Discrete manufacturing: IT-OT intelligent integration

Trend 3: 5G powered remote operations and maintenance boosts efficiency across the value chain

Remote operations and maintenance are becoming important enablers to enhance remote operability, sustainability and monitoring in real-time for enhancing efficiency across the value chain. The Round-Trip Time (RTT) - a network request from initiation to destination for a given workflow must be minimal, underlining the need for a 5G cloud network, which addresses lower latency and seamless connectivity requirements. Cloud computing and AI on edge for data-intensive processes such as inventory consumption, critical to quality (CTQ) assessment, and online process inspections mandate 5G technology as the digital foundation layer for efficient connectivity. The need for an intelligent alert system from connected IoT devices with operation and enterprise layers necessitates highly stable network connectivity for overall system performance. 5G will provide a seamless and secure communication channel between OT and IT for data ingestion, analytics and reporting. The demand for multiple communication layers with multi subsystem configuration in discrete manufacturing will utilize network slicing with 5G technology. Industry 4.0 and 5G initiatives enable remote shared services that connect central processing and operation teams with production, machines, processes and maintenance workflows in real-time.

Infosys collaborates with clients to design and develop unmanned and remotely operable platform solutions across the value chain. Inbound logistics, for example, can be remotely operated for efficient and autonomous material movement. The fault tree data for equipment is managed with a cloud-based, AI-enabled diagnostics solution. High-end operational analytics are carried out for equipment operation and maintenance data to improve their utilization. These platforms are enabled with VR, AR to carry out contactless remote maintenance as an immersive experience.

Discrete manufacturing: IT-OT intelligent integration

Trend 4: 5G influences accelerated adoption of unmanned technologies like robotics, autonomous and drone systems

Manufacturers are accelerating the adoption of unmanned solutions to achieve higher efficiencies in the supply chain, logistics, surveillance and monitoring.

Unmanned movement of material in manufacturing demands intelligent navigation systems and remote monitoring with secured communication. 5G's lowerlatency and high data transfer rate affirm its utility in autonomous mobility. Constant remote monitoring and situational awareness activate real-time responses for safer navigation on the shop floor. Furthermore, 5G enables faster data transmission by capturing images, sending the data for processing on edge with an AI layer for controlling as per the business layer. Track and trace will be used more often as real-time movement tracing and action will be possible with 5g.

Smart warehouse operations today use unmanned aerial vehicles (drones) for video capture of inbound inventory. Drone systems help with vision-based inspection for mission-critical systems. Autonomous mobility platforms improve the supply chain efficiency of both inbound and outbound logistics. Industry 4.0 solution integration expects autonomous guided vehicles to optimize infrastructure and connect autonomous technologies with the supplier ecosystem for scheduled intelligent delivery systems (JIT), enhancing overall efficiency. Collaborative robotics systems improvise productivity and overall equipment efficiency.

These unmanned technologies will create flexible manufacturing floors through infrastructure transition with integrated unmanned mobility solutions and digital platforms across the value chain.

A leader in electric mobility services developed autonomous vehicles and robotic platforms to amplify human potential and enhance human safety and security. For this Infosys client, the advanced work was achieved in a 3D environment by utilizing next-generation platforms built on AI, machine and deep learning.