Between expected cycle time and real production behavior
Catch the gap between planned time and real productionbefore it becomes shift loss.
Offram gathers live production data from PLC and edge systems. It compares planned cycle time with real performance. When drift starts, teams see the reason, update the recipe, and approve the action.
Offram Runtime / Cycle-Time IntelligenceLive data
Cycle time driftPLC/edge protocol supportData retention layerAgent-assisted risk indicationUNS workflowLocal recipes
PLC / edge connectivityProduction memoryAI insight + action flow
4.0 data, 5.0 decision flow
Turn machine data into the action flow your teams can use.
Offram collects live PLC, SCADA, MES, and ERP data, compares planned production with reality, surfaces drift early, and helps the right team take the right action.
Industry 4.0
Collect data from the floor
Capture cycle, stop, quality, energy, and production data from PLC, sensor, and SCADA sources.
Industry 5.0
See drift earlier
Compare the planned target with actual production behavior and make delay, stop, and quality anomalies visible.
Offram
Attach the decision to flow
Operators, maintenance, quality, and production teams see recommendations, approve action, and track the result in the same flow.
Offram Runtime / Cycle-Time Intelligence
Live data, production memory, action flow.
PLC / edge protocol support / Expected cycle time / Actual cycle time / Data retention layer / Time-series DB / SQL DB / Vector DB / UNS architecture / Local workflow builder
01Data Connection
Connects near PLC and edge data
Collects cycle, stop, speed, and quality signals close to the machine through S7, ADS, OPC-UA, and similar protocols.
02Production Memory
Writes every event to a timeline
Machine, product, shift, operator, stop, and recipe context are retained in the same production memory.
03Risk Indication
Flags plan drift earlier
Actual cycle time is compared with the plan. A 5-hour job drifting toward 8 hours is treated as a pilot scenario visible inside the shift.
04Cause Analysis
Makes the reason legible
Micro stops, speed loss, quality rework, and waiting time are separated so the team can see a clear recommendation.
05Action Flow
Drops the decision into team flow
Maintenance, quality, planning, and production act on the same event while recipe or work-order changes are approved.
Platform
Build an open intelligence layer above existing factory data.
Offram is added above the MES, ERP, historian, and operator screens you already use. It collects live floor data, writes production memory, interprets plan drift early, and connects insight to the workflow your teams act on.
Edge data became an action
In the pilot scenario, Offram flags the risk that a 5-hour plan may drift toward 8 hours inside the shift. Production, maintenance, and quality teams see the cause through the same workflow, review the recipe, and approve the action.
offram-runtimeLive data
PLC.LineA3.Connectedge runtime active
Plan.Order.4821.Expected5h 00m
Line.A3.Projection7h 48m risk scenario
Retention.Writewritten to production memory
Agent.Insightline variation is high
Workflow.Openproduction + maintenance + quality action opened
MES.ERP.Syncdrift event recorded
Offram.Connect
Offram.Retention
Offram.Agent
Offram.UNS
Connects close to PLC and edge data
ADS, S7, OPC-UA, Modbus, and MQTT connections collect data near the machine. Work order, recipe, shift, and machine signals are captured in the same production context.
ADSS7OPC-UAModbusMQTT
Anomaly Examples
Small deviations become large losses by the end of the shift.
Offram joins expected cycle, actual production signal, and team action on the same timeline, making delay, quality, energy, and data mismatch visible earlier.
01 / Planned cycle escapePlan
Plan risk inside the shift
If a work order is planned for 5 hours and actual cycles extend, the system calculates the risk of drifting toward 8 hours as a pilot measurement.
02 / Accumulating micro stopsOutput & OEE
The total effect of short stops
Short 10-20 second stops look minor alone. Offram clusters them, shows their effect on speed loss, and flags shift-end delay earlier.
03 / Quality rework riskQuality
Read cycle and quality signals together
Measurement drift, rework, or lot-condition change is watched alongside cycle extension so the quality team sees which recipe or process step to review.
04 / Unexpected energy useEnergy
Connect energy difference to production behavior
When energy use rises above expectation for the same output, the system relates it to cycle and machine state.
05 / Operator waiting and response delayAction
Time from alert to action
When an alert appears but intervention is delayed, loss grows. Offram measures the delay between warning and action start.
06 / Floor record and system record mismatchConsistency
MES/ERP record versus floor reality
If MES/ERP records disagree while a floor stop or drift is happening, the event is marked and decisions are tied to the same real production data.
Buying Criteria
MES, ERP, and Offram solve the same problem at different layers.
Offram is not another MES screen. It runs above existing systems and turns floor signals into plan risk, cause, and action workflow.
Classic MES/MOM
Digitizes operations
Standardizes work orders, OEE, stops, quality, maintenance, and reporting. It acts as the primary system for production tracking.
- Production tracking and reporting
- Operator panels and quality forms
- Paperless production processes
ERP / IIOT Integration
Moves data into business processes
Connects production data to enterprise workflows through gateways, mobile apps, ERP connectors, and dashboards.
- Two-way ERP synchronization
- Mobile approval and manager follow-up
- Protocol, hardware, and endpoint management
Offram Intelligence Layer
Accelerates decision and action
Reads live production behavior, surfaces plan drift early, and connects agent recommendations to workflow.
- Added above MES/ERP without replacing them
- Cycle drift and future-risk indication
- Open workflow, API, and local recipe architecture
Offram does not replace MES/OEE/ERP investments; it is an AI operations layer above them. It connects live production behavior to plan risk, root cause, and action flow.
Offram Technical Positioning
It starts smaller than an integration program and grows like factory intelligence.
Offram can begin with one line, one machine, or one work order. As value becomes visible, new data sources, agent scenarios, and workflows are added.
Local Workflow Builder
Workflows are not black boxes
Teams can see and adjust production flows, then save successful actions as reusable recipes.
Microservices
Start without opening a large program
Services can go live machine by machine. The system grows where value is proven.
Edge-First Architecture
Floor data does not wait in the center
Data is captured close to the machine, helping PLC signals reach the action layer without creating central bottlenecks.
AI Insight Reports
Insight returns in language teams understand
The agent does not only create alarms. It can guide the team with clear statements such as a work order risking shift overrun at the current speed.
Capabilities
From measurement to insight, from insight to action.
Offram is an open industrial software layer spanning PLC/edge connectivity, production memory, risk-reading agents, and action workflow.
01
PLC and edge connectivity
PLC, sensor, and SCADA data is captured close to the machine through ADS, S7, OPC-UA, Modbus, and MQTT connections.
02
Production memory
Cycle, stop, alarm, quality, energy, lot, and action records become available for analysis and learning.
03
Agent-assisted risk indication
The agent watches a defined production rhythm, prioritizes drift by plan effect, and flags approaching delay risk.
04
Action workflow
Drift connects to maintenance, quality, production, and planning flows. Teams manage action and recipe decisions visibly.
05
Edge-first open architecture
Offram is added above existing systems. Edge devices, open APIs, and sustainable architecture reduce central bottlenecks.
Pilot Measurement Plan
Define the first 5 pilot measurements upfront.
An Offram pilot is not a demo screen. Planned cycle, actual cycle, drift cause, captured anomaly, and triggered action are measured together.
01 / Cycle scopeTarget
Set the pilot boundary
Expected and actual cycle are watched in the same view for the selected work order, line, or machine.
02 / Plan escapeMeasure
Calculate plan drift
The system calculates how far production may drift from the planned finish time at its current speed inside the shift.
03 / Anomaly captureProve
Measure risk-flag timing
The pilot measures how early the agent flags cycle extension, micro stops, quality rework, or waiting patterns.
04 / Action timeShorten
Track decision delay
The time between warning and the start of maintenance, quality, production, or planning action is followed.
05 / SynchronizationConsistent
Tie records to the same event
ERP, MES, floor, and team-action records are checked to confirm they reflect the same drift event.
Scenarios
Build the first agent scenario around a real production drift.
One line, one machine, or one work order is enough. The critical move is comparing expected behavior with actual behavior and connecting it to action.
Automotive / Quality
Cycle and quality risk on a press line
Expected cycle, actual cycle, and quality measurement are watched together. The agent flags the risk that extended cycles may become scrap or rework.
Food / Traceability
Live lot conditions
Temperature, humidity, fill speed, recipe, and cycle behavior are watched together. The agent follows lot conditions by plan and quality effect.
Packaging / Throughput
Micro-stop intelligence
Short stops and cycle extensions cluster on the same timeline. The agent calculates how recurring stops affect the plan.
Pilot Result Formats
Pilot outcomes become visible in the same measurement format.
Each format answers the same question: what was the plan, what drifted, what did the agent see, what did the team do, and how was the result measured?
Format 01
Cycle escape
In a scenario where a 5-hour job is drifting toward 8 hours at the current speed, the report shows when drift was seen and which action was evaluated.
- Line / machine name
- Expected and actual cycle
- Agent insight and team action
Format 02
Quality and rework risk
When cycle extension combines with rework risk, the report shows the behavior caught before scrap and the recipe/workflow change made by quality.
- Lot / recipe context
- Quality signal and drift cause
- Recorded action recipe
Format 03
Energy, micro stops, and waiting
The report measures how small signals such as micro stops, operator waiting, or energy peaks were caught before becoming large shift-end loss.
- Captured small signal
- Shift / delivery effect
- Measured pilot metric
Sectors
Specific problems. One open intelligence layer.
Every sector has a different data shape and risk language. Offram first makes production behavior visible, then builds the right data model, agent, and action flow.
01
Automotive
Press, robot, and test-cell behavior becomes lot-level quality and cycle intelligence. Traceability records can stay synchronized to support IATF 16949 preparation.
02
Food & Beverage
Temperature, filling, cleaning, recipe, cycle, and lot records are written into production memory that supports GMP, HACCP, and audit preparation.
03
Packaging & FMCG
Micro stops, print issues, line balancing, cycle drift, and scrap risk are brought into agent tracking.
04
Heavy Industry
Energy, furnace, maintenance, and safety signals are turned into early action events before they become costly downtime.
Integrations
Connect the systems your factory already uses.
Offram fits into the existing industrial architecture. PLC, sensor, SCADA, historian, MES, and ERP data is collected in the same production context, and agent insight is synchronized with team actions.
PLC / edge protocol supportADSSiemens S7OPC-UAModbusMQTTSensorsSCADAHistorianEdge-first deviceTime-series DBSQL DBVector DBAgent runtimeInsight reportsUNS architectureLocal workflow builderRecipesMESERPREST APILiveOps
Set Up The First Pilot
Start with the line, work order, and cycle drift you want to understand.
In the first pilot, we watch expected and actual cycle together, capture data at the edge, write production memory, help the agent see drift early, and build the first measurable action workflow.
Pilot Request
Scope the first cycle-drift pilot together.
Share your ERP/MES/SCADA setup, the first line or machine to inspect, and the expected cycle context.