A novel hybrid method for constructing resilient microalgae supply chain: Integration of n-1 contingency analysis with stochastic modelling
Shirleen Lee Yuen Lo, Bing Shen How, Sin Yong Teng, Juin Yau Lim, Adrian Chun Minh Loy, Hon Loong Lam, Jaka Sunarso
Abstract
Microalgae biomass is currently gaining the limelight due to its flexible characteristics such as easily adaptable in cultivation environment, high lipid content that makes it suitable for biofuel processing. However, one of the main challenges faced is the resiliency of the microalgae supply chain network (MSCN) when facing external factors that can lead to supply and demand disruptions. In this study, the integration of n-1 contingency analysis with Monte Carlo simulation model was proposed to conduct resilient supply chain planning when there is supply and demand disruption (i.e., the developed supply chain is robust to fulfil all the demand even when any of the processing hubs is malfunctioning). The n-1 contingency analysis was conducted via the P-graph model framework with the integration of sustainability index —economic and environmental. Subsequently, Monte Carlo simulation model was performed for the extracted distribution network to evaluate the financial probability profile of the optimized distribution network. The collaboration between separate processing hubs was proposed to assist in meeting demand when one of the processing hubs malfunctions with the consideration of lowest additional cost and carbon dioxide emission pathway. The results obtained highlighted that inter-plant collaboration is able to increase the mean Net Present Value (NPV) value by up to four times and percentage standard deviation was able to be reduced by up to 49% when inter-plant collaboration is being implemented. Thus, it can be said that the inter-plant collaboration can provide a solution when production plant malfunction and also increases the cash flow in.