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levels/L0-production-enterprise/README.md
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levels/L0-production-enterprise/README.md
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# L0 — Production Enterprise
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The top-level enterprise context for the production organisation.
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Typical concerns:
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- production portfolio;
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- plants and sites;
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- high-level KPIs;
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- safety, quality, environmental and financial targets;
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- enterprise data governance.
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levels/L0-production-enterprise/process.yaml
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levels/L0-production-enterprise/process.yaml
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process:
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id: "oipf.l0.production-enterprise"
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level: "L0"
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name: "Production Enterprise"
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purpose: "Represent the enterprise-level production context in which operational intelligence is deployed."
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inputs:
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- production strategy
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- plant portfolio
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- business KPIs
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- compliance obligations
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outputs:
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- production intelligence scope
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- enterprise-level operational objectives
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children:
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- "oipf.l1.production-domain"
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levels/L1-production-domain/README.md
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levels/L1-production-domain/README.md
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# L1 — Production Domain
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Defines the domain context for production operations. The generic library remains industry-neutral, but domain packages can specialise it.
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Examples:
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- food and beverage;
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- chemicals;
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- pulp and paper;
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- water and wastewater;
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- pharma;
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- metals and materials.
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levels/L1-production-domain/process.yaml
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levels/L1-production-domain/process.yaml
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process:
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id: "oipf.l1.production-domain"
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level: "L1"
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name: "Production Domain"
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purpose: "Represent a domain such as food production, chemical processing, water treatment, pulp and paper, pharma, or metals."
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inputs:
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- plant scope
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- domain-specific production constraints
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- asset classes
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- regulatory context
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outputs:
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- domain process model
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- domain package selection
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parent: "oipf.l0.production-enterprise"
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children:
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- "oipf.l2.production-line-operations"
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levels/L2-production-line-operations/README.md
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levels/L2-production-line-operations/README.md
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# L2 — Production Line Operations
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Represents a production line, unit operation, or operational area.
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This level maps real plant systems into OIPF structures:
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- asset hierarchy;
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- tag mapping;
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- material and energy flows;
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- operating states;
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- events;
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- procedures;
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- constraints.
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levels/L2-production-line-operations/process.yaml
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levels/L2-production-line-operations/process.yaml
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process:
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id: "oipf.l2.production-line-operations"
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level: "L2"
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name: "Production Line Operations"
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purpose: "Represent a line, unit operation, or production area where operational intelligence is applied."
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inputs:
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- asset hierarchy
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- tag list
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- historian data
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- operating modes
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- events
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- procedures
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outputs:
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- mapped operational context
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- selected optimisation use case
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parent: "oipf.l1.production-domain"
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children:
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- "oipf.l3.operational-intelligence-loop"
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levels/L3-operational-intelligence-loop/README.md
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levels/L3-operational-intelligence-loop/README.md
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# L3 — Operational Intelligence Loop
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The reusable intelligence loop:
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```text
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Observe → Contextualise → Infer → Check → Recommend → Approve → Act → Record → Learn
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```
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This is the central reusable process pattern of the library.
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levels/L3-operational-intelligence-loop/process.yaml
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levels/L3-operational-intelligence-loop/process.yaml
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process:
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id: "oipf.l3.operational-intelligence-loop"
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level: "L3"
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name: "Operational Intelligence Loop"
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purpose: "Convert contextualised production data into governed recommendations and learning feedback."
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pattern:
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- observe
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- contextualise
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- infer
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- check
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- recommend
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- approve
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- act
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- record
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- learn
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parent: "oipf.l2.production-line-operations"
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children:
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- "oipf.l4.recommend-act-record-learn"
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levels/L4-recommend-act-record-learn/README.md
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levels/L4-recommend-act-record-learn/README.md
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# L4 — Recommendation-to-Outcome Work Task
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This level describes the concrete work task by which an AI/ML/physics model recommendation becomes a governed operational action.
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The key output is not only the action. It is the recorded outcome, because outcome feedback allows the intelligence loop to improve.
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levels/L4-recommend-act-record-learn/process.yaml
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levels/L4-recommend-act-record-learn/process.yaml
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process:
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id: "oipf.l4.recommend-act-record-learn"
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level: "L4"
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name: "Recommendation-to-Outcome Work Task"
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purpose: "Execute a human-in-the-loop recommendation cycle and record the measurable outcome."
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inputs:
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- model output
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- recommendation
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- constraint result
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- operator approval
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outputs:
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- action record
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- measured outcome
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- audit event
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- feedback signal
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parent: "oipf.l3.operational-intelligence-loop"
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