Supply chain pinch analysis to optimal planning of biogas production

Abstract

Supply chain is essential for an organization as it helps to maximize the operations which are profitable through the production, capacity, subcontracting, inventory and stock outs optimum levels. The traditional supply chain involves high documentation cost, with data involved that are mostly inaccurate and useless. In supply chain, the system of production plays an important role. The pinch analysis concept is initially used in the approach of energy conservation, and has extended to the optimization of resources and process integration. This paper presents the application of supply chain using pinch and cascade analysis for biogas production from palm oil mill effluent (POME). Biogas falls under the renewable energy where it can be produced via anaerobic digestion of POME. POME contributes to huge environmental impact mainly due to its high organic content. Supply chain via pinch analysis is used targeting to eliminate or reduce the difficulties faced in conventional supply chain. In this biogas supply chain analysis, it aims to meet the demand in a specific time frame. Minimum production rates are determined as accordance to the demand of electricity from 2020 to 2050. The pinch points are the points where the supply and demand are at the minimum, which the optimum production rate of electricity is able to determine from supply chain via pinch analysis. Monte Carlo Simulation tool is involved in the later stage of the study. It is used in the findings of analysing the increment of more than 10% of up-scale and down-scale production demand for each year for 35 years. The simulation is done from 2016 to 2035 of every five years interval. At the end of the study, the optimization of biogas production was achieved with the application of supply chain via pinch analysis. The supply and demand of biogas to electricity projection from 2020 to 2050 is forecasted. The optimal planning of electricity production from biogas was indicated in the supply chain cascade analysis.