Investment in capacity expansion remains one of the most critical decisions for a manufacturing organisation with global production facilities. Multiple factors need to be considered making the decision process very complicated. The purpose of this paper is to establish the state-of-the-art in multi-factor models for capacity expansion in manufacturing plants and networks. A three phase research programme is presented consisting of an extensive literature review and a structured assessment of the strengths and weaknesses of the current research. The study found that there is a substantial amount of work on development of mathematical multi-factor models for capacity expansion. Despite that, no single work captures all the different facets of the problem.
Simulation cloning is designed to satisfy the requirement of examining alternative scenarios concurrently. This article discusses the issues involved in cloning distributed simulations based on the High Level Architecture (HLA) and proposes tentative solutions. Alternative solutions are compared from both the qualitative and quantitative point of view. In terms of federation organization, candidate solutions can be classified into the single-federation and the multiple-federation categories. To guarantee the correctness and optimize the performance of the whole cloning-enabled distributed simulation, the single-federation solution requires an additional mechanism to isolate the interactions among alternative executions. Data distribution management (DDM) is one of the candidate approaches. To measure the trade-off between complexity and efficiency, the authors introduce a series of experiments to benchmark various solutions at the runtime infrastructure (RTI) level. The benchmark results indicate that the single-federation solution provides encouraging performance when using DDM.
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