?? IIoT AI Framework {#Infographic}

?? IIoT AI Framework {#Infographic}

??? The Industrial Internet of Things (IIoT) integrates industrial assets and machines (the things) with business infosystems, processes, and the people who operate or use them.

??? IIoT enables the application of AI to data to gain insights into machine operations, optimize productivity, increase quality, reduce energy and material consumption, increase flexibility, and create new business value.

??? All this must be done while maintaining commitments to safety, reliability, resilience, security and data privacy and trustworthiness.

?? Technology Revolutions?

??? IIoT is a natural extension of prior technology revolutions:

• 1st: Water/steam power to mechanize production.
• 2nd: Electricity to create mass production.
• 3rd: Electronics/infotech to automate production.
• 4th: Converges physical, digital, and biological.

(Note: The above parameters are not universally defined. In many ways, we are entering the 5th Tech Revolution)

??? Industrial AI applies AI to IoT applications in industry, as in smart manufacturing, robotics, predictive maintenance, diagnosis of infectious disease with machine learning, and autonomous vehicles.

?? 4-Level FRAMEWORK

??? IIoT is best viewed on 4 levels:

?? 1. BUSINESS

??? Stakeholder IIoT vision, values, and objectives, and how IIoT achieves objectives through mapping and system capabilities.

??? Through a proper AI DigiTransform process, a business can more effectively increase production throughput, avoid or reduce operating costs, deliver higher margins, enable new capabilities, minimize mistakes, reduce inventory, improve safety, make better and faster decisions and improve the quality of products –all in a future-proof way.

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?? 2. USAGE

??? Sequences of activities by human users or IIoT to achieve system capabilities.

??? AI can be adopted into countless applications such as predictive maintenance, quality inspection and assurance, supply chain optimization, equipment condition-based monitoring, and manufacturing process optimization.

??? All aspects of data security and privacy are essential.

?

?? 3. FUNCTION

??? Components and their internal/external interrelations, interfaces, and interactions.

??? The process to use AI and Machine Learning (ML) involves two phases: model building and usage. Model building is an iterative process of exploring algorithms, training, fine-tuning and verifying the models.

??? Models also can be retrained with new data to increase its accuracy or to cover other issues. Again, quality data is of critical importance.

?

?? 4. IMPLEMENTATION

??? Technologies for Function communication and procedures, Usage coordination, and Business support.

??? The requirements for implementing AI into applications must be assessed for their suitability, economic viability, and ability to produce solutions that are “industry-ready” use cases.

??? The design of the AI system must also meet the performance requirements including data collection, data preparation, AI model learning, and AI model retraining.

??? An agile approach, with structured and measured steps across multi-disciplined groups, should be used to define the scope and integrated steps.

?? IN SUM …

??? The rapid emergence and convergence of AI with other IT and OT transformative technologies such as IoT, digital twins, edge, XR, 5G, distributed ledger, etc. promises to unleash a new generation of highly distributed systems that are personalized, contextualized, and feature real-time human-to-machine (H2M) and machine-to-machine (M2M) interactions, and new human machine interfaces.

??? This will empower a new generation digital transformational capabilities in organizations in virtually every industrial sector, with AI is acting a main catalyst for such disruptive IIoT solutions.

??? Moreover, Quantum AI (QAI) will achieve results that are impossible with classical computers. QAI will overcome these challenges.

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Source: Extracted and adapted from Link. Combined Infographic is mine. https://www.iiconsortium.org/pdf/Industrial-AI-Framework-Final-2022-02-21.pdf

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