Characteristics
Defined by: PLC (Programmable Logic Controller)
- Invented in 1969
- Early adopters: Germany and Japan
- Late adopter: United States (late 1980s)
Point-to-Point (P2P) Approach
The Industry 3.0 approach involves creating point-to-point (P2P) connections between layers of software and hardware, such as:
- PLC to HMI or OPC server
- HMI to SCADA
- PLC to SCADA
- SCADA to MES
- MES to ERP
- ERP to the cloud
This is the traditional automation and integration work, focused on solutions. See Technology vs Solution Driven Architecture. It doesn’t use the modern Smart Factory Architecture and the Unified Namespace (UNS).
Often talked about in videos’ by Walker Reynolds and in industry sources. Many marketing texts write they are doing industry 4.0 stuff, but meanwhile they are doing 3.0 stuff.
Walker Reynolds
Deterministic integrations are dead (single function, peer to peer only)
Solution-Centered Method
This method requires in-depth knowledge of each specific solution (e.g., ControlLogix tags, Siemens tags, Modicon).
Warning
It doesn’t scale well for IIoT or Industry 4.0 because it results in inflexible, siloed systems. Integrating non-partner products involves significant labor and time, limiting adaptability and innovation.
Historical Context
Walker Reynolds
“Actually, in the United States, we really didn’t even start doing it until the late ’80s, which is the reason we had to offshore jobs.”
The delay in adopting PLCs and automation in the US led to significant economic consequences, including offshoring of manufacturing jobs.
Limitations
- Scalability Issues: Doesn’t scale well for modern manufacturing needs.
- Integration Challenges: Difficult and time-consuming to integrate new technologies.
- Data Silos: Information trapped in separate systems, hindering holistic analysis.
- Inflexible Manufacturing: Unable to quickly adapt to market changes or new opportunities.
Contrast with Industry 4.0
Industry 3.0 practices differ from Industry 4.0 in several key ways:
- Automation vs Intelligence: Focus on automation alone rather than intelligent, data-driven systems.
- Reactive vs Predictive: Reacting to issues instead of predicting and preventing them.
- Manual vs Automated Decision Making: Relying on human decision-making for processes that could be automated.
- Siloed vs Integrated Data: Lack of a unified namespace or similar data integration strategy.
Walker Reynolds
“If you’re an industry 3.0 company, that is you are still focused on automation, you’re dead. If you haven’t jumped the chasm yet, you’re dead.”
Caution
Companies still operating in the Industry 3.0 paradigm risk falling behind competitors who have embraced Industry 4.0 technologies and strategies.