Vision inspection of mixed worn parts for remanufacturing

Remanufacturing disassembly produces the opposite of a production line: a mixed stream of cores — gaskets, couplings, valve assemblies — each dirty, worn or damaged, and each needing two answers. Which part is this, and is it fit to reuse? One camera station answers both. It identifies each core from geometry wear cannot change, then runs only the inspection branch written for that part, at 15-30 parts per minute with automated presentation and 6-10 with an operator. This guide gives the identification rules, the cycle math, a worked camera, lens and lighting example with the arithmetic shown, and the cases where vision must hand the core to another test.

Can a camera identify a worn part without misreading it?

Yes — identify from machined geometry that wear does not change: bolt-hole count, bolt-circle diameter, flange outside diameter and shaft steps, matched with tolerance bands of ±1-2 mm, while wear and corrosion move surfaces by fractions of a millimeter.

Cracks, dents and corrosion change surfaces; they rarely change hole patterns or overall proportions. So the identification step measures two features on different scales — one silhouette dimension such as flange diameter, one internal pattern such as the bolt circle — and matches both against taught models. Two features on different scales mean a chipped corner cannot make one family look like another.

Set each tolerance band from measurement, not guesswork: wash 20 cores per family, measure the two features on every one, and set the band at three times the observed spread. Dimensional identification of new parts works the same way — part identification by dimensions to prevent mixed parts — except cores need the wider bands.

Then draw a hard line: a match score of 0.90 or above runs the part program, anything below goes to a manual review bin, and the system never guesses. In a tuned cell fewer than 2% of cores land in that bin, mostly untaught variants; verifying the correct part when sorting mixed batches covers that bin logic. Keep identification geometric, and send appearance-driven defect calls to a classifier — AI versus rule-based inspection on a smart camera lays out that trade-off.

How many parts per minute can one station really inspect?

Plan on 15-30 parts per minute with automated presentation and 6-10 with an operator loading nests, because the two vision steps together take 1-3.5 seconds and handling takes the rest of the cycle.

Add the rows: 2-4 s per part on a handler gives 15-30 parts per minute, and 6-10 s with an operator gives 6-10. The camera is never the constraint — two frames per part plus retries stays under 10 frames per second, a rate any modern vision camera meets. Budget two-thirds of the cycle to mechanics and one-third to vision, and spend your engineering time on the mechanics.

Log every core: family, decision, image. Warranty claims in remanufacturing are settled with images, and inline inspection that runs multiple checks and tracks each unit shows the tracking pattern to copy. When one core needs two faces checked, present it twice or re-orient it — triggering a camera at each waypoint keeps one camera serving all views.

How do you structure one program for many part types?

Branch by family: one shared identification step selects an item type, and each item type carries its own snapshot position, exposure, lighting recipe and pass rules — the structure multi-type sorting systems already use.

Each family is one item type with one branch. Teach it once, parametrically where geometry repeats: parametric teaching for geometric parts cuts teach time from hours to minutes across a family of flanges that differ only in diameter. When two families share the station, give each its own taught position — teaching two parts in one program with separate snapshots — and route by tray slot as sorting parts by face into tray layers does.

Commit to a ceiling: 20-40 families per station. Teach time runs 30-60 minutes per family, illumination tuning adds about an hour for the shiny ones, and past 40 families the station spends more time switching recipes than inspecting. Split the stream by size across two stations instead of degrading the first. For the wider system questions around this choice, selecting a machine vision system for parts inspection walks the same decision from the plant floor view.

What camera and lens do you need for cracks and wear?

A 12 MP camera on a 1.1" sensor with a 16 mm lens at 200 mm working distance covers a 162 × 120 mm field of view at 0.040 mm per pixel — a 0.25 mm crack spans 6 pixels and 0.5 mm of wear spans 12.

Size from the reject decision upward. A feature needs at least 3 pixels to be detected and about 10 pixels to be measured with edge tools; pixels per defect when sizing a camera for crack detection works the same rule from the defect side. Example inputs for this station: a largest core envelope of 150 × 110 mm, and a sensor of 14.1 × 10.4 mm with 4096 × 3000 pixels on a 3.45 µm pitch. Swap in your numbers.

The reject lines then follow from the pixel size. A gasket is scrapped when a crack opening of 0.25 mm or more appears — 6 pixels wide. A coupling goes to rework when its land runs 0.5 mm under nominal — 12 pixels, measured with edge tools repeatable to about a third of a pixel (0.013 mm), so the limit sits 37 times above the noise floor. For how dimensional systems hold that accuracy on small parts, computer vision dimensional inspection for small parts covers calibration and fixturing.

Camera and lens that match these numbers: the MV-CH120-11UC is a 12 MP USB3 area scan camera with a 1.1" sensor, a C-mount, a global shutter and a color imager that separates rust from clean steel. The LS-FFL-0567 is a 16 mm C-mount lens rated for 1.1" sensors, with an aperture range of F2.8-22 and distortion under 0.3%.

Both live in the area scan cameras and machine vision lenses catalogs, filterable by sensor format and mount. Then check the pairing against your own envelope:

How much depth of field and exposure does a mixed stream need?

Set f/8 and nest every family at one height: at this magnification the total depth of field is about 16 mm (±8 mm) with a two-pixel permissible blur, and strobe exposure is 1 ms for a static nest or a 100 µs pulse on a moving belt.

Mixed streams tempt you to stop down until everything is in focus. Resist at the small apertures: depth of field grows linearly with f-number, but so does the diffraction spot.

At f/8 the diffraction spot is about three pixels; at f/11 it reaches 4.3 and a 6-pixel crack loses its edges. The decision: fix each family's height in its nest and run f/8 with ±8 mm of freedom, rather than chasing ±15 mm at f/16. Aperture, f-number and depth of field works the formula both ways, and Airy disk size and the diffraction limit is why the small end of the aperture ring is never free. Where height still varies between families, scale compensation for part height variation corrects the measurement.

Exposure follows presentation. A part sitting still in a nest takes 1 ms at f/8 under a diffuse panel. The same part on a belt at 200 mm/s smears 200 mm/s × 1 ms = 0.2 mm — five pixels — so strobe instead: 200 mm/s × 100 µs = 0.02 mm, half a pixel. Static presentation also lets a rolling shutter do the work. For that case the MV-CS200-10UM is a 20 MP USB3.0 camera with a 1" sensor, a C-mount and a mono imager. Those are about 60% more pixels than the example station, worth spending when the smallest crack decides the verdict.

How do you light dirty cores with mixed surfaces?

Three recipes, not one: low-angle dark field makes cracks glow on flat gasket faces, a diffuse dome tames curved polished couplings, and a strobe controller fires 100 µs pulses so nothing smears.

Dark field lights a flat face at a grazing angle, the specular surface reflects that light away, and only the crack walls scatter brightness into the lens — the crack reads as a light line on a dark field, the easiest call in the program.

A dome does the opposite job on curved polished parts, illuminating from every direction so no single highlight saturates. Oil sheen defeats both; polarized light cuts it, and polarization comes integrated on some devices — the LS-SMC-0063 is a 1.6 MP smart camera with a 16 mm lens, white polarized light and 60 fps, fit for completeness checks on small assemblies.

Wash cores upstream regardless: oil and soot change reflectance more than any lighting recipe can compensate. Each core then takes two exposures — crack view under dark field, shape view under the dome — and two exposure times from one camera without serial commands is the mechanism. Gate the light to the inspection moment rather than the whole cycle; triggering a vision light on for two seconds at the inspection moment keeps LEDs cool and lifetimes long.

Smart camera or PC camera for the reman cell?

Stay on a smart camera up to about 20 families with single-view 2D checks; move to an area scan camera on a PC once families multiply, exposures alternate per trigger, or you need 12 MP and image archiving for audit.

The smart camera wins on simplicity: one sealed unit, inspection on the device, no PC in the cell. The MV-SC5060XM-08M-WBN is a 6 MP mono smart camera with an 8 mm M12 lens and a GigE interface, suited to the completeness branch on small assemblies. The PC path wins on headroom: more pixels for cracks, every image archived for warranty, and a place to add AI surface defect inspection to existing cameras once the reject bin shows what fixed rules missed. Set the three architectures side by side:

Values as printed in each product's data sheet; open a part for its drawing and full specifications.

Decision per case: a single station under 20 families doing presence and geometry checks takes the smart camera. Cracks under 0.3 mm, 20-40 families, or audit image storage takes the PC with an area scan camera. Start on the PC path if remanufacturing is new to the plant, because you will re-teach often in the first quarter. Browse smart cameras for the sealed option, or the camera finder for the PC path.

When does vision fail to qualify a core?

Vision qualifies only what light can see on an external surface: fatigue, hardness, internal cracks and subsurface flaws need dye penetrant, magnetic particle or ultrasonic testing, and vision feeds those stations rather than replacing them.

Four honest limits. Fatigue and hardness leave no visible signature — no camera setting finds them. Deformable cores such as rubber bellows never present the same silhouette twice; sort them on tolerant feature bands like perimeter and area, not exact match. Two cores with identical geometry but different alloys are indistinguishable in 2D, so mark them at teardown or carry them in keyed totes and let barcode to part verification for similar assemblies confirm identity. Heavily blackened parts return no contrast at all until cleaned, which is a wash problem, not a vision problem.

The rule to apply: if the evidence for reuse is not visible light on an external surface, vision routes the core to the instrument that can see it.

What should you check before ordering the cameras?

Two days of bench work on real washed cores settles all eight checks below — feature spread, pixel budget, lens coverage, nest heights, light recipes, exposure, cycle budget and traceability — before any purchase order is cut.

• Wash and photograph 20 cores per family, worst-case wear included, and measure the two identification features on each; the spread sets the tolerance bands.
• Compute object pixels from your largest envelope; confirm the smallest reject feature spans at least 3 pixels, or 10 if you measure it.
• Check the lens covers your sensor format and resolution class before anything else is decided.
• Fix one nest height per family and note the height spread the depth of field must swallow.
• Trial dark field on one cracked gasket and a dome on one coupling before writing the recipe list.
• Set exposure against your real belt speed; a 100 µs strobe pulse covers 200 mm/s.
• Budget the cycle at two-thirds mechanics, one-third vision, and confirm the handler holds it.
• Decide where every image and decision is stored before the first core crosses the camera.

Then start in the camera step of the configurator, or read plan your first vision inspection station if this cell is your first. Whatever the bench work leaves open, take it to the contact page with the core photos attached.