• International Journal of Technology (IJTech)
  • Vol 12, No 1 (2021)

Risk Control Failure of Iron Pipes in Finished Goods Warehouses using Dynamic Systems

Risk Control Failure of Iron Pipes in Finished Goods Warehouses using Dynamic Systems

Title: Risk Control Failure of Iron Pipes in Finished Goods Warehouses using Dynamic Systems
Arief Suwandi, Teuku Yuri Zagloel, Akhmad Hidayatno

Corresponding email:


Cite this article as:
Suwandi, A., Zagloel, T.Y., Hidayatno, A. 2021. Risk Control Failure of Iron Pipes in Finished Goods Warehouses using Dynamic Systems. International Journal of Technology. Volume 12(1), pp. 15-21

110
Downloads
Arief Suwandi Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Teuku Yuri Zagloel Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Akhmad Hidayatno Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Email to Corresponding Author

Abstract
Risk Control Failure of Iron Pipes in Finished Goods Warehouses using Dynamic Systems










The condition of risk control failure causes many consumer complaints because many defective products are found with purchase orders for iron pipes. Storage management is very important for companies in maintaining quality and delivery accuracy for customer satisfaction. At this stage, there is a definite risk of failure from finished product control, such as material handling errors and product damage due to storage. The purpose of this research is to develop a failure risk control model in the finished goods inventory system. Iron Pipe defects are caused by poor material handling and product storage in the company. Exogenous variables from this simulation are the reliability of product handling, percentage of successful rework, and percentage of deteriorated product. The simulation results show that the optimistic scenario has the smallest defect of 0% and is followed by a most likely scenario of 1% and a pessimistic scenario of 4%. The resulting model can minimize the risk of failure of iron pipe products in finished goods warehouses, and the model can be applied in more complex real-world cases.

Deteriorated percentage of success rework; Optimistic scenario; Product handling; Warehouse

Introduction

The rapid development of science and technology requires every company to have good product quality to compete with their business competition. A quality product is something that can meet consumer expectations. Companies that produce iron pipes use steel plate raw materials which are generally used for construction, such as Pipes, Casing and Tubing, Subsea Pipes, Steel Water Pipes, Steel Pipes for Piles, and Steel Pipes for general structures. The risk control failure condition resulted in many complaints from consumers because defective products were often found in pipe purchase orders. This is a serious problem for the management of the pipeline company, and they need to immediately take corrective action to overcome the problem of defective products being manufactured (Suwandi et al., 2020).

The risk of failure to store finished products determines how the company proceeds in maintaining product quality and company sustainability. If the defect to a product is high, the company will experience losses and a lack of customer trust, resulting in serious disruption to the company (Suwartha et al., 2015).  The risk of failure needs to be identified and  then  a  model  developed  to  reduce  the  failure  to  store  the  finished  product (Kilibarda, 2013). Factors causing failure in storage include oxidation, aging, mildew, sealing failure and other slow chemical or physical processes (Liu and Liu, 2018).

The selection of the most suitable selective inspection, partial flow control, and defect correction policy is based on an analysis of the impact of actions on the overall system and the quality performance of the entire process chain, so that quality and productivity can be maintained at the system level (Grösser, Reyes-Lecuona, & Granholm, 2017).

This study aims to design a model to control the risk of failure of iron pipe products in the finished product warehouse by using a dynamic system that can help reduce the number of damaged products produced by the company.

This study focuses on the manufacture of metal pipes, where product damage occurs due to poor storage and material mishandling.

Conclusion

The dynamic system model developed describes the risk conditions of the failure of the production process. The model designed validated the actual results, which did not differ significantly from the simulation results. The risk of failure in the warehouse of finished products is based on the field and historical data, which are used to make the following models: the optimistic model, which is obtained from the minimum defect; the most likely model, which is obtained from the average defect; and the pessimistic model, which is obtained from the maximum defect. Each process in the warehouse is based on monthly historical data and then represented as a quantified dynamic system.

Several policy scenarios related to the risk of failure of the production process are tested to obtain a percentage of product defects each month. Exogenous variables from this simulation are the reliability of the product handling, the percentage of successful rework, and the percentage of products that deteriorate.

The simulation results show that the optimistic scenario has the smallest product defects of 0%, and that the most likely condition is 1%, while the pessimistic one is 4%. The optimistic situation has a difference of 115 tons from the actual condition, so the company can make savings of IDR 1,995,000,000 per month.

   The largest benefit comes from an optimistic scenario with IDR 226,480,000,000/month; the most likely scenarios give a benefit of IDR 224,632,000,000/month; and, finally, the pessimistic scenario gives one of IDR 217,413,000,000/month.

Supplementary Material
FilenameDescription
R1-IE-4068-20200819220955.docx Figure & Table
References

Grösser, S.N., Reyes-Lecuona, A., Granholm, G., 2017. Dynamics of Long-Life Assets: From Technology Adaptation to Upgrading the Business Model. Switzerland: Springer

Hidayatno, A., Rahman, R., Muliadi, R., 2015. Policy Analysis of the Jakarta Carbon Mitigation Plan using System Dynamics to Support Decision Making in Urban Development – Options for Policymakers. International Journal of Technology, Volume 6(5), pp. 886–893

Kilibarda, M., 2013. Logistics Failures in Distribution Process. Logistics International ConferenceVolume 114(1), pp. 247–252

Liu, C., Xie, Z., Sun, F., Chen, L., 2015. System Dynamics Analysis on Characteristics of Iron-Flow in Sintering Process. Applied Thermal Engineering, Volume 82, pp. 206–211

Liu, Z., Liu, X., 2018. Storage Reliability Assessment for the Stored Equipment Under Periodical Inspection. Advances in Mechanical Engineering, Volume 10(6), pp. 1–7

Moeis, A.O., Desriani, F., Destyanto, A.R., Zagloel, T.Y., Hidayatno, A., Sutrisno, A., 2020. Sustainability Assessment of the Tanjung Priok Port Cluster. International Journal of Technology, Volume 11(2), pp. 353–363

Poles, R., 2013. System Dynamics Modelling of a Production and Inventory System for Remanufacturing to Evaluate System Improvement Strategies. International Journal of Production Economics, Volume 144(1), pp. 189–199

Qiao-Lun, G., Tie-Gang, G., 2011. System Dynamics Analysis of RFID-EPC’s Impact on Reverse Supply Chain. In: International Conference on Management Science and Engineering - Annual Conference Proceedings, Rome, Italy

Sterman, J.D., 2000. Systems Thinking and Modeling for a Complex WorldManagement. Volume 6(1), pp. 7–17

Suwandi, A., Zagloel, T.Y., Hidayatno, A., 2018. Conceptual Model of Failure Risk Control on Raw Materials Inventory System. In: IOP Conference Series: Materials Science and Engineering, Jakarta, Indonesia

Suwandi, A., Zagloel, T.Y., Hidayatno, A., 2020. Minimization of Pipe Production Defects using the FMEA method and Dynamic System. International Journal of Engineering Research and Technology , Volume 13(5), pp. 953–961

Suwartha, N., Berawi, M.A., Zagloel, T.Y.M., Surjandari, I., 2015. Enhancing the Quality of Products and Projects through Better Designs and Modeling. International Journal of Technology, Volume 6(5), pp.  718–721