Design and Analysis of Storing Experiments: A Case Study

• Published in: Quality engineering Vol. 16; no. 4; pp. 591 - 611
• Main Authors: Bjerke, Frøydis, Aastveit, Are Halvor, Stroup, Walter W., Kirkhus, Bente, Næs, Tormod
• Format: Journal Article
• Language: English
• Published: Milwaukee Taylor & Francis Group 01-06-2004; Taylor & Francis Ltd
• Subjects: Case studies; Empirical modeling; Food products; Linear mixed models; Linear programming; Mayonnaise production; Product development; Quality control; Repeated measures; Response surface methods; Robustness; Studies; Viscosity
• ISSN: 0898-2112; 1532-4222
• DOI: 10.1081/QEN-120038021

In order to achieve robust and stable food products of desired quality and characteristics, all stages of the food production process, including storage conditions, should be considered during product development projects. This article describes a multistage production development project on low-fat mayonnaise, where experimental design was used to set up a pilot plant study involving ingredient factors, processing factors, and storage factors and their effect on mayonnaise viscosity. The article discusses three alternative empirical modeling approaches to analyze the data-namely, a simple graphics approach, a robustness approach, and a mixed models approach-considering their multistratum (split-plot) structure and repeated measurements of each subsample. In the case study, all information relevant for business decisions was obtained through the combination of graphical analysis and the robustness approach. This information could also be extracted by a practitioner, while the mixed model analysis clearly requires a graduate statistician. In order to obtain valid and useful information for the practitioner in an efficient way, the authors believe that, usually, the first two approaches would be sufficient. The more complex mixed model strategy might be advisable if a deeper understanding is required or desired.