ModelEnterprise

Environmental optimization for the Green Supply Chain

In ModelEnterprise you can associate "emissions burdens" with all processes and take these into account during optimisation.

Conventional view of the supply chain – click to enlarge

Conventional view of the supply chain: direct material inputs and outputs (click to enlarge)

Lifecycle view of the supply chain – click to enlarge

Lifecycle view: inputs and outputs have associated burdens

Fig. 1 – Conventional and lifecycle views of the supply chain

Trade-off curve between costs and emissions for H2 production – click to enlarge

Fig. 2 – Trade-off curve between costs and emissions for H₂ production

The green supply chain is a concept that has risen to prominence in recent years.

Essentially it involves designing and operating supply chains that minimise environmental impact – for example, by avoiding suppliers whose products and services consume most natural resources or pollute the environment.

How does it differ from the conventional supply chain?

Under the green supply chain concept, the creation of undesirable materials such as Nitrous oxides (NO_x) or CO₂ is treated as a task in the resource-task network (RTN) in the same way as any other task. The main difference is that these "products" are created at many steps within the supply chain or production process.

Where their economic impact can be quantified – for example, where the costs of any cleanup process are known, or where there is a market in trading carbon credits – the figures are included as they are in any conventional "production step".

In cases where the economics cannot easily be quantified, the production of pollutants can be penalised in order to make polluting routes unnattractive.

How does ModelEnterprise handle the Green Supply Chain?

In ModelEnterprise you can associate "emissions burdens" with all processes by including output resources for tasks that capture the amount of each type of emission produced. For example any combustion process associated with power generation can have "output resources" such as CO₂ and NO_x.

However, this "factory boundary" view can lead to the wrong outcome when trying to minimise emissions. For example wastewater emissions can be reduced at the expense of more grid electricity – hence shifting the burden to a remote power plant.

For this reason, the resources entering the process are also be associated with emissions burdens – how much CO₂, NO_x etc. was required to make a unit quantity of each resource entering the process?

The subsequent an emissions minimisation will then optimise across the entire lifecycle, i.e. within and outside the factory gate.

Example

For example, consider a hydrogen production process (Fig 1).

The "conventional" RTN model includes only the direct material inputs such as CH₄. The "lifecycle view" on the other hand includes additional tasks – those used to generate the inputs and which have associated emissions burdens (often known as "inventories").

For example all processes required to produce, purify and transport the CH₄ to the factory gate are accounted for and the unit amount of CO₂ calculated. This allows the "well-to-wheel" optimisation of alternative hydrogen supply chains.

By exploring the trade-off curve between costs and emissions, alternative hydrogen roadmaps can be compared with the Pareto optimal solution family (Fig 2.)