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03 / Advanced Technology Solutions

AI-Enabled Software Modules

Software built around a defined production problem, available evidence and a measurable acceptance criterion

Scope question 03

Which production problem is defined well enough to justify a dedicated module?

Starting point
One operational problem and its available evidence
Owner
The process owner who accepts the result
Acceptance
A criterion measured before production release
  1. Bound the problem
  2. Verify evidence
  3. Accept against criteria

Decision scope

Define the module boundary before its feature list

argemas designs modules for a specific operational problem and connects them to the ERP, MES and other systems of record already in use.

Development does not begin until the problem owner, available data, system boundary and measurable acceptance criterion are agreed.

Decision casebook

Three problems, three measurable acceptance boundaries

Each case defines the problem, evidence, module response and measures to track before a pilot begins.

CASE 01

Schedule changes leave delivery risk hidden

Operational problem

A new order, capacity loss or operation delay changes the plan, but the affected orders and lines cannot be assessed together.

Evidence used

  • 01Order and due-date data
  • 02Operation times and routing
  • 03Line, machine and shift capacity
  • 04Planned-versus-actual production

Module response

APS, capacity forecasting and line optimization are evaluated as one decision scenario. The proposed plan reaches the system of record only after user approval.

Acceptance measures

  • Orders exposed to delivery risk
  • Time required to revise the plan
  • Planned-versus-actual capacity variance
CASE 02

A quality deviation is found in the next operation

Operational problem

Defect codes, inspection results and images remain in separate sources, so the deviation is not linked to its originating operation in time.

Evidence used

  • 01Inspection results and defect codes
  • 02Product, lot and operation relationships
  • 03Approved product images
  • 04Rework and scrap records

Module response

A quality-analysis or computer-vision module prioritizes review for the defined defect classes. The authorized quality role retains the final disposition.

Acceptance measures

  • Deviation detection lead time
  • False-accept and false-reject rates
  • Scrap and rework rate
CASE 03

Unplanned failure repeatedly disrupts maintenance

Operational problem

Failure history, machine signals and maintenance work orders are not evaluated together, so intervention usually begins after downtime starts.

Evidence used

  • 01Failure and downtime history
  • 02Sensor and counter signals
  • 03Maintenance work orders
  • 04Spare-part and planned-maintenance data

Module response

A predictive-maintenance module proposes review or maintenance when a defined risk threshold is crossed. A work order opens only through the approval workflow.

Acceptance measures

  • Unplanned downtime
  • Time between warning and failure
  • Approved maintenance recommendation rate

Scope index

Work that can become a dedicated module

  1. Advanced planning and scheduling (APS)
  2. Manufacturing operations decision support
  3. Production planning and line optimization
  4. Demand, capacity and delivery-date forecasting
  5. Quality analysis and computer vision
  6. Predictive maintenance
  7. Decision-support systems and executive assistant
  8. Enterprise knowledge and document assistant
  9. Facility-specific AI-enabled software modules

Delivery approach

The technical solution is designed with the production decision

  1. 01

    The work starts with the production process, decision rule and available data—not with a preselected model.

  2. 02

    Data objects, integration boundaries, failure behavior and user approval are part of the module design.

  3. 03

    The pilot scope does not expand until the acceptance criterion is met.

Delivery boundary

What every module defines explicitly

  1. Operational problem and process owner
  2. Data boundary across ERP, MES and other systems
  3. Analysis, forecast or automation output
  4. Acceptance test and tracked measures
  5. Change, maintenance and extension responsibility

Next decision

Define the first module scope

Select one operational problem, identify the required data and agree on a measurable acceptance criterion.

Discuss the use case