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Artificial intelligence moves into long-term planning for composite manufacturing

At CAMX 2026, Plataine is introducing new AI Agents capable of simulating production capacity, demand and resources months or years ahead, assessing the impact of autoclaves, tooling, machines and workforce before new investments are made

Plataine is extending artificial intelligence from day-to-day production management into long-term industrial planning. At CAMX 2026, taking place in Atlanta from September 22 to 24, the company has introduced new AI Agents for Long-Term Production Planning, designed to simulate future factory performance before manufacturers make production commitments or major investments.

The technology extends Plataine’s AI Agents beyond short-term scheduling. Manufacturers can build and compare scenarios involving demand, production capacity, machines, tooling and moulds, workforce, materials, shifts and process dependencies, assessing their impact across the entire production environment.

The aim is to address one of the key challenges in advanced manufacturing: determining whether adding a new machine, autoclave, shift or tooling will actually increase overall capacity. Removing one bottleneck can simply move the constraint to another stage of the manufacturing process.

The AI Agents can simulate these situations using real factory constraints and compare different strategies before implementation. Applications include evaluating the ability to support programme ramp-ups, identifying future bottlenecks, assessing additional production lines and determining whether existing resources can support new contracts. 

This approach is particularly relevant to composite and aerospace manufacturing, where resources such as autoclaves, moulds and tooling can involve significant capital expenditure and long lead times. Long-term planning can therefore be connected with daily production scheduling to provide a more complete view of future factory requirements.

According to Plataine, moving from traditional spreadsheet-based planning towards AI-powered simulation can help manufacturers understand in advance where additional capacity should be invested and what impact it will actually have on production, extending artificial intelligence into strategic industrial and investment decisions.

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