to losses and decreased competitiveness in the market. To address this issue, a dynamic system simulation model was designed to optimize the production of Puree Mangosteen.

Methodology

The design of the dynamic system simulation model began with building a conceptual model, namely *rich picture *and *causal loop diagram *, which is then simulated using anylogic software. The model was verified to ensure accuracy and free from errors. Model validation was also carried out using * mape test * with 4.94% results, showing a good compatibility between the simulation model and real data. Furthermore, the experimental simulation was carried out with four scenarios for the next five years.

Four Scenarios Optimizing Production

The four scenarios designed for the simulation model are:

Scenario I: The company only takes raw materials from North Sumatra.
Scenario II: The company takes raw materials from North Sumatra with additional labor.
Scenario III: The company takes raw materials from North Sumatra with the addition of production machine units.
Scenario IV: The combination of scenarios I, II, and III.

Simulation Results

The simulation results show that Scenario II is the best choice with the optimal total daily production of Puree Manggis:

Year 1: 5,0433 tons/day
Year 2: 4,6330 tons/day
Year 3: 5,9898 tons/day
Year 4: 4,8757 tons/day
Year 5: 12,6774 tons/day

Analysis and Implications

The Dynamic System Simulation Model provides a comprehensive solution to optimize the production of Puree Mangosteen at PT. Agrosari Sentraprima. The simulation results show that the addition of labor is the most effective strategy in increasing production capacity. This is caused by several factors, such as:

Increasing efficiency: Additional labor can help speed up the production process and minimize stop time. Flexibility: With a greater number of workers, companies can adjust production needs in accordance with the availability of raw materials. Risk Reduction: Dependence on one source of raw materials can be reduced by utilizing local workers.

Recommendation

Based on the simulation results and analysis, the following recommendations are made:

Scenario II implementation gradually with strict monitoring and evaluation.
Diversification of raw material sources by considering the potential of other regions such as Aceh and Padang.
Development of an integrated information system to monitor raw material stocks and optimize procurement.

Conclusion

With the application of the right strategy and the use of simulation technology, PT. Agrosari Sentraprima can reach the optimal mangosteen puree production target and increase competitiveness in the market. The dynamic system simulation model designed in this research provides a comprehensive solution to optimize the production of Puree Mangosteen, and its implementation can lead to significant improvements in the company's production capacity and competitiveness.

Future Research Directions

Future research directions include:

Further validation of the simulation model using real-world data.
Development of a more detailed and realistic simulation model.
Implementation of the simulation model in other companies to optimize their production processes.

Limitations of the Study

The study has several limitations, including:

Limited data availability: The study was limited by the availability of data, which may not be representative of the entire industry.
Simplification of the simulation model: The simulation model was simplified to make it easier to understand and analyze, which may not reflect the complexity of the real-world production process.
Assumptions made: Several assumptions were made in the study, which may not be accurate in reality.

Conclusion

In conclusion, the dynamic system simulation model designed in this research provides a comprehensive solution to optimize the production of Puree Mangosteen at PT. Agrosari Sentraprima. The simulation results show that the addition of labor is the most effective strategy in increasing production capacity. The implementation of the simulation model can lead to significant improvements in the company's production capacity and competitiveness.

Q: What is the main challenge faced by PT. Agrosari Sentraprima in maintaining the stability of Puree Mangosteen production?

A: The main challenge faced by PT. Agrosari Sentraprima is the availability of fluctuating mangosteen fruit in North Sumatra, which is the main obstacle in achieving production targets.

Q: What is the purpose of the dynamic system simulation model designed in this research?

A: The purpose of the dynamic system simulation model is to determine the optimal daily production of Puree Manggis, in accordance with the availability of raw materials in North Sumatra.

Q: What are the four scenarios designed for the simulation model?

A: The four scenarios designed for the simulation model are:

Scenario I: The company only takes raw materials from North Sumatra.
Scenario II: The company takes raw materials from North Sumatra with additional labor.
Scenario III: The company takes raw materials from North Sumatra with the addition of production machine units.
Scenario IV: The combination of scenarios I, II, and III.

Q: Which scenario is the best choice according to the simulation results?

A: Scenario II is the best choice with the optimal total daily production of Puree Manggis.

Q: What are the factors that contribute to the effectiveness of Scenario II?

A: The factors that contribute to the effectiveness of Scenario II are:

Q: What are the recommendations made based on the simulation results and analysis?

A: The recommendations made are:

Scenario II implementation gradually with strict monitoring and evaluation.
Diversification of raw material sources by considering the potential of other regions such as Aceh and Padang.
Development of an integrated information system to monitor raw material stocks and optimize procurement.

Q: What are the future research directions?

A: The future research directions include:

Further validation of the simulation model using real-world data.
Development of a more detailed and realistic simulation model.
Implementation of the simulation model in other companies to optimize their production processes.

Q: What are the limitations of the study?

A: The limitations of the study include:

Limited data availability: The study was limited by the availability of data, which may not be representative of the entire industry.
Simplification of the simulation model: The simulation model was simplified to make it easier to understand and analyze, which may not reflect the complexity of the real-world production process.
Assumptions made: Several assumptions were made in the study, which may not be accurate in reality.

Q: What is the conclusion of the study?

A: The dynamic system simulation model designed in this research provides a comprehensive solution to optimize the production of Puree Mangosteen at PT. Agrosari Sentraprima. The simulation results show that the addition of labor is the most effective strategy in increasing production capacity. The implementation of the simulation model can lead to significant improvements in the company's production capacity and competitiveness.