FAQs

Based on the White paper located here, “Minimum Incremental Move”—which is also sometimes referred to as “Minimum Step Size”—is defined as the smallest amount of motion that a control system is capable of realizing. As a common parameter found on single and multi-axis motion system datasheets, its true value depends heavily on the exact location where it is measured, dictating that any specification claim should always have a specific location associated with it. This metric is influenced by numerous variables, specifically control approaches and the system’s design architecture, which encompasses factors like sensor location, force delivery, bearing type, and load point offset. 

Crucially, the document highlights a significant distinction between measuring this step size at the actuation point versus the actual load point. At the actuation point, this minimum step size is generally equivalent to the system’s overall resolution. However, at the load point—where the critical process activity actually takes place—the minimum step size is generally equivalent to the system’s repeatability. Because a system’s repeatability is frequently larger than its resolution, specifying raw resolution as the minimum step size is a poor and inaccurate representation of performance at the load point; ultimately, for a minimum step to have a useful outcome, it must be repeatable.

At ALIO, we frequently remind our customers that while Resolution and Minimum Step Size are related, they represent very different practical metrics. Resolution is simply the theoretical distance that a single encoder count represents. Conversely, Minimum Step Size is the actual, physical minimum motion that the control system can reliably realize. While resolution and minimum step size might appear equivalent at the internal actuation point, the true minimum step size at the load point—where your critical process actually occurs—is generally equivalent to the system’s overall repeatability. Because repeatability is often significantly larger than the base resolution (sometimes by a factor of 5 to 10), using resolution to define a stage’s minimum step capability is highly inaccurate; for a minimum incremental move to have a useful, predictable outcome, it must be repeatable.

A traditional Stewart Platform, commonly known as a hexapod, achieves six degrees of freedom (6-DOF) by connecting a top platform to a fixed base using six independently actuated legs in a parallel kinematic configuration. While this design is capable of complex, coordinated movements, it inherently suffers from mechanical bottlenecks. In a standard hexapod, every leg and joint contributes to overall positioning errors, making non-vertical motions (such as X, Y, pitch, and roll) less precise because all legs must perform different motions simultaneously. This traditional structure also struggles with a lack of passive stiffness when unpowered, degradation in flatness and straightness that is unacceptable for nanometer-level work, and a yaw rotation that is typically restricted to small angular ranges. 

The Hybrid Hexapod® serves as an evolutionary next step by retaining 6-DOF capabilities while fundamentally changing the underlying mechanical structure to solve these limitations. Instead of relying on six identical actuators for all movement, the Hybrid Hexapod utilizes a parallel tripod kinematic structure for Z-axis, pitch, and roll movements, pairs it with a monolithic serial kinematic XY stage for planar motion, and incorporates a dedicated rotary axis for continuous 360-degree yaw. This specific design allows for direct control of primary motion axes and significantly improves motion fidelity. As a result, the Hybrid Hexapod delivers sub-micron-level accuracy, greater stiffness in both powered and unpowered states, and a usable workspace that is up to 10 times larger than that of a conventional hexapod. The XY stage base architecture also enables long travel distances to also serve as a transport mechanism. In a traditional hexapod, however, loading and un-loading, or applications requiring multiple step processes performed by different sub-systems, would require an additional seventh and eight motion axis.

When comparing precision motion stages, understanding the fundamental difference between accuracy and repeatability is critical to selecting the right architecture for your application.

Accuracy

Accuracy is the measure of how closely a motion system’s actual physical position matches the commanded position. Using the classic target analogy, accuracy is how close your arrows land to the absolute center of the bullseye. In precision motion stages, the best strategy is to minimize mechanical error sources so that when motion is commanded, the stage arrives at that exact, true point in space without deviation.

Repeatability

Repeatability—often specified as bi-directional repeatability—is the system’s ability to reliably return to the exact same location under identical conditions, regardless of where that location is relative to true zero. Going back to the target analogy: if you fire a cluster of arrows and they all land in a tight, overlapping group out on the outer ring, you have high repeatability. The shots missed the bullseye, but the behavior is perfectly predictable.

In a stage, this means that every time you command a move to a specific coordinate, it lands in precisely the same spot every single time. Crucially, you can calibrate a highly repeatable system to become accurate, but no amount of calibration can make an unrepeatable system accurate.

The Cost of Accuracy vs. The Cost of Repeatability

The financial dynamics between these two metrics frequently drive system design choices. Achieving pure mechanical accuracy straight out of the box requires significant upfront capital. It demands ultra-precise machining, premium bearing architectures (such as crossed-roller or air bearings), and high-end encoders designed to minimize Abbe errors, yaw, and structural deflections.

Because mechanical accuracy is expensive, many engineers attempt to bridge the gap using software error mapping. This involves taking a less expensive, highly repeatable stage and measuring its absolute positioning errors at discrete intervals across the travel range. The controller then compensates for these known deviations on the fly.

While this software compensation is often used to improve accuracy, care should always be taken to understand the environment, as temperature is strong contributor to any mapped application. Other factors impacting mapped performance are location (Y position when mapping X), Duty Cycle (temperature rise from internal motor heating), and component replacement (new components could be installed with large impacts to original mapped outcomes.

Angular errors (pitch, roll, and yaw) are important because the actual work in a precision system happens at a load point located a certain distance away from the stage’s internal sensors. In physics, this physical offset creates what is known as Abbe error. A tiny tilt (pitch or roll) or twist (yaw) at the base of the stage gets magnified over that distance, creating a much larger linear misalignment at the tool center point. Because of this magnification, an internal encoder might read a perfect position, but angular errors will still physically shift the active vector and cause the tool to miss its true target.

In practical manufacturing, hitting a single theoretical point is not enough. A system must maintain volumetric accuracy across the entire travel. If you do not control angular errors, the resulting geometric shift produces real-world defects like line wander, uneven thickness, and obvious stitching artifacts in micro-printing applications. For fields like advanced packaging and smart metrology, unchecked angular wobble and drift directly corrupt datasets and cause yield loss. By controlling pitch, roll, and yaw alongside linear motion, you protect overlay integrity, ensure accurate bio-image tiling, and guarantee your process is built on a stable foundation.

When a linear stage moves along a straight path, it is supposed to stay perfectly flat and square. However, mechanical imperfections in the bearings or machined surfaces can cause the platform to twist or tilt slightly as it travels. These unintended rotational movements are called angular errors, and they are broken down into three specific types:

• Pitch: Rotation around the side-to-side axis (typically the Y-axis). Imagine driving a car over a speed bump; the front tilts up and then down. For a stage, pitch means the platform is tipping forward or backward as it moves.
• Roll: Rotation around the axis of travel (the X-axis). Think of a boat rocking side to side, or an airplane dipping a wing. In motion control, roll happens when the carriage leans sideways left or right during a move.
• Yaw: Rotation around the vertical axis (the Z-axis). Picture steering a car left or right. For a linear stage, yaw is the tendency of the platform to twist horizontally off its straight path.

Together, these three errors define how much a stage deviates from a perfectly flat, straight, and level orientation during its movement.

6D Nano Precision® is a term trademarked by ALIO Industries to describe a higher, more rigorous standard of performance than traditional 2D planar metrics.

In the motion control industry, companies frequently specify a stage’s performance based on 1D or 2D “planar repeatability”—meaning they only measure how well the stage repeats its position along the axis of travel, assuming the axis is perfectly straight. However, ALIO points out that all motion systems operate in three-dimensional space and have error motions in six degrees of freedom (6-DOF). At the nanometer level, an axis of travel is never perfectly straight; it bends, twists, tips, and tilts as the stage moves.

“6D Nano Precision” means measuring and accounting for all of these spatial errors—linear positioning, straightness, flatness, pitch, yaw, and roll—simultaneously. By focusing on “point repeatability” rather than plane repeatability, ALIO ensures that a specific point in space is accurately and repeatably targeted. This guarantees that a stage doesn’t just stop at the right coordinate on a linear scale, but also stays perfectly flat and square, which is critical for highly demanding applications like microlithography, wafer manufacturing, and advanced metrology.