Complex Design Requirements in the Food Industry: Cases and Implementations Using JMP(R) ( 2019-EU-45MP-088 )
Feb 11, 2019 4:32 PM
| Last Modified: Mar 18, 2019 9:28 AM
Level: Intermediate Job Function: Analyst / Scientist / Engineer Bart De Ketelaere, Research Manager, KU Leuven Volker Kraft, JMP Senior Academic Ambassador, SAS Peter Goos, Full Professor, University of Leuven and University of Antwerp
New product development in the food industry often is a highly complex setting that might involve batch-to-batch variation in addition to mixture variables, process variables and observable but uncontrollable factors. Designing experiments with such a complexity requires a tailored and flexible approach that is offered by so-called optimal designs. During this joint presentation, we will show typical examples from the food industry to set the scene. Next, we will show the possibilities offered by JMP to produce such optimal designs. Finally, we will elaborate on a practical case from a food company that wishes to optimize a new product. The envisaged experiment involves a constrained mixture of seven components in addition to six covariates measuring properties of the batches used. After presenting a plausible model for this case, we will create an optimal design using the unique features of JMP and analyze results obtained from it.