Abundant literature is available on the application of simulation in solving layout, materials handling, and production control problems, both in traditional and JIT environments. Senko and Suskind [1] have applied simulation in warehouse designs. Watford and Greene[2] reported on the use of simulation to determine minimum storage facility requirements and the length of time for materials to move between terminals. Pulat and Pulat[3] described a handling capacity study of an automated storage and retrieval system. Tavrou and Nagarajah[4] used simulation to compare push and pull systems of production control for an assembly line of an electronic device. Hearn[5] used simulation to analyse the effect of a JIT type solution to control materials flow and reduce workin-process inventory in a complex environment. More details of simulation and analytical models can be found in Graves et al.[6].This article describes our methods of addressing design problems faced by a leading chemical company in Australia when changing from a traditional manufacturing system to JIT. Our approach was to employ simulation using the SIMAN simulation language.The objective of this article is to report on the use of simulation models in:q analysing the performance of alternative cell designs in terms of materials handling requirements;q estimating the operator work loads under the new JIT operating system;q determining the reorder levels in order to operate the JIT system successfully.
A case study involving the use of simulation to analyze options to increase production of a copper production facility in Australia is reported here. A detailed and accurate model was developed capturing the factors affecting production and materials handling. The study resulted in prototype software with an Excel-based interface that allows the user to do further experiments with the model. Animation was used throughout the life cycle of the simulation. The paper illustrates various modeling issues faced and how they were resolved in the modeling of this copper production process. The model allows for experimenting with many options to increase production, including change of pot sizes, casting rates, storage, and other resources' capacities. The study is an example for the usefulness of computer simulation technology to analyze manufacturing systems.
This is a further development of a network model for electrons in solids. It is postulated that the electrons are restricted to move along I-dimensional lines between atoms. The network for a given solid corresponds to that which one would use in a wire and ball model to exhibit the crystal structure. A potential of the form V = -Vo sech' yx is associated with each "atomic" node point. The atom can have 1,2,3, or more electronic bound states, depending on Vo and y. The wavefunctions have the usual Bloch form and involve hypergeometric functions. The density of states is plotted. Localized defect energy levels are also given for various types of atomic defects. An especially interesting feature of the model is that all the above-mentioned calculations are made exactly, without resorting to perturbation theory.
The partition function and critical equations for the generalized triangular Ising lattice are determined in terms of weight factors associated with the decorating lattice. As an example, a lattice which incorporates the Kagome, hexagonal, triangular, and rectangular lattices is solved by the method developed.
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