AX Solution

Manufacturing AI Agent

Production, quality, equipment and energy judgements come together as a response ready for approval.

OVERVIEW

From judgements scattered across departments to one response plan

Production, quality and equipment deciding apart

  1. 01Gather judgementsProduction, quality, equipment, energy and carbon analyses are brought into one context.
  2. 02Review optionsOperating goals and execution constraints are weighed together to set priorities.
  3. 03Approve and feed backThe plan an owner approves is carried out, and its result informs the next decision.

WHY AI AGENT

Decisions each team made on its own, now made as one

  1. 01

    Brings together what each domain's AI concludes, and weighs how processes affect one another and where their goals collide.

  2. 02

    Compares responses against delivery, cost, quality and environmental targets, within resource and safety limits, then sends the approved one to the MES as work orders.

  3. 03

    Learns from what actually happened, so the plant's decision criteria keep improving along with its data.

  • Decision scope

    Manufacturing AI AgentOptimized plant-wide

    Manual coordination
    Individual experience
    Domain AI
    Optimized per domain

  • Issue response

    Manufacturing AI AgentPrioritized by impact and urgency

    Manual coordination
    Meetings and calls
    Domain AI
    Separate alarms per domain

  • Trade-offs

    Manufacturing AI AgentOptions compared, best one proposed

    Manual coordination
    Resolved after the fact
    Domain AI
    Not considered

  • Execution

    Manufacturing AI AgentApproval → MES order → learning

    Manual coordination
    Manual instructions
    Domain AI
    Each team acts separately

KEY FEATURES

Four capabilities for operating decisions

From one operations board to conversational queries, response plans, and approval and history.

Agent Capability

01 / 04

01

Operations board

Results from production, quality, equipment, energy and carbon AIs are brought onto one screen with the issues open now. Each issue shows its reach and its owner, so it is clear what to look at first.

Management Scope

  • Department AI results
  • Issue list
  • Impact reach
  • Status summary
  • Live updates
  • Owner assignment

Four capabilities joined in one operating-decision flow.

WORKFLOW

Each capability, as the work actually runs

For each capability, the order it runs in and the check it passes before moving on.

Five operating views in one context

  1. 01

    Define

    delivery · quality · equipment issue

  2. 02

    Gather

    department data · AI results

  3. 03

    Integrate

    same lot · equipment · time

  4. 04

    Summarise

    risks · constraints · actions needed

Recorded alongside

01

Issue · target · time

02

Department judgements · evidence

03

Data · model versions

Operating check

Do the departments' judgements describe the same target?

YES

Consistent → combined judgement

NO

Differences → check target · time basis

An example workflow · the detailed links and criteria are set to suit your floor.

SYSTEM ARCHITECTURE

What it connects, and the work it leads to

From the data that goes in to the results on the floor.

01 / INPUT

01Department judgementsproduction · quality · equipment · energy · carbon
02Operating goalsdelivery · cost · quality · environment
03Execution constraintsresources · process · permissions · safety

CONNECTED OPERATIONS

Manufacturing AI Agent

Risks and information from each department combined
Conflicting conditions and options compared
Owner approval linked to execution

03 / OUTPUT

✓Response prioritiesimpact · urgency · conditions
✓Action plansplanning · operating · maintenance options
✓Operating historyevidence · approval · results fed back
Linked by common identifiers, master data and historyResults checked → fed into the next run
Who uses itPlant operations leadsProduction · quality · maintenance teamsEnergy · carbon owners

METHOD

How it is built

Department AIs' judgements and operating rules go in, a response plan comes out, and the approved action goes back to the floor.

Collection01 →

Data Ingestion

Department AIs

Quality · equipment · energy analysis

MES / ERP link

REST API · actuals · plans

Operating rules

SOPs · permissions · safety rules

ProductionQualityEquipmentEnergy · carbon
Context merge

Links judgements by equipment, LOT and time

Permission & constraint check

Authority · safety · resource conditions

Target System

Judgement historyResults by department
Knowledge baseSOPs · past actions
Approval historyGrounds · approvals · results
Modelling & analysis02 →

AI/ML Modeling

Judgement & coordination

Agent orchestration

Calls department AIs · gathers results

Prioritisation

Impact · urgency · feasibility

Option simulation

Plan · condition · maintenance options

Grounds

Relevant data and past cases

Feedback & refinement

Outcome evaluation
Approval & rejection history
Criteria updates
Service03

Response plans

PrioritiesImpact · urgency
Action plansPlan · conditions · maintenance

Approval & execution

MES
ERP
Work orders

Operating history

Grounds, approvals and results feed the next decision

Built for plants where decisions across departments interlock

  • Automotive and battery manufacturing site

    Automotive & batteries

  • Close-up of a printed circuit board with a semiconductor chip mounted on it

    Semiconductors & electronics

  • A pipette dispensing a sample in a laboratory

    Chemicals

  • Steel and metal manufacturing site

    Steel & metals

  • A machinery manufacturing site with extrusion moulding equipment

    Machinery & equipment

  • A researcher inspecting vials on a pharmaceutical production line

    Bio & pharmaceuticals

Brings every department's AI together into a response an owner can approve.

  • Production plans and actuals
  • Quality predictions
  • Equipment anomaly signals
  • Energy and carbon status
  • Operating goals and permissions
Manufacturing AI Agent
  1. Risks and information combined
  2. Conflicting conditions and options compared
  3. Approval linked to execution
  • Recommendation adoption
  • Response lead time
  • Decision time
  • Action traceability

EFFECT

What changes from judgement to action

  • 01

    Faster decisions

    The grounds each department checked separately are seen on one screen, and the response is decided there.

    Decision timeReview steps
  • 02

    Fewer cross-department conflicts

    How one department's action affects another's goals is reviewed before it is carried out.

    Goal conflictsRework of plans
  • 03

    Consistent response criteria

    Experts' criteria are tied to data, so the response follows the same basis whoever is on duty.

    Response criteriaVariation between owners
  • 04

    A record of actions

    Grounds, approvals and results are kept as history and become the basis for the next decision.

    Approval historyAction results

CONNECT THE NEXT

Connected solutions

The solutions that take this one's data and results and carry them on.

See all solutions →

Manufacturing AI Agent

Data · work · execution linked

START WITH YOUR FACTORY

Start with your factory's own challenges

Check where you stand with the AX readiness check first, then carry on to a consultation.

Request a consultation