Design of Experiments (DOE) has long been at the heart of innovation, quality improvement, and product optimization. While classical designs such as full factorial and fractional factorial experiments remain foundational, modern engineering and product development challenges increasingly demand more flexibility. That’s where optimal designs come in — and why Minitab’s continued investment in this area, including the addition of Effex’s optimal design capabilities, meaningfully strengthens the portfolio.
Optimal designs are computer-generated experimental designs that are built to satisfy specific modeling or practical constraints. Instead of relying on predefined design structures (like 2^k factorials), optimal designs use algorithms to select the most informative experimental runs based on:
At their core, optimal designs answer a critical question:
Given real-world constraints, what is the most statistically efficient set of experiments we can run?
This flexibility makes them indispensable in modern industrial, pharmaceutical, advanced manufacturing, and R&D environments where textbook designs often don’t fit the problem.
Organizations face increasing pressure to:
Traditional factorial or response surface designs work well under ideal conditions. But real-world experimentation rarely happens under ideal conditions.
Optimal designs allow practitioners to:
1. Handle Irregular Design Spaces
When certain factor combinations are infeasible, unsafe, or impossible, optimal designs can exclude those regions while maintaining statistical power.
2. Manage Mixed Factor Types
Experiments often include a combination of continuous factors, categorical factors, and constrained mixture components. Optimal design algorithms accommodate this complexity seamlessly.
3. Minimize Runs While Maximizing Information
When runs are expensive — such as in aerospace testing, pharmaceutical development, or high-value manufacturing — optimal designs ensure each run contributes maximum information toward the desired model.
4. Support Custom Modeling Goals
Different problems require different optimality criteria:
Optimal designs allow teams to choose the criterion aligned with their business objective.
Minitab has long supported optimal designs as part of its comprehensive DOE platform, giving users:
The addition of Effex’s optimal design technology further enhances Minitab’s portfolio in meaningful ways.
1. Advanced Algorithmic Depth
Effex brings additional optimization techniques and computational approaches that expand the range and robustness of design generation. This strengthens:
As experiments become more multidimensional, algorithmic sophistication becomes increasingly important.
2. Greater Flexibility in Complex Constraints
Modern experiments often involve:
Effex’s capabilities extend the ability to generate statistically efficient designs even under highly restrictive conditions — reducing compromises between feasibility and statistical power.
3. Enhanced Support for Advanced Modeling Needs
In advanced R&D settings, teams may require:
By expanding the available design generation strategies, the combined Minitab + Effex portfolio better supports these sophisticated use cases.