Lucian Fogoros (@fogoros) header
Lucian Fogoros (@fogoros) profile picture

Co-Founder https://teapawt.net/t.co/KwXjxubObe Advisory Board Cleveland State University Computer Eng. #IIoT #AI #ML #CxO #IndustrialTransformation #ICSCybersecurity #AR

United States
Joined January 2009
Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)Photo by Lucian Fogoros (@fogoros)
Volkswagen Group collects all available data at the edge without pre-selecting what to keep, and metadata about product, maintenance state, and operating conditions travels with the data from the point of capture. When one plant solves a quality problem with AI, the other 42 benefit immediately. Partner content with @InfluxDB. #influxdata_iiot
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Rather than centralizing everything, Volkswagen keeps data at each plant while a semantic layer ensures consistent meaning across all 43 global plants, connecting IT, OT, and engineering data into a single digital thread from order intake through manufacturing.
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An AI-ready data backbone requires five capabilities beyond traditional historians: durability with store-and-forward for network outages, nanosecond timestamp precision, open data standards, support for both training and inference workloads, and a semantic layer for consistent meaning.
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Doug Pagnutti from Tiger Data ran machine learning on a powder dosing line when he was an automation engineer. The model found that humidity and other processes in the room were directly related to the tuning parameters. Nobody on the team knew that. Once they fed that data in, they could speed up the process. Partner content with @TigerDatabase.
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When an AI agent links a critical process parameter like temperature or pH to a critical quality attribute like potency or purity, full provenance metadata must be captured at the moment of decision. Partner content with Adlib. #adlib_iiot
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Every element of that linkage must be recorded at the time of the decision, covering the full feature set, not a summary produced later. Merck's core architectural question is whether agents are built to emit evidence or answers, since these serve different purposes.
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Fluency-optimized output and attribution-optimized output are not the same thing. Only one of them survives a regulatory inspection, making the architectural choice between them a compliance decision, not a performance optimization.
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An AI model in OT trusts its sensor inputs more than an experienced operator would. Sensor drift and spoofing are distinct attack surfaces. Matt Morris of EverLine adds work orders, vendor manuals, and tickets ingested by the model are also vectors for poisoning and prompt injection. Partner content with @skkynetinc. #skkynet_ai #everline_ai
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Historian integrity and time sync fall under data and source integrity in Morris's industrial AI risk register framework. If training or inference data provenance is compromised, the model's decisions are compromised and the operator may never know.
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Morris flags automation bias as a human-control boundary risk. Will an operator actually catch a confident but wrong recommendation from an AI? Named accountability for AI-driven decisions is required, the model did it is not an owner.
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An AI optimization application proposes a new process setpoint. An intermediate DataOps layer then checks: is the value in acceptable range? Is the process in the right operating state? Is the command reasonable in context? #highbyte_iiot
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Eli Goldratt's theory of constraints says any optimization outside your main bottleneck makes things worse. Right now, manufacturing teams are building analytics on data that's still scattered across CSVs and disconnected systems. Matty Stratton says the real bottleneck is getting all of it into one place first. Partner content with @TigerDatabase. #tigerdata_ai #IMTS2026
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Lucian Fogoros retweeted
Ko smo se odločali za vstop v EU, si ni nihče predstavljal, da bo v kaki njeni članici in uniji nasploh mogoče brez posledic: 1. Razveljaviti predsedniške volitve (Romunija); 2. Ukiniti informativni program na nacionalni RTV (Madžarska); 3. Poslati policijo na Ustavno sodišče (Poljska); 4. Tri tedne pred volitvami poslati v zapor predsednika stranke, ki vodi v anketah (Slovenija); 5. Zasesti nacionalno RTV s policijo in zamenjati vodstvo (Poljska); 6. Prekiniti mandate vodstvu nacionalne RTV in izvesti čistko zaposlenih (Slovenija); 7. Poslati v zapor člane prejšnje vlade brez možnosti obrambe (Madžarska); 8. Podeliti skoraj milijon državljanstev ilegalnim migrantom po hitrem postopku (Španija); 9. Zapreti novo Nuklearno elektrarno in zgraditi plinovod do Rusije (Nemčija); 10. Obdavčiti ogljične energetske vire ob hkratnem zapiranju NE ter preseliti industrijo v države z nizkimi ekološkimi standardi pod pretvezo, da tako rešujemo planet. Nastala je EU, ki se mora reševati sama pred sabo.
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New equipment introduced into a production environment carries the same unverified-device risk as a contractor laptop at a substation. Partner content with @OPSWAT. #opswat_ics
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The solution places SOC visibility at the point where access decisions are made: the SOC issues the verdict, and the field operator acts on it.
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More than 40% of ICS/OT security incidents resulted in operational downtime, per the SANS 2025 ICS/OT Cybersecurity Report, making device-access control a direct operational continuity issue.
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