Using Experimental Design Techniques to Optimise Products (2 x 1hr sessions)
Product code: R-DoE
May 6, 2020 - May 7, 2020
Virtual option available
Course runs Wed 6th May 2-3pm and Thu 7th May 2-3pm (GMT).
The remote learning package consists of a live lecture delivered online by one of the Qi Statistics team, plus a pdf of the lecture notes and email support for you to ask questions on the course material after the course for up to 2 weeks following the course. More than just a recorded webinar and as close to face-to-face training as it can be!
This module focuses on the statistical techniques of experimental design (DoE) applied to sensory and consumer science projects. It covers the approaches to product optimisation which control the recipes/processing variables tested with the aim of giving clear guidance on the key drivers of sensory/consumer responses. There are many different software tools which help with this, creating the experimental sample designs and providing graphical analysis to aid interpretation of the results.
The course content (split over the 2 sessions) is as follows:
- Motivation for use of structured sample designs.
- Finding the key influences on consumer liking and sensory characteristics and uncovering interactions between ingredients and process parameters.
- Using these key parameters to plan further studies to optimise and predict liking.
- Dealing with more difficult problems -investigating the complete recipe or mixture.
- Visualisation of the response surfaces, simultaneous optimisation of several performance measures including cost.
Design techniques (factorials, response surfaces, mixtures) will be illustrated by case studies using consumer and sensory panel data.
The different software options that could be used (e.g. Design Expert, JMP, Minitab, MODDE etc.) will be discussed.
The course will run for 2 consecutive days, with each online sessions starting at 2pm (GMT) each day.
A basic understanding of statistics is assumed i.e. knowledge of statistical significance, ANOVA
$265.48 – $294.25 (Excluding any applicable taxes)