Manufacturing Operations Business Data Model: AI-Ready Edition

The Manufacturing Operations Business Data Model: AI-Ready Edition is for CIOs, architects and transformation leads who need to know what information manufacturing work runs on before an AI agent touches it. It covers 15 subject areas, 120 entities, 880 key attributes and 405 relationships. Every entity and key attribute is classified for sensitivity, with the AI uses and data-quality requirements an agent depends on. It is the data-model part of Business Architecture for Manufacturing Operations: AI Transformation Blueprint, sold on its own.

What's Inside

The same model comes in three files: the full model in Word, a workbook to filter and extend, and a guide to the scales and the license.

• 15 subject areas and 120 entities, each with a definition, its typical system of record, sensitivity class, AI uses and data-quality requirements
• 880 key attributes with sensitivity and AI relevance, and 405 relationships with cardinality
• Under each entity, the capabilities that need it and the agents that read it, by name and ID
• The data and information items of the earlier edition of this model, each mapped to the entity that now holds it
• The Business Data Model (Word): every subject area and entity in full
• The workbook (Excel): subject areas, entities, attributes and relationships in sheets you can filter and extend
• The guide (Word): the scales the model refers to, the data foundation, and the license
• Free corrections, and new versions free for 180 days

Every file names your organization and carries your license ID.

The 15 Subject Areas

The 120 entities are grouped into 15 subject areas. The list gives what each holds and how many entities it has.

• Manufacturing Strategy, Capacity & Cost (8 entities): The direction, capacity and cost of manufacturing: the manufacturing strategy, plant roles, make-or-buy analyses, demonstrated plant capacity, investment cases, plant budgets, the operational inputs to standard costs and the variances explained in operational terms.
• Products, Processes & Work Instructions (8 entities): How each item is made: the manufactured item, its manufacturing bill of materials and routing, process parameters with their validated limits, recipes, line balances, work instructions and standard work.
• Industrialization, Validation & Change (8 entities): The records that take a product or a change into stable production: industrialization projects, pilot production runs, production readiness assessments, validation plans, equipment qualifications, process validations, process change requests and their impact assessments.
• Production Scheduling & Shop Floor Execution (8 entities): The plant schedule and what happens on the floor: production schedules built within the approved scheduling rules, schedule changes, changeovers, production orders, downtime events, line stops, production deviations and shift handovers.
• Line-Side Materials, Records & Genealogy (8 entities): Material at the line and the record of what was made: material staging requests, material issues, work-in-process lots, material consumption, scrap and rework, production records, their corrections and the genealogy links that make up the plant part of traceability.
• Plant Workforce & Qualifications (6 entities): The people who run the plant and what they are qualified to do: shift crew plans, position assignments, plant skills, skills matrix entries, operator qualifications and qualification assessments.
• Quality Planning, Inspection & Measurement (10 entities): How quality is planned and measured: control plans, process risk analyses, quality documents, internal quality audits, inspection plans, inspection results, control charts, process capability studies, measuring instruments and calibration records.
• Nonconformance, Supplier Quality & Release (10 entities): Product that does not meet its requirements and the decisions about it: nonconformances, dispositions, planned deviations, root cause analyses, corrective and preventive actions, supplier quality requirements, supplier corrective action requests, quality holds, product release decisions and suspect product scope.
• Production Assets, Maintenance & Spares (10 entities): The equipment that makes the product and the work that keeps it running: production assets, asset criticality, maintenance plans, requests and work orders, maintenance deferrals, equipment condition readings, failure predictions, failure analyses and spare parts.
• Plant Safety Risk & Safe Work (8 entities): How the plant controls hazards and high-hazard work: workplace hazards, task risk assessments, safety observations, work permits, energy isolation records, safety system bypasses, process hazard analyses and pre-startup safety reviews.
• Safety Incidents, Exposure & Emergency (7 entities): Safety incidents and the health of the work environment: incidents, near misses, investigations and their actions, exposure assessments, exposure measurements and the plant emergency plan.
• Plant Environment & Energy (7 entities): The plant's environmental controls and use of energy and water: environmental aspects, emission and discharge measurements, waste records, spill or release events, energy use readings, energy performance baselines and water use records, released by the Plant Environmental Lead for the organization's reporting.
• Plant Performance & Improvement (8 entities): How plant performance is measured and improved: plant measures and results, equipment effectiveness records, manufacturing losses, improvement projects, standard work confirmations, tier review actions and employee ideas.
• Operational Technology & Plant Data (7 entities): The control systems that run equipment and the plant data drawn from them: control systems, control program versions, control system changes, plant data points, plant data quality issues, production analytics models and technology pilots.
• AI & Digital Labor Governance (7 entities): The records that keep AI in manufacturing accountable: AI systems, agents, their action logs, AI decision records, validation records, human reviews and agent authority limits, each agent with its own identity and read-only access to plant and control system data.

Who Uses It

Data owners and stewards, data architects, and AI and analytics engineers who need to know what an agent may read, how sensitive it is and how good it must be first; and business architects who link capabilities to data.

How It Fits With the Other Products

The capabilities named under each entity are defined in the Manufacturing Operations Capability Model: AI-Ready Edition. The agents are specified in Business Architecture for Manufacturing Operations: AI Transformation Blueprint, which contains this data model and adds the value streams, use cases, controls, an operating model and a roadmap. The Manufacturing Operations Value Streams are sold on their own too.