When Glazing Experts Aren't Robot Programmers: Bridging the Skills Gap in Sanitaryware Glazing

There is a problem that most robotized sanitaryware plants are dealing with today. When a factory installs a robotic glazing system, the expectation is straightforward - the robot will perform, quality will improve, and production will become more consistent. What is not planned for, in most cases, is who will actually make the robot perform well.

And that question leads to a gap that is costing plants more than they realise.

The Robot Programmer Who Does Not Understand Glazing

The people who truly understand glazing in a sanitaryware plant are the experienced spray applicators, the process engineers, the quality supervisors who have spent years on the factory. They know exactly what a good glaze thickness and surface should look like. They understand the right gun settings including distance between the product and the gun, the correct spray angle on each area of the pieces like rim, the tap hole area, the sump area, the trapway and bowl, the places where the gun needs to slow down and the places where it can move faster.

But they cannot programme a robot.

On the other side, the robot technician who can write and edit programmes ? he understands coordinate systems, motion paths, and robot syntax. What he does not understand is why a particular section of a one-piece WC needs a slower traversal speed, or why the gun angle on the external body needs to change near the footprint area. The robot programme that comes out of this gap exactly.

The Common Misconception About Robot Programming

Most factory personnel believe that robot programming is extremely complex, something that only highly specialised engineers can understand or do. That belief is actually not accurate. When you look into it carefully, robot programming, especially for a dedicated application like glazing, is not inherently difficult. The barrier is more about familiarity and access than about technical complexity.

But because this misconception exists, glazing experts stay away from the programming process entirely. They treat it as somebody else's domain. And as a result, valuable glazing knowledge accumulated over years of hands-on experience never makes it into the robot programme.

What Actually Happens on the Glazing Department Shopfloor

When a robot is running on a programme that is not optimised for the product geometry, the glazing team does not stop the line to fix the programme. They work around it.

If the robot is spraying too much glaze in one area  because the spray path is too slow or the gun distance is too close, an operator will sponge the excess after spraying. If a particular section is coming out thin because the programme misses it or the gun angle is wrong, the operator will apply glaze manually by brush before the piece goes into the robot. This kind of manual intervention happens regularly, and most plants accept it as normal.

What many do not account for is the time this takes, and what it does to productivity. Every piece that needs sponging or manual brush application is a piece that requires extra handling. In a plant running three shifts over 24 hours, this adds up significantly.

There is also a surface quality issue. Glaze applied by brush does not behave exactly like robot-sprayed glaze. The brush strokes can show on the fired surface. To reduce this, operators apply compressed air at around 6 bar over the brushed areas to smooth out the strokes immediately after brushing the piece with glaze. This is an additional step in the process, one that exists purely because the robot programme was not doing the job correctly in the first place.

The Auto-Learning Programme: A Compromise That Looks Like a Solution

In most sanitaryware plants, when a new product is introduced on the glazing line, the common practice is to first run it on a similar existing model's programme to see how it performs. Then, before the product goes into full production, an auto-learning programme is created by teaching the robot using human hand movement. A trained operator physically guides the robot through the spray path, and the robot records that movement.

This approach is often presented as an efficient solution, but in practice has a fundamental problem.

The person doing the robot teaching is not the skilled glazer. The skilled glazer knows exactly how to spray that product, the speed, the angle, the distance, the pauses near complex geometry. But he does not know how to guide a robot. The person who can guide the robot (the robot technician or a trained operator) does not have that deep glazing instinct.

So what happens during the teaching process? The person guiding the robot is careful. He is slow. In complex curved areas, near edges and rims, he over-stays or under-stays because he is not confident. He is thinking about the robot, not about the glazing. The programme that results from this captures hesitation and uncertainty, not expertise. And that programme then runs in production, consistently replicating those same imperfections across every shift, every day, until someone decides to address it.

Additionally, glazing a complex sanitaryware product involves coordinating the gun movement with the rotation of the product. The product is rotating on a turntable while the robot arm moves around it. An experienced glazer manages this coordination naturally, instinctively. Replicating that coordination accurately during manual robot teaching is genuinely difficult and when it is not done well, the resulting programme is inefficient from the start.

The Defect That Keeps Coming Back

When an auto-learned programme has a weakness, a section where the glaze is consistently thin, or an area where overspray builds up, the defect is systematic. Unlike manual glazing, where defects vary randomly by operator and shift, robot defects appear in exactly the same place on every piece.

The response in most plants is to manage the defect rather than fix the programme. Operators are given feedback. Pieces are corrected manually before and after spraying. But a batch of work-in-progress pieces with the same defect has already moved down the kiln. That is rework, and it is a recurring cost.

Where Offline Programming Changes This

The offline programming tool, 3D-ProSim, developed exclusively for sanitary robotic glazing, takes a completely different approach. Instead of teaching the robot by hand on the shopfloor, the programme is developed in a digital environment using the 3D model of the sanitaryware workpiece. The glazing station & cabin, robot, spray guns, turntable, are all simulated virtually. The spray paths are built based on the actual workpiece geometry.

This changes where the glazing knowledge can be applied. In the 3D-ProSim environment. Production continues while the programme is being developed and refined.

An optimal trajectory is automatically generated for the robot, based on the product's geometry, which removes the burden of manually calculating every robot coordinate. The glazing expert contributes what he actually knows (the application knowledge) and 3D-Prosim translates that into an executable robot programme.

As the programme is built correctly from the beginning, the need for manual intervention, sponging, brush application, and air smoothing is significantly reduced. The final product comes out of the robot glazed properly, not glazed approximately.

A Practical Shift for the Plant

For a sanitaryware manufacturer, the value of this approach is not just in the programme quality. It is in how it changes the relationship between glazing knowledge and robot programming. The glazing expert is no longer standing on the side watching someone else make decisions about the programme.

The robot technician's role becomes more focused and effective as well, he is working with a well-defined programme developed from product geometry, not trying to interpret hand-taught movements and guess at what the glazing team actually needs.

The misconception that robot programming is too complex for shopfloor personnel to engage with is the barrier that a tool like 3D-ProSim, specifically built for sanitary ware glazing, addresses most directly, not by making the programming invisible, but by making it accessible to the people who actually understand what good glazing looks like.

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