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A stochastic optimisation model for biomass outsourcing in the cement manufacturing industry with production planning constraints

Abriyantoro, Dedi, Dong, Jingxin, Hicks, Christian, Singh, Surya P.
Energy 2019 v.169 pp. 515-526
Geographical Locations, biomass production, cement, consumers (people), cost effectiveness, data collection, energy, environmental sustainability, fossil fuels, handling machinery, manufacturing, models, planning, purchasing, trucks, uncertainty
It is estimated that 12–15% of total global industrial energy is consumed by the Cement Manufacturing Industry (CMI). To improve environmental sustainability, biomass has been used as an alternative to fossil fuels. There is a comprehensive literature on biomass production and conversion, but little attention has been paid to biomass logistics in the cement industry. We propose the use of cement distribution trucks to collect biomass on their return journeys. Compared with the use of specialist biomass suppliers, the collection of biomass via cement distribution networks has greater uncertainties in delivery times, volume and quality. This is because biomass collection is a secondary activity and is subject to cement order quantities and the random geographical locations of cement customers. To cope with these uncertainties, additional on-site storage and handling equipment is required. This paper proposes a stochastic programming model to measure the cost-effectiveness of collecting biomass using returning cement distribution trucks in comparison with purchasing biomass from specialised biomass suppliers. A numerical experiment based on a real-word dataset was conducted to verify the effectiveness of the developed model.