Trelleborg advancing use of AI in design, production operations

Trelleborg, Sweden – Trelleborg Group is progressing its use of artificial intelligence (AI) to improve production processes and products across various businesses.

Trelleborg Sealing Solutions (TSS), for one, is “well on the road” to effectively using AI in automated inspection, said TSS president Gordon Micallef 7 May.

According to the company leader, conventional inspection machines employ an established detection technology to monitor the surface-quality of components.

These systems, he said, can then identify lighter or darker defects when compared to the general area being inspected.

However, Micallef pointed out, there are some sealing geometries and parts where traditional detection methods are not effective.

“Currently, Trelleborg has a project coming close to industrialisation addressing these challenges,” reported the TSS president.

The process involves taking pictures of the parts produced and classifying them as good or bad, explained the senior executive.

There can, he said, be "a variety of defect types and sizes, and the machine is taught which parts are correct and which are defective.

"The more you teach the machine, the better it becomes at recognising the parts that do not meet a specification."

Group-wide, Trelleborg said it is using AI in other ways, including a process that recommends optimum compounds for automotive brake shims to design engineers.

Furthermore, the Swedish polymer group has lined up projects to improve rubber mixing and energy consumption using AI.

With the “common thread” on all AI applications being data, Micallef said a minimum of one year’s data is needed for high-volume processes.

“It is vital that we are collecting process data that we will require for future AI projects now,” he said – noting that the group is working with machine suppliers on data-capture.

And, while newer machines provide data as an in-built process, Trelleborg is using additional sensors on older machinery to collect data from the devices.

“We have developed ActiviTEE, a digital software for monitoring overall equipment effectiveness (OEE), to collect this information,” Micallef explained.

AI also plays a role in Trelleborg’s efforts to increase the sustainability and circularity of manufacturing.

Sensors, for instance, gather data on the amount of energy used in a process and combine it with data from production monitoring.

Comparing consumption with activity and cost, an energy usage profile will optimise the output of a manufacturing machine and minimise the energy used, said Micallef.

In the longer term, “AI could be used to estimate the carbon footprint of components during manufacturing,” the Trelleborg leader continued.

“By having a clear understanding of the environmental impact, we can potentially look for sustainable alternatives or improve processes to reduce emissions,” he added.

“AI presents us with so many prospects for the future improvement and enhancement of our manufacturing processes that we must try and benefit from every opportunity the technology gives us,” Micallef concluded.