The Psychology of Quality and More

A Toolbook for Quality Improvement and Problem Solving (contents)

Design of Experiments (DOE): Examples

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When to use it | How to understand it | Example | How to use it | Practical variations

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Example

The marketing group in an airline wanted to increase the number of business class seats sold on its off-peak flights. Key factors were identified as advertising level and pricing strategy. They trialed two advertising campaigns and three pricing strategies in geographically separate but demographically similar areas. As there was a small number of possible trials, they performed a full factorial experiment, as illustrated. The results showed in the individual effects plots that the level of advertising campaign was significant and that pricing had a non-linear effect on seats sold. This was confirmed in the interaction effects plot, which showed that the first advertising level was ineffective whatever the pricing, and the second advertising level was most effective when coupled with the second pricing strategy.

Fig. 1. Example experiment

Other examples

• A plastic molding workshop wants to reduce injection molding rejects and thus perform a set of experiments which change injection pressure, mix temperature and setting time. Analysis of the results shows a combination of temperature and setting time as the most significant factor. Further experiments find the optimum combination of these.
• A market research team designs an experiment to determine which factors will most influence customers to purchase a product. They run a survey which asks questions about several levels of price, packaging and delivery. Unexpected results include a high sensitivity to price-delivery combinations. Consequently, a premium-rate couriered delivery service is set up and proves to be very popular.
• A yacht design team aims to improve speed through changing the shape of the boat's sail. Rather than try random shapes, they identify the key sail parameters and then design and perform a set of experiments with each factor set at two levels. They follow this up with multi-level experiments for the two most significant factors found in the first experiment set. The result is a new sail that increases speed by 5%.

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