Best way to review an extended size run
- Approve the base-size fit and confirm the intended size chart and grade rules first.
- Pair each graded size with the avatar that represents its intended body measurements.
- Simulate the sizes and compare silhouettes under consistent viewing conditions.
- Use fit maps to locate areas for investigation, then trace an outlier to its pattern pieces and grading rules.
Yes. You can visualize how grading affects fit across a size range by pairing each size with an intended avatar, simulating each garment, and comparing the results side by side. CLO’s Grading Review is one documented option: it compares simulated garments and avatars for all grading sizes on one screen. The review is most useful after the base fit, target size range, and grading logic are settled.
1. Set the base size, size range, and grading rules
Start with an approved base-size garment, then review the extended sizes. This keeps an existing base-size fit issue distinct from a change introduced by grading and gives the CLO review a clear point of comparison.
Write down the sizes being added, their intended body-measurement profiles, and the grade rules that connect them to the base. The ISO 8559-1:2017 measurement definitions describe measurements used to build physical and digital anthropometric databases and size-and-shape profiles for apparel development. The ISO 8559-3:2018 methodology addresses how to establish body-measurement tables and intervals for population groups; its examples offer a method for building tables, rather than universal size values to apply to every brand.
Treat the body chart, pattern grade rules, and avatar measurements as related but distinct inputs. A body-size interval describes intended people; a grade rule controls how pattern points change from one size to another. The reviewer’s job is to confirm that the extended pattern follows the team’s documented rules and that each avatar reflects the intended size profile.
This distinction matters because a size label alone does not prove that the underlying measurements and grade increments align. In a 2005 study, Nancy A. Schofield and Karen L. LaBat examined 40 women’s clothing size charts and found structural assumptions that did not match anthropometric research. In their analysis of upper-torso measures, only 17% of measurements were useful for grade-rule formation, and 11 of 38 compared grade rules corresponded to body measurements. Those findings support a practical review: keep the approved measurement chart and grade-rule specification beside the simulation, and investigate a size whose pattern changes do not match either one.
Before opening a 3D review in CLO, look over the 2D graded patterns for the new sizes. Check notches and corner points, including those on waistbands, and compare corresponding body-pattern segment lengths across sizes. For example, compare a waistband seam with the garment edge it joins in each size. A mismatch can surface as a stitching or fit problem in the simulation, so resolve the pattern relationship before interpreting a map as a body-fit issue.
2. Pair every graded size with an intended avatar
Set up a size-to-avatar match for every size you plan to review, including each new size beyond the original run. CLO’s Pair Avatar for Grading Size instructions support adding avatars for graded sizes. The guide says the avatar in the 3D window applies to all sizes by default, so update the size-specific pairing when a separate avatar is needed to represent a new size.
CLO’s Pair Avatar instructions show the workflow in Object Browser → Grading: click Update, then use Pair 3D Form beside Base Size to add an avatar or avatar-size file. The added avatar replaces the avatar in the 3D window, or the added size file is applied. CLO also notes that other size groups are combined based on the base size, so check the listed size-to-avatar assignments when extending an existing set.
For a clear review record, note the garment size, its paired avatar or measurement profile, and why that profile represents the intended fit target. CLO’s size-specific avatar pairing helps keep those assignments visible as you review the extended range.
Use avatars that match the customer or fit model profile the product is designed for. If the new range spans distinct body-shape groups, use an avatar for the intended profile in each relevant size group where the software workflow allows it. A single avatar scaled through the range gives a consistent visual reference, while size-specific avatars let the team inspect how the garment relates to different size profiles. Keep the chosen avatar and measurement assumptions with the review so a later comparison uses the same inputs.
3. Simulate the sizes and compare them together
Run a simulation for each graded size you intend to assess, using the size’s assigned avatar. CLO’s Grading Review guide states that the review is activated from simulated results for each grading size and can compare all graded garments and avatars on one screen. This makes CLO’s Grading Review a useful way to assess the extended range in one place after running those simulations.
A repeatable CLO sequence is:
- Finish the grading edits and update the Pair Avatar assignments.
- Select the size items to review and simulate the garment on each assigned avatar.
- If you want the review to retain each size’s pose or arrangement, save that size’s 3D state from the Pair Avatar panel.
- Open Grading Review to compare the simulated sizes together.
CLO’s Save 3D State instructions say to save a 3D state for each size and explain that the saved states are applied in Grading Review mode. This provides a consistent comparison view: for example, pose a shirt’s sleeves and hem in a way that keeps the same areas visible, then save that presentation for each size.
Keep comparison conditions stable across the run. Use the same camera angle, garment presentation, and simulation settings for the sizes being compared, and note any deliberate exception such as a different avatar profile. As a suggested team workflow, capture the same front, side, and back views for the base size and the newly added sizes; consistency makes a change in shoulder slope, hem balance, or sleeve shape easier to spot than a changing viewpoint would.
A useful first pass compares the base size with the smallest and largest newly added sizes, then checks the intermediate sizes for a smooth progression. For a two-size extension, compare each new endpoint directly with the base. For a larger extension, use CLO’s Grading Review to scan the sizes together and trace any abrupt change back through adjacent sizes.
4. Read silhouette and fit maps as diagnostic signals
Compare the garment’s outline first, then use maps to locate pressure, tightness, or stretch patterns that merit a closer look. Across the same views, check shoulder and armhole shape, bust or chest balance, waist and hip ease, sleeve and leg proportions, and hem level.
CLO’s Garment Fit Maps guide describes four different signals. The Fit Map represents garment tightness: red marks “Can’t Wear,” orange “Very Tight,” and yellow “Tight,” described as slightly tight. The Strain Map shows garment stretch rate as a percentage, with blue at 100% (no stretch) and red at 120%; the Stress Map represents force along the fabric grain per unit area that causes garment deformation, with red at 100 kPa and blue at 0.00 kPa. The Pressure Map represents external pressure exerted by the garment onto the avatar.
Choose the map that answers the question you are investigating. A yellow Fit Map area near a waistband, for example, directs attention to tightness in that location; the next step is to compare the corresponding body and garment measurements and inspect the pattern pieces. A high-strain region on a stretch knit calls for a different interpretation from a similar location on a woven garment, so compare the map with the fabric and intended ease used in the design.
Map colors are software-defined signals that help locate regions for review. In CLO, interpret each map in the context of the garment, avatar, fabric, and intended fit rather than treating a color as a universal pass or fail.
Record what changes from size to size, not simply whether a color appears. For example, if the armhole looks smooth in the base size but shows a concentrated signal in one extended size, note the location, the size, the avatar, and the map type. Then compare the pattern and garment measurements in that area and determine whether the visual change matches the design’s intended fit.
5. Trace an outlier back to its pattern and grade rule
When one size looks different, compare it with the size immediately before and after it, then trace the affected shape to its grade points, adjoining seams, and documented rule. Start with a specific observation such as “the front hem rises at the larger size” or “the waistband joins a shorter body seam.” That turns a visual difference into a testable pattern question.
Fitinline’s guide to extending a size range illustrates a 4 cm circumference increase distributed among relevant pattern pieces, rather than 4 cm added to every edge. A pattern comparison shows where graded geometry changes, while the size chart and grade rules establish whether that change matches the team’s intended target. If a rule change is needed, record the size point and affected pieces so the correction can be checked in the next simulation.
A concrete example comes from patternmaker Alison Hoenes’s comparison of a dress graded from a medium. In Hoenes’s medium-based dress example, the waist became snug relative to bust and hip ease, the front hem hiked up at size 5X, and the bust darts sat too high. They show why an outlier review should inspect shape and landmark position, rather than treating the circumference number as the whole fit result.
Use this order when investigating a discrepancy:
- Confirm that the avatar is paired with the intended size and measurement profile.
- Compare the outlier with adjacent sizes in the same garment view and map.
- Record the pattern piece and point where the mismatch appears, then connect that location to the observed silhouette or map change.
- Flag a size when its target body measurements and documented pattern-grade progression no longer align.
- Correct the base pattern when the same fit issue appears across sizes; adjust the affected grading rule when the issue appears only as the size changes.
- Re-simulate the affected size and its neighbors, then compare the results under the same views and settings.
After the correction, retain the original and revised observations with the avatar assignment and rule change. The next development step is to share the updated comparison with the pattern and product-development decision makers, along with the size-specific findings that informed the change.
FAQ
Can I visualize how grading affects fit across a size range?
Yes. Pair each graded pattern with its intended avatar, simulate each size, and compare the same views across the run. CLO Grading Review displays all graded-size garments and avatars together after each size has simulated.
Do I need a separate avatar for every size?
Use a size-specific avatar when the team needs to represent that size’s intended body profile. CLO supports adding avatars for graded sizes; keep each assignment aligned with the target measurement profile.
Should I review only the smallest and largest sizes?
Review the endpoints first to see the full extension, then compare intermediate sizes for sudden shifts. The endpoint check is a quick screen; a visible outlier or a change in the intended fit calls for a closer look at the adjacent sizes and grade rules.
Do fit-map colors set a universal pass or fail?
No. Each software maker defines its map signals, while the team judges those signals against the garment’s fabric, avatar, construction, and intended ease. Use the map to find an area to inspect, then connect it to the measurements and design requirements.
What should happen after an outlier is corrected?
Re-simulate the changed size and its neighboring sizes, then compare the same views and map under the same conditions. Record the changed grade point or pattern piece with the updated results before moving the range to its next development review.