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RAMI 4.0 (Reference Architectural Model Industry 4.0): Explained with example

April 14, 2021December 8, 2023 by Kaviraju

What is RAMI 4.0? How it relates to Industry 4.0?

The RAMI 4.0, Reference Architecture Model Industrie 4.0 (Industry 4.0), was developed by the German Electrical and Electronic Manufacturers’ Association (ZVEI) to support Industry 4.0 initiatives, which are gaining broad acceptance throughout the world. Industry 4.0 (also termed Industrie 4.0) is a holistic view of manufacturing enterprises, started in Germany, with many worldwide cooperative efforts including China, Japan, and India. Industry 4.0 concepts, structure, and methods are being adopted worldwide to modernize manufacturing.

RAMI 4.0, or Reference Architectural Model Industry 4.0, is a three-dimensional map showing how to approach the issue of an Industry 4.0 in a systematic and structured way. RAMI 4.0 is a unified model for all the components that ensures all the participants involved in an Industry 4.0 ecosystem to share data & information efficiently and effectively. RAMI 4.0 maps all the players of the connected industry to three axes of definition as listed below:

  • Architecture Layers: This layer contains sub-layers like Business, Functional, Information, Communication, Integration and Asset.
  • Life Cycle value stream: This layer contains sub-layers like Development, Production and Maintenance usage.
  • Hierarchy levels: This layer contains below sub-layers like Product, Field, device, Control device, Station, Work centers, Enterprise and Connected world.

Lifecycle Value Stream: The lifecycle value stream axis is divided into Type and Instance. The Type is divided into Development and Maintenance/Usage, while the Instance is divided into Production and Maintenance/Usage. A type represents the initial idea of the product development, while each manufactured product represents an instance of that type. The value stream in the totally digitized production can be viewed in conjunction with value-adding processes, since it enables linking of purchasing, production planning, logistics, quality, customers and suppliers. In simple words, if a product is in a development state, then we refer to it as a “Type”. Once it moves into production, then it becomes an “Instance”. Whenever a product is redesigned or a new feature is being added to it, then again, its state turns to “Type”.

Hierarchy Levels: The Industry 4.0 architecture at hierarchical level shows a functional assignment of components. This axis within an enterprise or factory follows the IEC 62264 and IEC 61512 standards. The level over and below the IEC standards area represents steps further and describes also groups of factories, collaboration within external engineering firms, component suppliers and customers. Therefore, the hierarchy levels are: product, field device, control device, station, work center, enterprise, and connected world.

Architecture Layers: The architecture layer includes sub-layers as mentioned above. This layer enables the development of Industry 4.0 software solutions in a consistent way so that different and mutually dependent manufacturing operations are interconnected taking into account the physical and the digital world.

RAMI 4.0 breaks down complex processes into package, making it easy understandable, and includes by design data privacy & IT security. It addresses and answers all the problematics about semantics, identification, functions, communication standards, internationalization and partnering for the smart factory.

With RAMI 4.0 architecture, the factory is not an overlay of layers but a network of interaction between smart products and the connected world. Functions are distributed to all participants allowing more flexible operations between systems and machines. To connect physical thing to the Industry 4.0 world, the RAMI 4.0 provides an administration shell which comes to be placed over the system; the system being a sensor, a machine, a unit or a plant. Also, every asset having their own administration shell, several assets can then form a unit with a common administration shell for higher level communication and management. Once connected to the physical system, the shell serves as the network’s standardized communication interface to share all data and information about the asset.

As described, RAMI 4.0 function is to transform physical objects into their interoperable digital twin. Bringing the industrial world in the IoT, RAMI 4.0 is the root of the Industry 4.0 revolution.

Example: Edge analytics solution architecture in the context of the RAMI 4.0 showing architecture layers.

Hierarchy Levels: The edge analytics solution architecture in the frame of RAMI 4.0 is applicable at component, machine or production process level. In this sense, it can be implemented in flexible smart systems and machines capable of interacting and communicating across the hierarchy levels through a network. The implementation of the architecture in a “Connected World” (i.e. connected factories with integrated edge analytics processes) would require its use by all of them in order to create synergies (e.g. between a factory and its supplier of raw-materials or maintenance spare parts).

Architecture Layers: Below figure shows the edge analytics solution architecture in the frame of the RAMI 4.0 architecture layers, which is self-explanatory.

Industry 4.0 technologies are developed to enable smart prediction systems to flexibly make decisions during the production process. In Industry 4.0; most of the operational decisions are made according to the experiences of supervisors. However; how to analyze the collected information and provide the insights and meaning to help the users to make better decisions is a crucial issue for the current prediction systems. Though data collection process is simple and easy to implement by using sensors and data acquisition softwares, without the data analysis, collected data is useless. It is necessary to calculate, store and analyze the data to make it meaningful and useful for Shopfloor operations. Using the big data analysis and cloud computing platforms, some of the important insights or upcoming events in the machines can be discovered. The development of the digital system and decision support system will transform the information into visualization which users can see and understand. The characteristics of Industry 4.0 ecosystem in the 21st century can be applied to smart prediction system as described in below table:

Characteristics of enabling technologies

Description

Internet of Things (IoT)

a) Ability to connect and manage machines / equipments
b) Sensor data collection from machines in real-time

Big data analytics

a) Allow real-time use of analytics tools for large amounts of data
b) Real-time decision-making support

Edge computing / Cloud computing

a) A model for managing, storing, and processing prediction system data on edge or in cloud
b) Real-time commands to machines based on data analysis results computed on edge or in cloud

System integration

a) Allow for different computer of machines to be linked together
b) Enabling actual communication and passing on of IoT data from machines to IT systems

You can relate each of the components shown in above diagram to the components in below diagram.

Lifecycle Value Stream: Taking predictive maintenance as the example for edge analytics implementation, the lifecycle value stream of predictive maintenance has both managerial and technical implications. As far as the managerial perspective is concerned, the type includes the idea as well as the development and validation of a predictive maintenance strategy. After successful validation, the new consulting service is released. Each instantiation of the predictive maintenance strategy to a specific production process or industry represents an instance of that type. As far as the technical perspective is concerned, the type includes the idea as well as the development and testing of a unified information system for predictive maintenance which sets the basis for serial production. Each instantiation of the predictive maintenance information system to a specific equipment, production process or industry, and to a specific legacy data system or installed sensor represents an instance of that type.

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