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IIoT for the evolution of smart factories and urban mobility platform

AI and IoT are the bedrock for Industry 4.0. There is a rapid proliferation of digitalization – technologies to improve processes, functions, and operations in a business entity – across all industries such as agriculture, education, infrastructure, healthcare, retail, and consumer. Estimates are that by 2020 about 30 billion smart devices are going to be connected. This article touches upon the needs, challenges, and workarounds through digital transformation.

Some of the needs in a factory setting are:

· Machine-to-Machine (M2M) interaction on a shop floor.

· Machine-to-Computer (M2C) interaction – Example: sensorization of injection molding machine and cycle time for the molding process.

· Innovation on CNC (computerized numerical control) machines in a production workhouse.

· A tailored ontology with sensor implementation for machine maintenance.

· Monitoring solution for preventive maintenance and management.

· Security around IoT devices and data.

In the urban mobility area, the needs are towards a MAAS/TAAS platform. Digitalization of electric mobility, vehicle motion control, autonomous driving, and integrated safety are focus areas of IoT adoption.

Challenges are broad:

Localization of components, price sensitivity, production automation, consumer goods automation, digital twinning.

How do we meet the above needs?

First up,

  1. To transform the Brownfield device to a Greenfield IoT device, retrofit plugin sensors & actuators. This enables the operationalization of devices, data extraction, and monitoring in an efficient way.
  2. Enable Programmable Logic Controllers (PLC) with Ethernet/IoT connectivity to pump back gathered data into the production floor plant after intelligent processing.
  3. Enable IoT connectivity for remote I/O units – the IT system i.e. storage, compute, and analytics.

Secondly, The infrastructure – MicroEdge, MiniEdge, FullEdge: Delineate the infrastructure based on the needs. For real-time applications like in an autonomous car, storage & computation can be closer to the field devices (MicroEdge). Scalability and Resiliency are easier with MicroEdge datacenter being closer to the field. Resolve the bandwidth, latency and capacity issues by adopting a 5G network as the backhaul for devices to Edge/Cloud.

It’s important to closely follow communities like the Open Connectivity Foundation (OCF) for standards on seamless communication, interoperability & bridging specifications across multi-vendor devices, cloud implementations, and edge-compute platforms.

Thirdly, Designing service security for shopfloors: Adopting well-defined processes and protocols like OPC-Unified Architecture with portability and endpoint protection of devices. Secure communication is set up between sensors and cloud over a TLS channel with AES-256 encryption for data protection.

Fourthly, Support for REST API, MQTT-standards for orchestration, monitoring, telematics, and streaming of data between devices and edge/cloud-DC. Open-source frameworks like IoTIVITY, which defines device-discovery, config, management & tracking mechanisms, messaging and data exchange models can give a leg up for graded implementations.

Lastly, Investments need to be made in IP creation and IoT automation for a feature or functional transformation, product lifecycle, and recycling.

Future trends are volatile and the fidelity for digital twin is high. Excellence is achieved in manufacturing by moving onto cloud, cobots, and using AR/VR. Prioritize guidance for economies of scale and influencing customer’s customers. In a digital transformation world, companies do not compete against each other. The disruptions in the ecosystem, strategies, and the value proposition created is the key to success.

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