Abstract: In order to address construction project requirements
and specifications, scholars and practitioners need to establish
taxonomy according to a scheme that best fits their need. While
existing characterization methods are continuously being improved,
new ones are devised to cover project properties which have not been
previously addressed. One such method, the Project Definition Rating
Index (PDRI), has received limited consideration strictly as a
classification scheme. Developed by the Construction Industry
Institute (CII) in 1996, the PDRI has been refined over the last two
decades as a method for evaluating a project's scope definition
completeness during front-end planning (FEP). The main
contribution of this study is a review of practical project classification
methods, and a discussion of how PDRI can be used to classify
projects based on their readiness in the FEP phase. The proposed
model has been applied to 59 construction projects in Ontario, and
the results are discussed.
Abstract: An artificial neural network (ANN) approach was used to model the energy consumption of wheat production. This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury in the 2007-2008 harvest year.1 In this study several direct and indirect factors have been used to create an artificial neural networks model to predict energy use in wheat production. The final model can predict energy consumption by using farm condition (size of wheat area and number paddocks), farmers- social properties (education), and energy inputs (N and P use, fungicide consumption, seed consumption, and irrigation frequency), it can also predict energy use in Canterbury wheat farms with error margin of ±7% (± 1600 MJ/ha).
Abstract: Supply network management adopts a systematic
and integrative approach to managing the operations and
relationships of various parties in a supply network. The objective
of the manufactures in their supply network is to reduce inventory
costs and increase customer satisfaction levels. One way of doing
that is to synchronize delivery performance. A supply network can
be described by nodes representing the companies and the links
(relationships) between these nodes. Uncertainty in delivery time
depends on type of network relationship between suppliers. The
problem is to understand how the individual uncertainties influence
the total uncertainty of the network and identify those parts of the
network, which has the highest potential for improving the total
delivery time uncertainty.
Abstract: Semisolid metal processing uses solid–liquid slurries
containing fine and globular solid particles uniformly distributed in a
liquid matrix, which can be handled as a solid and flow like a liquid.
In the recent years, many methods have been introduced for the
production of semisolid slurries since it is scientifically sound and
industrially viable with such preferred microstructures called
thixotropic microstructures as feedstock materials. One such process
that needs very low equipment investment and running costs is the
cooling slope. In this research by using a mechanical stirrer slurry
maker constructed by the authors, the effects of mechanical stirring
parameters such as: stirring time, stirring temperature and stirring
Speed on micro-structure and mechanical properties of A360
aluminum alloy in semi-solid forming, are investigated. It is
determined that mold temperature and holding time of part in
temperature of 580ºC have a great effect on micro-structure and
mechanical properties(stirring temperature of 585ºC, stirring time of
20 minutes and stirring speed of 425 RPM). By optimizing the
forming parameters, dendrite microstructure changes to globular and
mechanical properties improves. This is because of breaking and
globularzing dendrites of primary α-AL.