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OPTIMIZATION CRITERIA FOR BATCH RETORT BATTERY DESIGN AND OPERATION IN FOOD CANNING-PLANTS

Authors :
Arthur A. Teixeira
Sergio Almonacid
Ricardo Simpson
Source :
Journal of Food Process Engineering. 25:515-538
Publication Year :
2003
Publisher :
Wiley, 2003.

Abstract

Optimization of thermal processing in the commercial sterilization of canned foods is of great interest because the canning industry plays an important role within the economy of the food processing sector. Many food canning plants operate in a batch mode with a battery of individual batch retorts. The aim of this study was to propose and analyze several criteria and methodologies for optimum design and operation of such retort systems. Two criteria were proposed in the case of choosing the optimum number of retorts to be installed when designing a new batch-operated canning line. The third criterion dealt with seeking optimum process conditions for maximizing output from a fixed number of retorts when processing small batches of different products and container sizes. In the case of new plant design optimization, one objective was to determine the optimum number of retorts that would minimize on-going processing costs related to labor and energy. Retort scheduling (programming) was studied from which a simple mathematical expression was derived for this purpose. A second objective was to determine the optimum number of retorts that would maximize the net present value of initial investment. Approaches based upon engineering economics were studied from which to develop a mathematical procedure for this purpose. In the case of maximizing output from a fixed number of retorts for different products and container sizes, isolethal processes were identified for various product/containers from which a common set of process conditions could be chosen for simultaneous processing of different product lots in the same retort.

Details

ISSN :
17454530 and 01458876
Volume :
25
Database :
OpenAIRE
Journal :
Journal of Food Process Engineering
Accession number :
edsair.doi...........a6ba34142ca09843210b2475cb4f99f1