Research in Supply Chains of the Future
Supply chains of the future will have to deal with a host of new challenges facing us in the 21st century

These challenges include:

  • Exploiting new energy and material sources;
  • Cleaner exploitation of existing sources (e.g. high-carbon fossil fuels);
  • Resource efficiency to deal with increasing scarcity of non-fuel resources (e.g. water and minerals);
  • Decarbonised supply chains;
  • Customisation of products and services (e.g. healthcare) closer to the point of use.

An example of such emerging supply chains is the concept of the biorenewables supply.

Biorenewable supply chains

Forecasts of fossil fuels price increases have been leading to the search for substitute carbon-based materials for chemical processes. This has led to the concept of a biobased economy. This concept is focused on the development of industrial biorefineries, where biomass conversion processes which produce fuels, power, and chemicals are integrated to minimise the environmental impacts and maximise the value derived from the biomass feedstock.

The overall biomass value chain is strongly related to the feedstock pre-treatment unit, which consists of a set of preliminary processes to fractionate the biomass and accounts for a large share of the total capital investment. As an example, the organosolv process is currently one of the most promising pre-treatment processes. The technology aims at efficiently solubilising lignins and providing high quality cellulose fibres and hemicellulose from which a wide variety of products can be derived (e.g. polyolefins, polyurethanes, polyvinyl chloride, second generation biofuels, adhesives, resins and feed ingredients.

The main strength of this technological solution is the wide variety of lignocellulosic feedstock being used (e.g. cereal straws, deciduous forestry residues, short rotation coppice (SRC) wood).
However, the eventual bioproduct cost is determined not only by the performance of the conversion process, but also by the performance of the entire supply chain. In particular, a biorefinery requires a cost-effective biomass infrastructure where feedstock production, collection, storage and pre-processing are simultaneously optimised to guarantee a continuous all year round operation.

Process requirements are not only to be met in terms of biomass availability, but feedstock quality is to be guaranteed, too. Biomass transportation distance, storage needs and mass perishability reduction relies on optimal selection of densification technologies (e.g. chipping, pelletisation) and logistics infrastructure. In view of the above, quantitative design tools are useful to provide decision support assessing both financial and environmental performance of biorefineries in a holistic approach along the entire supply chain (SC) over the long-term.

This project, part of the BIOCORE programme (http://www. biocore-europe.org) aims at providing a Mixed Integer Linear Programming modelling framework to help define planning strategies for the development of sustainable biorefineries. The upscaling of an Organosolv Biorefinery is addressed via optimisation of the whole system economics. Three real world cases studies are proposed to show the high-level flexibility and wide applicability of the tool to model different biomass typologies (i.e. forest fellings, cereal residues and energy crops) and supply strategies. Model outcomes reveal how supply chain optimisation techniques could help shed light on the development of sustainable biorefineries. Feedstock quality, quantity, temporal and geographical availability are crucial to determine biorefinery location and the cost-efficient way to supply the feedstock to the plant. Storage costs are relevant for biorefineries based on cereal stubble, while wood supply chains present dominant pretreatment operations costs.

A French Case study

The optimal Organosolv biorefinery SC in the French region is mainly supplied with wheat straw while residues from barley harvesting are used at a lower extent. The energy crop share of feedstock supply (i.e. miscanthus) as well as biomass supply differentiation increase over time, to face the straw competitive use rise over time.

The pretreatment facility operates in cell 50, in the centre of an area devoted to the cultivation of the main crop (i.e. wheat straw). The land devoted to barley is located just around the area used for wheat crop, while miscanthus is grown in the same cell as the Organosolv pretreatment plant (Figure 1.a-1.c). The biorefinery location optimisation is driven by the quality of the infrastructure: the region selected is characterized by more dense truck transportation links, used to deliver about 90% of the feedstock. The seasonal supply chain of biomass is affected by the availability of feedstock over a year: i.e. cereal straw can be only harvested in summer, while miscanthus only in winter.

The fluctuating nature of the biomass availability results in a high reliance of the supply network on storage facilities which are mainly located on the field border (Figure 2).

If the biorefinery is sustained only through cereal crop residues (i.e. barley and wheat straw), the optimal biomass SC configuration is rather similar to the one in Instance A, having an Organosolv facility in cell 50 within a large area devoted to wheat straw, the leading crop with rather low seasonal effects (Figure 3).

The higher reliance of wheat straw in Instance B widens the biomass collection area, up to a maximum in of 0.41 Mha, increasing transportation and storage cost share of total costs. French case (Instance B): Seasonal biomass supply to the Organosolv facility.

 

 

Figure 2.
a) Wheat straw (top left) b) Miscanthus (top right)
c) Barley straw (bottom)

 

French case (Instance B): Seasonal biomass supply to the Organosolv facility.
Figure 3. French case: storage locations across the regions for a) wheat straw, b) miscanthus and c) barley straw. The circle size is scaled on the maximum storage capacity settled per each crops, across the region and over time). 

Figure (above).