A bespoke robotic handling cell has been retrofitted to a DMG Mori five-axis vertical machining centre at the Redditch factory of Optimal Manufacturing, helping the subcontract specialist automate the production of high-precision prismatic components and achieve reliable 24/7 unattended machining. Supplied by Whitehouse Machine Tools, the Tezmaksan CubeBOX robotic handling cell is unusual in that it exchanges components mounted in vices on pallets, rather than handling billets, castings or forgings directly.

Joint owners and directors Will Cooper and Tom Slimm selected this approach because many parts require tolerances of less than 10 microns. They believed handling individual components would not provide the repeatability needed, particularly where second operations were involved. Instead, workpieces are fixtured in vices mounted on zero-point pallets and loaded into a DMG Mori CMX 70 U five-axis machining centre.

Tezmaksan modified its CubeBOX Blues DR MAX system so that the three storage shelves, each holding four vice-mounted parts, could slide horizontally towards the robot and back again. This capability allows the 70 kg payload robot to safely access the lower shelves and handle the fixtured workpieces efficiently.

Commissioned in August 2025, the cell quickly proved its value when Optimal secured a large stainless-steel valve manifold order for an oil and gas customer. The company ran the system continuously for three months.

“It was ideal for automation,” states Cooper. “We ran the cell 24/7 for three months, unattended every night, allowing us to produce the parts economically while enhancing our reputation for short lead-time deliveries.”

Slimm adds: “With some machining cycles lasting well in excess of two hours, and our ability to gain 14 hours’ production overnight virtually for free, this type of easy-to-use automation is a big asset for any manufacturing organisation.”

More information www.wmtcnc.com

Instro AI Solutions has announced the results of its collaborative generative AI trials with AMRC Cymru, demonstrating measurable operational improvements and clear commercial impact for participating UK engineering firms, including cutting response times by more than two thirds.

Over the past year, Instro AI worked with AMRC Cymru, part of the University of Sheffield Advanced Manufacturing Research Centre, to deliver structured proof-of-value trials with engineering companies. Each programme was designed around defined business outcomes, with results reviewed alongside AMRC Cymru to validate performance.

Measured results included Colchester Machine Tool Solutions achieving 67.3% faster technical query response times, reducing average response times from 5.5 minutes to 1.8 minutes. Elsewhere, sliding-head lathe manufacturer Star Micronics recorded 44.6% faster engineering decision-making during technical support tasks, with engineers using the system more than 1200 times to diagnose alarm codes and locate technical information.

Instro AI delivers a sector-customisable generative AI platform designed to transform how knowledge is accessed and applied across organisations by staff, partners and customers. The system automatically ingests complex documentation including manuals, technical documents, training materials, compliance information and customer records, providing instant, accurate and context-aware responses to operational and commercial questions.

A key finding across all trial participants was that the greatest challenge was not the AI technology itself, but fragmented manufacturing data spread across documents, systems and service records.

Pritesh Patel, industrial digitalisation technical lead at AMRC Cymru, says the trials demonstrated that the biggest hurdle for manufacturers is often legacy data rather than AI adoption itself. Phil Sanders (pictured), commercial director at Instro AI Solutions, adds: “These outcomes demonstrate how generative AI is moving beyond experimentation and delivering measurable operational improvements across engineering support, enquiry handling and technical decision making for organisations of all sizes.”

More information www.instro.ai