AUTEN HiveX is our in-house MES/MOM, designed as a layer of execution, traceability and operational context between the plant floor and management. It organizes orders, lots, phases, events and quality per ISA-95 and ISA-88, with recipes separated from procedures and flows ready for batch, continuous and discrete processes.
The starting point is practical: production data with origin, context and meaning. Operations stop relying on parallel spreadsheets and key people to explain what happened on a shift. Engineering, maintenance, quality and management start working on the same record, with the same reading of the process. This is the mature Industry 4.0 foundation that most plants still need to close before reaching for algorithms.
It is on this base that applied AI begins to make sense in industry. HiveX paves the way for operations to ask their own data where the deviation happened, what the likely cause was, what changed against the baseline and which action fits that shift. AI here does not replace the operator. It helps whoever decides do it with more predictability, clearer responsibility over the process and less waste of raw material, energy and time. It is the natural step toward operations where people, machines, systems and AI work better together, respecting the stage each plant is in today.
Highlights
- Standardized execution by area, shift and process type (batch, continuous, discrete).
- End-to-end traceability with recorded evidence for audit, quality and accountability.
- Recipes separated from procedures, with master-data governance and versioning.
- Operations, maintenance, quality and engineering working on the same process data.
- A context base that makes applied AI reliable, instead of a trend-driven promise.
- Support for shift decisions, root-cause investigation and deviation reading backed by industrial data.
- Stability that turns into less waste and a more sustainable operation over time.
- Multi-plant scale without losing technical governance or execution standards.
Objectives
- Standardize execution and give context to production data.
- Connect operations, maintenance, quality and management around the same process record.
- Build the operational-context base that supports applied AI for shift decisions and root-cause investigation.
Deliverables
- Execution and recording models with recipes separate from procedures.
- Operational screens and flows by role (operations, maintenance, quality, engineering).
- Governed integration with PLC/SCADA, corporate systems and the applied-AI layer.
- Master-data governance, audit trail and context ready for analysis and investigation.
Expected results
- Less operational variation shift to shift.
- Traceability that sustains audit, quality and clear accountability over the process.
- Faster, safer decisions backed by reliable data and AI applied to plant context.
- Less waste of raw material, energy and time, as a consequence of the stability gained.
When it fits
- High operational variation shift to shift
- Weak or non-auditable traceability
- Production data without enough context to sustain decisions
- Plant ready to move beyond dashboards toward AI-assisted decisions
AUTEN HiveX is where operation becomes a system, and the system starts supporting whoever operates, maintains and decides on the plant.
