The Industry 4.0 revolution and the smart factory in process industry

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The Industry 4.0 revolution and the smart factory in process industry

Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. It includes Cyber-Physical Systems (CPS), the Internet of Things (IoT), Cloud and Edge Computing, and most recently Digital Twin and Cognitive Computing.

Industry 4.0 creates what has been called a “smart factory”. Within the modular structured smart factory, CPSs monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Manufacturing Processes can be represented by the Internet of Services, as the result of the convergence of IoT and CPS. CPS communicate and cooperate with each other and with humans in real time, and via Cloud Computing, both internal and cross-organizational services are offered and used by all participants.

Industry 5.0

The Industry 5.0, as described by the European Commission, complements the Industry 4.0 approach aiming to make the European industry sustainable, human-centric and resilient. Industry 5.0 brings benefits for both, workers (i.e., safe and beneficial working environment, respect of human rights, etc.) and industry (long-term competitiveness, capability to attract and retain talents, etc.). 

Elements pertinent to Industry 5.0 are already part of major Commission policy initiatives:

  • adopting a human-centric approach for digital technologies including artificial intelligence
  • up-skilling and re-skilling European workers, particularly digital skills
  • modern, resource-efficient and sustainable industries and transition to a circular economy
  • a globally competitive and world-leading industry, speeding up investment in research and innovation

Cognitive Digital Twin

According to what is described above, a relevant role is covered by the concept of Cognitive Digital Twin, a virtual representation that serves as the real-time digital counterpart of a physical object or process. The Digital Twin includes a range of services to do a set of operations and produces data describing the physical entities (human operator or machines) activities bringing a lot of benefits in the Process Industry (e.g., increase the productivity, support the decision-making operation, etc.). Many companies can communicate each other, as explained in the following, in order to simulate the process and predict its functionalities, facilitating the analysis phase of what is in place in the processes chain.

Data Space

Another recent concept directly connected with the digitalization of the European industry is the Data Space, a type of data ecosystem between trusted partners composed from all its participants (data providers, users and intermediaries), where each of whom apply the same high standards and rules to the storage and sharing of their data. Data sovereignty and trust are essential for the working of data spaces and the relationships between participants. To ensure these, the International Data Spaces Association (IDSA[5]), a founding member of the Gaia-X AISBL, has proposed a reference architecture model for participants.

Cognitive Automation Platform

The software required to implement data spaces runs on cloud/edge cloud infrastructures. In this complex interconnection recent advances in cloud and edge computing help to support the computation, data transfer and sharing, transforming data into information and knowledge. In the CAPRI project an innovative Cognitive Automation Platform (CAP) for Process Industry Digital Transformation has been developed and tested, encompassing methods and tools of the six Digital Transformation pathways (6P -> Product, Process, Platform, Performance, People, Partnership), engaging the cognitive human-machine interaction (industrial IoT connections, smart events processing, knowledge data models and AI-based decision support) and enabling cognitive tools that provide existing process industries flexibility of operation, improvement of performance across different indicators (KPIs) and state of the art quality control of its products.

The CAP reference implementation is based on major open-source frameworks, such as FIWARE and Apache, for batch, continuous and hybrid process industry plants and will be validated in three outstanding process sectors: asphalt (minerals), steel making, and pharma industry (chemical). The topics of flexibility, performance and quality control in the sectors addressed by CAPRI use cases have different implications at the three main functional hierarchy levels: planning, manufacturing operations management and control. Through CAP, it proposes cognitive solutions for each hierarchical level.

The publication of this article has been extracted and freely adapted from ENG website