The integrated supply chain at Xerox Ltd is a large complex organisation which has many potential impacts on the environment. In order to better understand and reduce those impacts, an environmental bias has been introduced into the decision making process which allows more environmentally conscious decisions to be made. This paper details how the environmental bias was developed and how it can be used to provide both a measure of environmental performance for the whole supply chain, each functional element within the chain and for different product delivery scenarios. The environmental decision making tool construction is discussed and preliminary results show that it is the working life of a typical product which causes the biggest environmental impact.
Although there has been considerable effort placed on measuring supply chains in order to assess their performance, these techniques have been found to be time and cost focused, aimed at coping with rapid change. This approach tends to have a short‐term outlook. Work on greening supply chains is much longer‐term in outlook. Is information intensive and biased towards the supply side? These two mindsets appear to be diverging, developing in conflicting directions. This is an alarming prospect for the environment, which has no place in future supply chain performance measurements, thus running the risk of being increasingly side‐lined; and for performance measurements, which is unconcerned with longer‐term sustainability in terms of the environment. The case is made to amalgamate the advantages of both schools of thought to allow long‐term views to be represented by short‐term performance measurement.
The three-dimensional characterization and mapping of remote environments is an important task that generates a good deal of attention both by end users and by researchers across several elds of interest. In the mobile robotics community, a great deal of work has been done in equipping vehicles with sensors that can acquire three-dimensional and even multimodal information about the location and nature of features and objects in remote environments. However, the interpretation of such data using fully autonomous methods, such as computer vision, is usually a highly complex problem that, we believe, is much better suited to a humanoriented solution.In this paper, we describe our work in the development of augmented reality (AR) techniques for the telerobotic inspection and characterization of remote environments. We describe how we are using stereoscopic camera feedback from a remote vehicle and equipping the human operator with three-dimensional virtual cursors that can be used to interactively measure and model real features and objects in the remote environment. We include a description of the calibration techniques used to correctly align the real and virtual images both statically and under vehicle and camera motion. We also describe how we are using our system to demonstrate the potential of AR for improving the inspection of underground sewer pipes.
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