OPTIMIZATION AND TECHNO ECONOMIC STUDY OF PLASTIC WASTE BENEFICIATION WITH PRODUCTION SIMULATION APPROACH CASE STUDY AT CV. PANDU KENCANA JOMBANG, EAST JAVA

Mahendra Rian Putra; Muslikhin Hidayat; Muhammad Arif Wibisono

doi:10.22146/ajse.v5i1.67366

OPTIMIZATION AND TECHNO ECONOMIC STUDY OF PLASTIC WASTE BENEFICIATION WITH PRODUCTION SIMULATION APPROACH CASE STUDY AT CV. PANDU KENCANA JOMBANG, EAST JAVA

https://doi.org/10.22146/ajse.v5i1.67366

Mahendra Rian Putra^(1*), Muslikhin Hidayat⁽²⁾, Muhammad Arif Wibisono⁽³⁾

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(*) Corresponding Author

Abstract

The problem of plastic waste is getting more and more worrying day by day. Meanwhile, the industrial demand for plastics is also increasing. So we need a recycling business that can bridge this. Plastic waste in the environment can be decomposed, and the industry fulfills plastic needs at low prices. This study aims to analyze and optimize the business of recycling plastic waste into plastic ore to reduce the amount of plastic waste in the environment and obtain material benefits. The research method used is a case study in a plastic waste processing company with the collection of data needed to determine the formulation of the problem so that a mathematical model of linear equations can be formed, which then, through production simulations, will be obtained optimization. The results are then analyzed with a techno-economic study to determine the feasibility of the business.

After optimization of production from simulations based on a mathematical model of linear equations, if the company wants to get maximum profit, then the company must produce PP Black A of 1022.73 kg, PP Black B of 852.27 kg, PP Gray of 625 kg. Meanwhile, PP Gray Jumbo should not be produced. Based on the techno-economic study, the feasibility analysis before optimization was obtained as ROIa=23.40%, ROIb=23.24%, POTa=2.99 years, POTb=3 years, BEP=36.07%, SDP=23.98% LANG=4.1, DCFRR=18.8 %. Then the feasibility analysis after optimization is ROIa=29.88%, ROIb=29.73%, POTa=2.5 years, POTb=2.51 years, BEP=31.03%, SDP=20.63%, LANG=4.1, DCFRR=24.85%.

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DOI: https://doi.org/10.22146/ajse.v5i1.67366