Simplify Complex Experiments with EngineRoom’s DOE Software

Design of Experiments (DOE) is a data-driven approach to testing multiple factors simultaneously to uncover insights that drive better decisions. Whether you’re optimizing a manufacturing process, improving a check-out process, or refining research methods, DOE provides a structured way to understand relationships between variables.

There are seven types of DOE studies:

• Full Factorial Designs test all possible combinations of factors and levels to fully understand interactions.
• Fractional Factorial Designs use a subset of combinations to save time while identifying key factor effects.
• General Factorial Designs allow factors to have more than two levels for detailed insights.
• Screening Designs (Plackett-Burman) identify the most important factors among many with minimal runs.
• Response Surface Designs optimize responses by exploring factor levels and non-linear relationships.
• Mixture Designs study how the proportions of components in a mixture affect the outcome.
• Taguchi Designs focus on improving robustness and quality by minimizing variability.

Start with the end in mind. What outcome are you trying to achieve? For the best cake recipe, your goal might be to bake a fluffy, moist, and evenly baked dessert that everyone loves. Identifying clear goals—whether it’s reducing defects in a process, improving product performance, or perfecting a recipe—is the foundation of any well-designed experiment.

EngineRoom How-To

1. Sign up for a 30-Day free trial of EngineRoom. It's completely free and does not require a credit card.
2. Login to EngineRoom and select New Project.
3. You can either use the search bar or navigate to Analyze > Design of Experiments to access the DOE Planning Worksheet.

The DOE Planning Worksheet is used to define the problem, set objectives, and outline key details like factors and timelines. This tool ensures your project team stays aligned and provides a clear reference for the experiment’s purpose and structure.

As your experiment evolves, the worksheet can be updated with new information. The completed worksheet will guide your experiment setup and maintain consistency throughout the process.

Decide how to test the factors you’ve identified efficiently. For the best cake recipe, you might test three factors—flour type, baking temperature, and baking time—at two levels each. Testing every possible combination provides the most detail but might not be practical if you’re short on time or resources. A structured experimental design helps you balance precision and efficiency.

EngineRoom How-To

1. Open the DOE Tool: Navigate to Analyze > Design of Experiments and select DOE to begin.
2. Add Factors and Levels: Input each factor (e.g., flour type, temperature, baking time) and specify the levels you want to test.
3. Select Resolution: Choose a full factorial design for maximum detail or a fractional factorial design to save resources.
4. Set Additional Options: Configure replicates, blocks, and other settings to tailor your experiment to your goals.
5. Generate the Design: Click Create your Experiment to produce a design matrix that organizes your trials and prepares you for data collection.

Challenge: A manufacturer of electronic components was experiencing inconsistent product quality due to unknown process variations.

Solution: Using EngineRoom’s full factorial design of experiments, the team tested combinations of factors like soldering temperature, conveyor speed, and material properties.

Result: They identified the key drivers of defects and implemented changes that reduced errors by 30%, saving thousands in rework costs.

Why It Matters: DOE enables manufacturers to find answers faster, optimize processes, and maintain high-quality standards in competitive markets.

Challenge: A mid-sized mortgage and leasing company, needed to reduce customer service call wait times, which remained above the industry standard despite recent improvements in staff training and scheduling.

Solution: Using a two-level full factorial design, the process improvement team tested three factors: number of queues (one or two), type of headsets (mono-aural or bi-aural), and the addition of an extra specialist.

Result: The analysis showed that implementing a single queue and bi-aural headsets significantly reduced call wait times, regardless of the addition of an extra specialist.

Why It Matters: DOE enabled LoanAssure to efficiently identify the optimal combination of factors, improving customer service and operational efficiency.

Challenge: A pharmaceutical R&D team needed to find the right combination of ingredients to ensure effective drug performance and consistent release.

Solution: Using EngineRoom’s DOE Wizard, the team designed an experiment to test different concentrations of active ingredients and excipients under various production conditions.

Result: The experiment identified the optimal formulation in half the time of traditional methods, significantly speeding up the development process.

Why It Matters: DOE helps researchers uncover critical insights faster, enabling them to develop high-performing, and even life-saving products with greater efficiency.