What are the key factors in choosing multi-factory automation?

Author:
Marc Fuentes
VP Commercial Growth

The best factory automation solutions for multi-plant operations share six traits: a standardized control architecture, visibility from the line to the enterprise, modular designs that replicate cleanly, readiness for industrial AI, secure governance of operational technology (OT), and one partner across the full lifecycle. Enterprise manufacturers that select on these factors turn one successful line into a repeatable template for the whole network. Plant-by-plant buying tends to leave a patchwork of PLC brands, custom code, and disconnected MES and SCADA layers that slows every rollout after the first.

Why does multi-plant automation need its own evaluation?

Enterprise leaders already see the upside. In Deloitte’s 2025 Smart Manufacturing Survey, 92% of large manufacturers named smart manufacturing the main driver of competitiveness over the next three years, and respondents reported 10% to 20% gains in production output. Scaling those industrial automation gains across a network is the hard part. McKinsey research found at least 70% of manufacturers stuck in pilot purgatory, with no clear approach for scaling innovations across plants. The gap between a strong pilot and a strong network is usually decided during selection.

Key takeaways

Which factors matter most when evaluating factory automation solutions?

1. Does the solution standardize control across every plant?

Start with the control layer. A global standard for PLC platforms, HMI templates, safety systems, and code libraries lets engineers move between sites and troubleshoot faster. Local needs, such as regional power specifications or product variants, fit inside a documented framework. McKinsey’s review of the Global Lighthouse Network notes that leading sites actively balance speed with standardization and autonomy with visibility. Your plant-wide control systems should make those trade-offs explicit.

2. Can leaders see performance from the line to the enterprise?

Visibility depends on a shared data model. Ask how the enterprise automation software connects machines, industrial IoT sensors, SCADA, and manufacturing execution systems into one view, and whether OEE, scrap, and downtime are calculated the same way everywhere. Deloitte reports that 57% of manufacturers already use cloud computing at the facility or network level. That connectivity pays off when every plant speaks the same data language, a core goal of a digital factory approach.

3. Will the design replicate without re-engineering?

Modular cells and platforms lower the cost of plant two, three, and ten. Look for digital twins that validate layouts, cycle times, and robot paths virtually before hardware ships. The volume of industrial robotics to standardize keeps climbing. The International Federation of Robotics counted 542,000 industrial robots installed in 2024 and 4.66 million in operation worldwide.

4. Is the architecture ready for industrial AI?

AI manufacturing use cases need clean, contextualized data and the right sensors. Deloitte found that 41% of manufacturers will prioritize factory automation hardware and 28% will prioritize vision systems over the next 24 months. Machine vision, predictive maintenance, and physical AI all rely on that foundation. McKinsey research shows predictive maintenance typically cuts machine downtime by 30% to 50% and extends machine life by 20% to 40%. The World Economic Forum’s Global Lighthouse Network now spans 238 sites, and generative AI accounted for 23% of its top solutions in 2025.

5. How is operational technology secured and governed?

Every connected plant adds attack surface. In Deloitte’s cyber research, 40% of respondents reported six to 10 cybersecurity breaches in the past year. Evaluate network segmentation, access control, patching standards, and change management that apply the same way at every site, so a fix in one plant protects them all.

6. Does one partner support the full factory automation lifecycle?

Multi-plant programs run for years. Roughly 70% of manufacturers now outsource key OT, IT, analytics, and cybersecurity roles to third parties, according to Deloitte. Favor a partner that covers engineering, simulation, build, installation, and post-automation support, so lessons from plant one carry into plant ten.

How should enterprise teams run the evaluation?

Build a reference line at one plant, document it as the standard, and measure results with the KPIs you plan to use network-wide. Then scale in waves, feeding each site’s lessons back into the template. Manufacturers that follow this rhythm spend less time re-engineering and more time improving throughput, quality, and uptime across their manufacturing automation footprint.

Explore the possibilities

Planning to scale automation across multiple plants? Book a discovery call to learn how Eclipse Automation supports standardized, scalable factory automation solutions for multi-plant operations.