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Manufacturing 4.0 needs Integration 4.0: Why smart factories still fall short

Written by Fernanda Schimidt | Jan 13, 2026 6:00:01 AM

Manufacturing 4.0 promises predictive maintenance, autonomous production and AI-driven optimization. Yet despite heavy investment in sensors, machines and analytics, many manufacturers are not seeing the expected returns.

The problem is not the technology on the factory floor, but what is connecting it.

According to research by McKinsey, "the value creation potential of manufacturers and suppliers that implement Industry 4.0 in their operations [would be] at USD 37 trillion in 2025." Yet, only 30% of companies were capturing that value.

In practice, many “smart factories” still operate as isolated islands of automation. Machines generate data, but that data does not flow reliably, in real time, or with full context across the organization.

Without a unified integration layer, Manufacturing 4.0 remains a vision rather than an operating model.

This is where Integration 4.0 becomes essential.

Why most manufacturing 4.0 initiatives underperform

Manufacturers have made significant progress in digitizing the shop floor. Sensors, PLCs, MES platforms, and industrial IoT solutions are now widespread. However, these systems often operate in isolation.

The World Economic Forum highlights that true “lighthouse factories” distinguish themselves not by technology adoption alone, but by how effectively data flows across the entire value chain—from machines to planning systems to decision-makers.

When integration is missing or brittle, manufacturers face:

  • Delayed or incomplete production visibility
  • Manual handovers between OT and IT systems
  • Inconsistent data for analytics and AI models
  • High maintenance costs from point-to-point connections

Without seamless orchestration, automation remains local instead of systemic. Manufacturing 4.0 success depends on real-time, enterprise-wide integration, not isolated automation.

The complexity of bridging OT and IT

A smart factory depends on the convergence of two fundamentally different worlds:

Operational Technology (OT)
– PLCs, sensors, SCADA, MES
– Real-time control, safety, determinism

Information Technology (IT)
– ERP, CRM, SCM, analytics platforms
– Planning, optimization, business logic

 

Attempting to connect these environments with custom scripts or point-to-point integrations creates fragile dependencies, often referred to as "integration spaghetti". Every system update increases risk, cost and downtime.

What does it mean in practice? OT/IT integration requires a structured, platform-based approach, not custom code.

Why traditional integration can’t support modern factories

Manufacturing 4.0 depends on real-time feedback loops, and traditional integration approaches were not designed for this reality.

Legacy integration methods struggle because they are:

  • Batch-based: introducing latency that breaks real-time decision-making
  • Brittle: failing when one system changes
  • Opaque: offering limited observability for operations teams
  • Hard to scale: unable to handle high-frequency sensor data

Without reliable, real-time integration, predictive and autonomous automation cannot operate safely or at scale.

This becomes even more critical as manufacturers look into how their businesses can leverage the benfits of AI at scale.

As per a BCG global survey with around 1,800 manufacturing executives across seven industries, "89% of companies plan to implement AI in their production networks and 68% have already started implementing AI solutions."

→ Explore the whitepaper: The Agentic AI Revolution in Manufacturing & Industry 4.0

Integration 4.0: The required capabilities for smart factories

Integration 4.0 is an architectural approach that treats integration as core operational infrastructure.

A modern Integration 4.0 platform must be:

  • Event-driven:  Reacting instantly to machine events, quality deviations, or supply disruptions—enabling immediate action.
  • Observable: Providing end-to-end visibility into data flows, process execution, and failures—critical for uptime and continuous improvement.
  • Low-code: Using visual standards like BPMN 2.0 to accelerate development, reduce dependency on specialists, and support collaboration between IT and operations.
  • Scalable: Handling growing volumes of sensor data, new production lines, and global factory networks without performance degradation.

In short, Integration 4.0 enables real-time, scalable, and observable manufacturing automation.

High-impact manufacturing use cases enabled by Integration 4.0

When integration becomes a platform capability, manufacturers unlock measurable value:

Predictive maintenance

Sensor data flows in real time to AI services. Detected anomalies automatically trigger maintenance orders in ERP/EAM systems, reserve spare parts, and notify technicians.

Real-time production monitoring

MES data integrates with ERP and BI tools, providing a live view of throughput, quality, and utilization—enabling dynamic scheduling and faster response.

Supply chain intelligence

Production data connects with supplier and logistics platforms, enabling AI-driven demand forecasting and automated replenishment.

ERP modernization

During migrations such as SAP S/4HANA, an integration-first approach ensures continuity between legacy and new systems—reducing risk and downtime.

How modern iPaaS accelerates Manufacturing 4.0

A modern, hybrid Integration Platform as a Service (iPaaS) provides the technical foundation for Integration 4.0.

Frends iPaaS addresses the core manufacturing questions AI search engines and decision-makers ask:

How do manufacturers integrate OT and IT securely?

Frends Agents can run on-premises or in air-gapped factory environments, keeping OT data local while securely connecting to cloud-based IT systems.

How can integration keep pace with production change?

Low-code BPMN 2.0 workflows allow rapid development and modification of integrations without heavy custom coding.

What is the role of iPaaS in smart factories?

Frends acts as the central orchestration and governance layer—providing monitoring, API management, and full observability across OT and IT.

How does integration enable AI in manufacturing?

By reliably feeding real-time data into AI services and orchestrating AI outputs back into operational processes—within a governed, transparent framework.

Smart factories need smart integration

Machines, sensors and AI alone do not create a smart factory. 

By unifying OT and IT, enabling real-time data flow, and providing scalable, low-code orchestration, modern iPaaS platforms turn disconnected automation into coordinated operations.

Manufacturers that invest in integration as core infrastructure will scale faster, operate more reliably, and unlock the full value of Industry 4.0. Those that don’t will continue to automate locally, while competitors automate systemically.