Analytics for Supply Chain Optimisation

Supply Chain analytics has gained greater significance this decade aiding in efficiency and responsiveness of a supply chain leading to a competitive advantage in almost every industry. Small scale industries and organisations are either unaware or reluctant to apply analytics and digitise their supply chain for multiple reasons. This paper is an effort to demonstrate the effect of supply chain analytics on a company and its current constraints. A detailed description of diverse analytics to aid in the surge of productivity at XYZ plant is presented. An underlying objective of this research was to impact all three aspects – strategy, design and execution of the supply chain to boost profits and optimise the system in consideration.

A Diverse and Sustainable Biodiesel Supply Chain Optimisation Model Based on Properties Integration

Producing sustainable biodiesel from oil crops has been a great challenge, especially for oil crops plantations that involve various small and medium stakeholders. Differences in plantation activities and environments create a unique sustainability profile for each oil crop that may impose more sustainability issues such as deforestation problems in oil palm plantations. This paper embraced the unique sustainability index profile of each oil crop, and an investigation was performed to evaluate the feasibility of integrating multiple oil crops into the existing biodiesel refinery to improve its economic and sustainability performances. The selection of the process feed is proposed to be based on oil crop properties such as iodine value, peroxide value and saturated and unsaturated fatty acid contents. The sustainability profiles considered in the study include deforestation, oil yield, fertiliser impact, water impact and carbon footprint. Case studies demonstrated that a more balanced sustainability index profile could be achieved at a higher production cost—from USD 6.43 billion·y−1 in a cost-saving-centric solution to USD 39.90 billion·y−1 in a sustainability-improvement-centric solution. The study provided excellent insight into the impact on production cost to achieve sustainability which can help stakeholders to evaluate the feasibility of integrating multiple oil crops in the system.

A Biomass Supply Chain Optimization Framework With Linear Approximation of Biomass Yield Distributions for Improved Land Use

Biomass and the bio-economy have strong potential to help shift dependency away from petroleum. Supply chain optimisation (SCO) has been used to help other industries and can be used to boost biomass industry viability. Biomass supply chain models frequently average the biomass yield of large tracts of land in their calculations. However, there can be large variation in the biomass yield within those tracts, losing useful information. This work presents a biomass SCO framework which approximates the available quality of land by piecewise linearly approximation of the biomass yield distribution, and incorporates this information into the optimisation. The linear estimates of the biomass yield distributions allow the SCO model to make more informed decisions about quantity and location of biomass growth operations, affecting all downstream decisions. A case study of mainland Great Britain has been examined using the framework to illustrate the impact of retaining biomass yield information in the optimisation, versus averaging the yield across tracts of land. The case study found that using biomass yield linear estimates reduced the overall land usage by 10%. Further, it improved biomass output, which increased the quantity of bio-products produced. All of this led to an increase in the overall profit.