From Industrial Automation to Intelligent Automation: The Impact of IIoT on Process Control - A Review?

The Industrial Internet of Things (IIoT) is reshaping process control, turning torrents of plant data into near-instant insight. Field evidence already shows unplanned-downtime cuts of 55%, maintenance-budget savings of 40%, and gains in overall-equipment-effectiveness of roughly 15%; nevertheless, fewer than 30% of facilities have pushed beyond pilot scale to full, always-on predictive maintenance. To clarify why, this review screens 312 Scopus records published between 2010 and 2023, then subjects 62 peer-reviewed studies and a broad set of industry reports to deep content analysis, bibliometric mapping, and thematic clustering.The results reveal four tightly connected research fronts—IIoT/Industry 4.0 core technologies, classical process-control theory, data-driven intelligence, and enabling infrastructure—with cybersecurity emerging as the fastest-growing theme. Across the surveyed literature, the synergistic use of edge computing, artificial intelligence, blockchain, and advanced wireless sensor networks demonstrably sharpens anomaly detection, accelerates control-loop response, and improves energy efficiency. At the same time, persistent obstacles—expanded attack surfaces, legacy-system interoperability, data-management overload, and fragmented standards—continue to throttle large-scale adoption.Drawing on comparative case studies from manufacturing, oil and gas, power generation, and water treatment, the paper distils actionable design rules: adopt zero-trust architectures with lightweight authentication at the edge; pair federated-learning filters with certified robust inference to resist data poisoning; and deploy delay-aware computation-offloading schemes that trade cloud muscle for millisecond-class responsiveness and extended battery life. A forward-looking agenda highlights open questions around sub-100 ms secure aggregation, benchmark metrics for energy-aware offloading, and cross-vendor interoperability for 5G-and-beyond networks.By unifying quantitative trends with hard-won field lessons, this synthesis provides researchers, control engineers, and plant managers a clear playbook for building robust, secure, and high-performance intelligent-automation systems—and charts the research paths most likely to unlock IIoT’s full industrial promise.

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Publication Details

Journal
Iraqi Journal for Computer Science and Mathematics
Published
2025-07-04
DOI
https://doi.org/10.52866/2788-7421.1281
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
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article

From Industrial Automation to Intelligent Automation: The Impact of IIoT on Process Control - A Review?

N. Ibrahim, Hayder Hussein Thary, Mohammad Sarfraz, Ali S. Allahloh et al.
Iraqi Journal for Computer Science and Mathematics
Digital Transformation in Industry
article

From Industrial Automation to Intelligent Automation: The Impact of IIoT on Process Control - A Review?

N. Ibrahim, Hayder Hussein Thary, Mohammad Sarfraz, Ali S. Allahloh, Duraid Y. Mohammed
article en

Abstract

The Industrial Internet of Things (IIoT) is reshaping process control, turning torrents of plant data into near-instant insight. Field evidence already shows unplanned-downtime cuts of 55%, maintenance-budget savings of 40%, and gains in overall-equipment-effectiveness of roughly 15%; nevertheless, fewer than 30% of facilities have pushed beyond pilot scale to full, always-on predictive maintenance. To clarify why, this review screens 312 Scopus records published between 2010 and 2023, then subjects 62 peer-reviewed studies and a broad set of industry reports to deep content analysis, bibliometric mapping, and thematic clustering.The results reveal four tightly connected research fronts—IIoT/Industry 4.0 core technologies, classical process-control theory, data-driven intelligence, and enabling infrastructure—with cybersecurity emerging as the fastest-growing theme. Across the surveyed literature, the synergistic use of edge computing, artificial intelligence, blockchain, and advanced wireless sensor networks demonstrably sharpens anomaly detection, accelerates control-loop response, and improves energy efficiency. At the same time, persistent obstacles—expanded attack surfaces, legacy-system interoperability, data-management overload, and fragmented standards—continue to throttle large-scale adoption.Drawing on comparative case studies from manufacturing, oil and gas, power generation, and water treatment, the paper distils actionable design rules: adopt zero-trust architectures with lightweight authentication at the edge; pair federated-learning filters with certified robust inference to resist data poisoning; and deploy delay-aware computation-offloading schemes that trade cloud muscle for millisecond-class responsiveness and extended battery life. A forward-looking agenda highlights open questions around sub-100 ms secure aggregation, benchmark metrics for energy-aware offloading, and cross-vendor interoperability for 5G-and-beyond networks.By unifying quantitative trends with hard-won field lessons, this synthesis provides researchers, control engineers, and plant managers a clear playbook for building robust, secure, and high-performance intelligent-automation systems—and charts the research paths most likely to unlock IIoT’s full industrial promise.

Iraqi Journal for Computer Science and MathematicsVol. 6(3)
Openalex Percentile: Top 77%
Digital Transformation in Industry
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