Industry 4.0 explained simply
Imagine a factory in which machines, products and people communicate digitally with each other permanently – without breaks, around the clock. In this setting, a product (e.g. with RFID) already knows at the start of production which steps it will go through. Machines exchange sensor data, make their own decisions and intelligently control processes. That is Industry 4.0: the fourth industrial revolution, centred on connected, smart manufacturing – more efficient, flexible, resource-saving and individual. Products become “smart”, the factory becomes a Smart FactoryIntelligent factory with fully networked machines and systems that self-organize and produce autonomously., in which data and intelligence go hand in hand.
Background information
Industry 4.0 is an originally German future project, first presented at the Hannover Fair in 2011. Sponsors included, among others, Plattform Industrie 4.0, BMBF and BMWi, as well as the working group led by Henning Kagermann, Wolf Dieter Lukas and Wolfgang Wahlster. It forms the basis of a fourth industrial revolution, building on the previous automation (Industry 3.0) and now enabling seamlessly networked production with Cyber-Physical Systems (CPS), IIoTIIoT is the internet-based networking of industrial machines, systems, and devices for data collection and process optimization., cloud computingProvision of computing power, storage space and software via the internet without own hardware. and artificial intelligence.
At its core, Industry 4.0 is based on four design principles: networking, information transparency, technical assistance and decentralised decisions. This means: sensors, machines, products and people are connected with each other; digital twins virtually replicate the real world; assistance systems support decisions; and CPS make local autonomous decisions, while only exceptions are forwarded centrally. The Smart Factory as the target model allows individualised production with high efficiency, even in batch size 1.
This transformation brings with it a wide range of advantages: production cycles shorten, maintenance is automated (e.g. predictive maintenancePredictive maintenance using data analysis and AI to forecast machine failures before they occur.), and flexibility and quality increase – while costs are reduced. Big DataHuge amounts of data that are too large and complex for conventional data processing software. is transformed into Smart Data in real time, turning data into value creation.
Big Data & Smart Data: From data flood to real-time insights
With the introduction of Industry 4.0, the volume of data in production environments increases exponentially. Sensors, machines, ERPEnterprise Resource Planning - software for integrated management of all business processes and resources. systems, Manufacturing Execution Systems (MESManufacturing Execution System - software for real-time control and monitoring of entire production.) and IoT platforms continuously generate large amounts of data – often unstructured, in real time and at high frequency. These data volumes are referred to as Big Data. However, on their own they bring no added value, as long as they are not structured, analysed and converted into context-related information.
This is where Smart Data comes into play. The goal is to generate specifically usable insights from the data flood – e.g. to optimise production processes, detect faults early or improve product quality. This is achieved through the use of modern analysis methods such as machine learningMachine Learning - algorithms for autonomous pattern recognition in production data for automatic process optimization without manual programming., complex event processing and semantic data models. Companies use edge and cloud solutions to filter and aggregate data and transfer it to dashboards or decision algorithms. As a result, real-time insights are created, enabling predictive and dynamic production control. Data becomes an active decision-making basis instead of a passive by-product – the core of Industry 4.0.
Use cases & success stories from practice
Predictive maintenance in the automotive industry
A classic among Industry 4.0 applications: in modern car factories, machines are equipped with vibration, temperature or pressure sensors. Using AI-based algorithms, patterns are identified that indicate impending failures. This allows maintenance to be planned in advance, downtime minimised and unplanned stoppages avoided.
Batch size 1 in discrete manufacturing
Customer-specific products in series quality – a wish that becomes reality with Industry 4.0. Manufacturers in the furniture and electronics industries produce individual configurations without losing the efficiency of mass production. This is made possible by digitally controlled, flexible production systems with connected order control and automated quality inspection.
Digital twins in process industry
Chemical and pharmaceutical companies use digital twins to virtually replicate entire plants or products. These models enable simulations, process optimisations and quality assurance – even before physical changes are implemented. This saves time, costs and reduces risks in highly regulated industries.
Smart logistics in intralogistics
Connected conveyor systems, autonomous vehicles (AGVs) and real-time data flows ensure transparent material flows. Intelligent systems detect delays or bottlenecks early and automatically adjust logistics. The result: less downtime, higher throughput, lower storage costs.
Further information and links
- CoreTigo: Comprehensive glossary on Industry 4.0 – https://www.coretigo.com/de/glossar/industrie-4-0-i4-0/
- DIN / BMBF: What is Industry 4.0? Definition & objectives – https://www.din.de/de/forschung-und-innovation/themen/industrie4-0/was-ist-industrie-4-0
- KUKA AG – Glossary of terms on Smart Factory and Big Data – https://www.kuka.com/de-de/future-production/industrie-4-0/industrie-4-0-glossary
- Technavigator Digitalisation 4.0: Definition and benefits of Industry 4.0 https://technavigator.de/digitalisierung/grundlagen/digitalisierung-4-0/