کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4909203 | 1427105 | 2017 | 37 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Quantifying and visualising variation in batch operations: A new heterogeneity index
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
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چکیده انگلیسی
Heterogeneity, a distribution of rates and achieved temperatures, during bulk chilling, drying and freezing processes can be a leading cause of losses and quality decline in the food manufacturing industry. Assessing or comparing system performance would benefit from a set of robust tools to report, compare and contrast the levels of heterogeneity; at specific times and over the entire operational period. A new heterogeneity index is presented here, including novel methods to model, visualise and quantify heterogeneity. The new index describes temperature or moisture distributions as a Skew-Normal distribution; introduces the heterogeneity plot to visualise heterogeneity over time; and quantifies total system heterogeneity with the Overall Heterogeneity Index (OHI). These methods were applied to the forced-air cooling of polylined kiwifruit. The index and methods can now be used to quantify benefits in package design and operational variation, thus providing a rigorous, substantive approach to evaluating innovations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Food Engineering - Volume 196, March 2017, Pages 81-93
Journal: Journal of Food Engineering - Volume 196, March 2017, Pages 81-93
نویسندگان
J.R. Olatunji, R.J. Love, Y.M. Shim, M.J. Ferrua, A.R. East,