Abstract
Abstract Due to the energy-intensive nature of the heat treating industry and the recent substantial increase of energy prices, the availability of predictive tools that can be used to optimize heat treatment processes has become a very pressing must. Load configuration (size and arrangement) during batch-type heat treating operations is the main factor that controls the rate of heat transfer between the furnace and the load, and hence it affects energy utilization and productivity of such operations. The main objective of this work is to develop a numerical model that can be used as a predictive tool for determining optimum loading of batch-type furnaces in order to achieve maximum productivity (mass treated per unit time) and minimum energy consumption per unit mass. A numerical model has been developed to simulate heat treatment processes in batch-type furnaces. The model has been validated by comparing numerical results with experimental data collected under laboratory and real-life conditions. Experiments have been carried out at the research facility at TPL as well as at different industrial sites. The paper presents the development and validation of the model as well as case studies of batch heat treatment cycles where best load configurations have been investigated.
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