Industry 4.0

Trends and innovations
The concept of the fourth industrial revolution was first introduced in Hannover earlier in this decade. This followed several decades of industrial automation, albeit at lower levels of functionality and complexity. Many developments have since shaped several industry 4.0 technologies that were previously under the purview of researchers. This is possible today, mainly due to innovations in technology, software, and hardware. Already, the increasing human-machine, machine-machine, and human-human connectivity influence production systems and processes across the world. Industry 4.0 trends and technologies are fundamental in achieving connected manufacturing geared towards smart and autonomous factories.

Trends Impacting Industry 4.0
    Employing artificial intelligence (AI) techniques across devices and processes forms the top industry 4.0 trend. Increasingly, emerging companies develop wearable solutions for the industrial workplace to ensure the safety and efficiency of the manufacturing process.
    Collecting data by implementing cloud and edge computing and designing cybersecurity solutions allow companies to establish the building blocks for setting up smart factories. Advanced robotic solutions comprising autonomous mobile robots, cobots, and swarm robotics, as well as robotic software development is also a major part of industry 4.0 trends.

Cyber Security, Transparency & Privacy
    The flow of information due to the connectedness in Industry 4.0 is raising concerns about security, transparency, and privacy. As the manufacturing practices are increasingly becoming personal and customisable, the data management practices done outside and within the shop floor will hugely influence the appeal of the company. The transmission and processing of sensitive industrial data need to be done securely to avoid cyberattacks on critical industrial facilities. Digital ethics and privacy, privacy-enhancing technologies, self-adaptive security, zero-trust security, end-to-end communication security, DevSecOps, blockchain are some of the new developments in this front. The focus on cybersecurity needs to be balanced with transparency and privacy.
    Industry 4.0 makes use of smart, connected devices sourced from multiple vendors. These devices need to be updated constantly with the latest software, firmware, and configuration files. Providing a secure update process for embedded devices. Cybercriminals potentially interfere with the upgrading process and compromise industrial facilities by tricking the staff into installing infected files. Adolus develops FACT, which solves this problem by working with equipment vendors to collect unique fingerprints of the files and compares these fingerprints with the ones received by the manufacturers. FACT gives a confidence rating during installation as well as visibility over the upgrading processes in critical systems.

Edge, Fog & Cloud Computing
    The immense amount of data being generated by the industrial internet of things (IIoT) is propelling the adoption of edge, fog, and cloud computing capabilities in Industry 4.0. Custom hardware and software solutions like connected clouds, distributed clouds, distributed compute and storage, hybrid computing, low code development platforms, microservices, mobile computing, and multi-access edge computing are shaping up this industry 4.0 trend.
    Hardware development as a service for edge computing applications. They shortens response time by moving AI from the cloud to the edge. The optimal performance of industrial systems depends on the efficient execution of the algorithm present in the machines. Edge computing facilities, along with IIoT, greatly improve the speed, security, and efficiency of the manufacturing process by accelerating the running of algorithms. The company provides support to the entire edge computing product development cycle.

Artificial Intelligence
    AI and machine learning are driving innovations across industries and functional areas. AI-specific hardware and new algorithms are being developed to optimise the existing systems and tackle new challenges facing manufacturing. Factories are beginning to integrate AI across their production systems and processes. Advanced AI makes it possible to conduct predictive maintenance, cognitive computing, swarm intelligence, context-aware computing, smart machines, hardware accelerators, and generative design. All of these technologies propel manufacturing facilities to move towards complete lights-out manufacturing.
    Production-grade AI for industrial operations. The technology enables the manufacturers to extract value from limited or imperfect datasets. They have incorporated industry domain knowledge into the AI system for delivering optimal performance. The solution enables using imperfect manufacturing data for autonomous decision making and process control. In addition, these AI products integrate with legacy assets, allowing more factories to adopt technology solution.

Human Augmentation & Extended Reality (XR)
    The physical and cognitive augmentation of humans forms another major industry 4.0 trend. The limitations in humans are being augmented with the help of technologies such as wearables and exoskeletons. Further, industrial mobile devices, natural and intuitive UI, and portable machine control screens enhance the ease of using such technology. XR technologies like mixed reality (MR), augmented reality (AR), and virtual reality (VR) are already in use in Industry 4.0 from the research and development (R&D) to full-scale production and post-production processes. This multi-experience paradigm is changing the way industrial manufacturing systems function. The nature of human-machine interaction is aligning more toward machine-enabled workers.
    Developing an exoskeleton technology platform. Many workers on the shopfloor encounter fatigue, weakness, and other physical discomforts due to the repetitive and monotonous nature of their tasks. The use of exoskeletons on the shop floor helps workers in doing their tasks efficiently while reducing or eliminating any physical strain. Exoskeletons usually provide support for the waist, upper limb (with 4 degrees of freedom), and lower limb (with 12 degrees of freedom).

Network & Connectivity
    Network and connectivity are among the main driving forces in enabling Industry 4.0. A number of technology developments such as edge-to-cloud, gigabit ethernet time-sensitive networks, low-power wide-area network (LPWAN), 5G, machine-to-machine communication (M2M), real-time deterministic ethernet, time-sensitive networking (TSN), ubiquitous radio access, unified IoT framework, and zero-touch networks nudge factories to implement IIoT to transform into Industry 4.0 facilities. These technologies constantly improve machine-machine and human-machine communication, as well as data transmission. As a result, innovations in this area increase speed, improve security and efficiency, and reduce the cost of network connectivity.
    A wireless IIoT communication service based on the IO-Link Wireless standard. IO- link is a communication protocol that works point to point and is usually wired. The IO-Link Wireless design allows it to handle a large number of devices while maintaining low latency and high reliability. Coretigo helps in wireless communication between sensors, actuators, and controllers.

Advanced Robotics
    Advancements in robotics make the processes in industry 4.0 faster, efficient, and safer. The most prominent robotic technologies impacting manufacturing include autonomous robots, collaborative robots (cobots), collaborative autonomous mobile robots, humanoid, mobile robots, cloud robotics, APIs, pick and place robots, and robot swarms. The use of robots offers higher precision and agility while improving the capability of rapidly developing customisable robots. Robots also free up time for the human workforce to focus on other non-repetitive or high-value tasks.
    SESTO Element, a multi-purpose autonomous mobile robot. Autonomous robots are essential for industrial automation facilities and allow the human workforce to focus on higher-level tasks, such as factory management. The compact mobile platform of SESTO Element is customisable with different types of top modules and is based on the nature of the tasks. They also offer SESTO Prime, an autonomous mobile robot equipped with a 7-axis robotic arm.

Internet of Everything
    The machine-machine, human-machine, and human-human real-time connectedness together comprise the internet of everything in manufacturing. It includes IIoT, internet of skills, internet of services, internet of systems, and shop floor IoT. The internet of everything combines together real-time data, machine intelligence, and human skills, resulting in faster, efficient, and cost-effective manufacturing processes. Interoperability and a unified internet of things framework are crucial for the smooth implementation of industry 4.0 facilities.
    Developing an internet of tools-enabled operations and maintenance management platform. The platform intends to replace the time-consuming nature of paper-based planning, execution, and reporting of maintenance activity. The use of smart connected tools, along with their platform, lead to transparent and traceable records of all maintenance operations. This helps in reducing costs associated with quality control and improving overall productivity.

Digital Twin
    Digital twin technology creates virtual models of industrial assets by combining dynamic real-time sensing and visualisation data. Some of the promising use cases of digital twins include model-driven design, virtual prototyping, virtual system validation, throughput optimisation, and evolutionary design. The use of digital twins is propelling industry 4.0 manufacturing towards hyper-automation. Digital twins provide valuable insights into all steps of the manufacturing process.
    A digital twin solution for various industrial processes. The solution allows manufacturing facilities to standardise meticulous operation and maintenance practices to optimise output. The physics-constrained AI, which drives the Gemius digital twin, provides self-optimised design and operational intelligence. The digital twin utilises SCADA systems to integrate with operational data, historian software, sensor gateways, and enterprise asset management tools.

Additive Manufacturing
    Manufacturers constantly search for new technologies to cater to all aspects of the growing market demand. Additive manufacturing, which started out as a prototyping technique, is revolutionising and decentralising production. Hybrid manufacturing aims to integrate both additive manufacturing and subtractive manufacturing. The advancement in material science and techniques such as stereolithography and metal 3D printing enables simpler fabrication of intricate structures and complex components. Additive manufacturing is making highly-customisable and sustainable cloud-based production a reality.
    An autonomous additive manufacturing solution by making use of swarm robots. Digital designs are split into smaller tasks that several different types of robots perform. Currently, the speed of additive manufacturing is limited by the size of the product. AMBOTS addresses this bottleneck by making use of a proprietary chunk-based 3D printing method.

Big Data & Analytics
    The scale of industrial data collection eventually enables factories to make the transition into industry 4.0 facilities. Big data is complex and is valuable only when it is captured, stored, and analysed in a quick and cost-effective manner. Advancements to utilize data for gaining valuable insights into the manufacturing systems, along with the availability of immediate and real-time data, open up opportunities for prescriptive, predictive, and augmented analytics at different levels of a company’s manufacturing facilities.
    Curiosity offers software platforms for extracting knowledge from structured and unstructured data. The platform integrates with the existing data infrastructure and provides accessible knowledge for users in any industrial setting. Data integration challenges in manufacturing companies arise due to the vast range of technical terms, documents, and abbreviations. Curiosity combines all relevant data sources into a knowledge graph that later helps in building custom tools for search and exploration.