Scale to reality: contract manufacturing goes big with automation

Automation is moving from the pilot bench to the plant floor. In a candid interview, Flex executive Rodrigo DallOglio explains how contract manufacturers are turning pilots into large scale production, deploying a mix of collaborative robots, autonomous mobile robots, and newer forms of physical AI to manage growing product complexity.

Manufacturers face pressure to lift productivity, quality, and resilience, and are treating automation as a core capability rather than a last resort. DallOglio notes the move is less about a flashy demo and more about steady, repeatable gains across multiple SKUs and demand swings. The contract manufacturing sector must deliver shorter cycle times and higher throughput as product variants proliferate, without sacrificing quality. The practical takeaway is that automation is an operating model decision, not a one time investment.

Flex is pursuing scale by combining human and machine workstreams in a structured, repeatable way. Collaborative robots handle repetitive, precision driven tasks, while autonomous mobile robots navigate busy factory floors to shuttle parts and materials. Emerging physical AI is being explored to optimize line setups, detect anomalies in real time, and adjust workflows on the fly. Deployment data shows that when these elements are standardized and integrated with existing plant systems, gains compound as lines are replicated across shifts and product families.

To make scale stick, integration is non negotiable. The article emphasizes that automation must talk to the plant’s software backbone, namely manufacturing execution systems and enterprise resource planning, with clear data streams for monitoring cycle times and throughput. Without reliable data plumbing, even the smartest robot cannot produce predictable outcomes. The message for plant managers and CFOs is clear: the ROI hinges on disciplined integration, not just clever hardware. The case for automation becomes compelling when cycle times shrink and throughput climbs in a way that is auditable and repeatable across lines.

The story also presents a realistic view of what automation can and cannot do. The old trope of plug and play is almost never true on a real factory floor. Two weeks of debugging is a more accurate predictor of time to value than a guaranteed quick start. That reality is not a deterrent, but a reminder that successful scaling requires planning for debugging, calibration, and operator training as the baseline cost of speed.

An important practical note for skilled trades. Automation typically augments line operators and quality inspectors, while installation and ongoing maintenance lean on automation technicians and systems integrators. In contract manufacturing, where lines run high mix, low to moderate volume, the dynamic is to offload repetitive, error-prone tasks to robots while keeping skilled staff focused on setup, inspection, and changeovers. The balance matters: too much automation without human in the loop can dull flexibility, while underinvesting in integration and maintenance can erode uptime and data fidelity.

Looking ahead, the industry expects continued broadening of the automation toolkit. Physical AI could sharpen line sensing and decision making, enabling faster response to process drift and defects. The challenge will be keeping the cost of scaling aligned with the benefits of standardization across products and sites. If Flex’s approach is any guide, the path to scale is paved not by a heroic pilot, but by disciplined replication, solid integration, and a clear, measurable operational metric mindset that keeps the numbers honest.