Quantifying and visualising variation in batch operations: A new heterogeneity index

Abstract

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.