Environmental Engineering Reference
In-Depth Information
chains caused by the application of innovation and the loss of resources through
waste and exhaust emissions. Further, the current scenario of resource utilization
creates a compilicated network among stakeholdes and is not conducive to the de-
velopment of innovative technologies.
Considering the above points, we propose a method for visualizing resource lo-
gistics such as where, how, and how much resources are utilized in each field; what
kind of changes are expected in the utilization of resources with the introduction of
new technology; and what are the ripple effects of technological innovation in the
supply of resources, which could face physical and economic barriers when used.
The study also aims to extract the number of stakeholders involved in logistics and
demonstrate the extent of their involvement.
Stakeholder dialogue is important for the introduction and implementation
of new technology and insufficient knowledge sharing among them can lead to
miscommunication. The visualization of resource logistics enables stakeholders
to share information and be aware of the knowledge gaps among themselves. By
clarifying resource logistics, it becomes possible to understand the flow of re-
sources such as metals and materials, and the products processed within the supply
chain. This also makes it possible to understand the efficiency of the system and to
identify ways of avoiding resource risk. This study attempts to identify the critical
nodes in the supply chain network, which will help in determining the areas that
need further research and should be the focus of development in relation to new
innovative technology, from the viewpoint of avoiding resource risk in the supply
chain.
9.2
Resource Logistics Analysis
9.2.1
Method
The main framework for resource logistics is based on the input-output (IO) model,
which follows the framework of the WIO-MFA model (Nakamura et al. 2007 ). In
this framework, the amount of input i necessary to produce a unit of output j ( i ,
j = 1,…, n ) is assumed to be a ij . A is assumed to be a matrix of size n × n (input coef-
ficient matrix), which treats the input as element i , j . The action of two matrices on
A yields à , which describes the actual output composition. The first matrix is a ma-
terial flow filter Φ, eliminating a substance flow that cannot be expressed in terms
of mass. This n × n matrix gives φ ij = 1, when the input makes up the output mass,
and φ ij = 0 in other cases. For instance, when the input does not have a mass, as in
the case of service businesses, or when the input has a mass but the output is limited
to supplemental purposes, the matrix gives φ ij = 0. The action of Φ on A enables a
description of the substance flow necessary for the materials flow analysis (MFA).
The second matrix is the yield coefficient matrix Г. All raw materials used as input
do not always form products in actual processes. Some of the materials are excluded
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