Dedicated to DOE techniques for improving process understanding and performance. Content here covers factorial designs, regression analysis, randomization, and optimization strategies to make data-driven decisions.

Sequential DOE Strategy: When Three Focused Experiments Beat One Large Design

In most real projects, running a sequence of smaller DOEs yields more knowledge per run and carries far less risk than committing everything to one large design upfront. You learn from each stage, adjust your assumptions, and spend resources where they matter most. That is the core logic behind a sequential DOE strategy, and [...]

Catapult DOE: Why Air Academy Uses a Wooden Catapult to Teach Experimentation

The wooden catapult is a signature Air Academy Associates teaching tool because it compresses complex DOE concepts into a tangible, memorable exercise. Instead of watching slides about factorial designs and interaction plots, learners physically launch a ball, record distances, and immediately see what the data is telling them. In this article, we'll unpack how [...]

How to Run a Fractional Factorial DOE in Excel Using DOE Pro XL: Step-by-Step

You are about to complete a full fractional factorial DOE workflow in Excel using DOE Pro XL, from design creation through analysis and factor recommendations. This guide assumes you already understand DOE fundamentals and have chosen DOE Pro XL as your Excel-native screening tool. In this article, we walk through each step with menu [...]

How Aerospace MRO Teams Use DOE to Cut Engine Overhaul Cycle Time

Structured Design of Experiments (DOE) has helped MRO shops cut engine overhaul turnaround time (TAT) by 20–40% in documented case studies. These results did not come from guesswork—they came from disciplined, statistically sound experimentation applied directly on the shop floor. In this article, we break down exactly how MRO teams design and run experiments [...]

A/B Testing as a Six Sigma Experiment: Optimizing Digital Conversion Rates

Digital marketers run hundreds of A/B tests each year, yet many declare a winner without confirming statistical significance or isolating the true drivers of conversion lift. When you treat an A/B test as a formal DOE, you move beyond guesswork and build a repeatable system for data-driven decisions that deliver measurable business outcomes. This [...]

Design of Experiments for Six Sigma Black Belts: From Screening to Optimization

Design of Experiments (DOE) serves as the statistical backbone of the Six Sigma Black Belt methodology, transforming complex process optimization from guesswork into precise scientific investigation. Professionals who want structured support can explore Air Academy’s broader Design of Experiments training options for practical DOE learning. Six Sigma Black Belts leverage DOE to identify critical [...]

Cross-Disciplinary Applications of DOE in Operations

Design of Experiments (DOE) is a crucial methodology for achieving operational excellence, providing a systematic, statistical framework for improving processes across various disciplines. Its utility spans numerous fields, including manufacturing, healthcare, and supply chain management. This approach empowers practitioners to base their decisions on solid, empirical evidence. This guide delves into the cross-disciplinary applications [...]

Mixed-Model DOE for Complex Operations

The ability to efficiently analyze and improve complex processes is paramount for managers and leaders. Mixed-Model Design of Experiments (DOE) is a critical methodology for achieving this goal. By integrating fixed and random effects, mixed-model DOE allows a nuanced examination of how various factors interact within complex operational systems. This approach enhances decision-making and [...]

Time Series Analysis and DOE in Operational Forecasting

The combination of time series analysis and Design of Experiments (DOE) is a critical tool for corporate executives and process optimizers trying to enhance operational forecasting in an increasingly data-driven world. This formal method takes advantage of the sequential character of time series data and DOE's capability for systematic exploration. This combination improves the [...]

Customizing DOE for Small and Medium Enterprises

Small and Medium Enterprises (SMEs) constantly seek ways to optimize processes, enhance product quality, and increase efficiency. One proven methodology for achieving these goals is the Design of Experiments (DOE), a statistical approach that allows for systematic, efficient experimentation. However, SMEs' unique challenges and constraints—such as limited resources and the need for cost-effective solutions—demand [...]

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