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MFG · Advanced Manufacturing

Agents that trace yield losses and plan the line

Plant data sits in MES, SCADA historians, SPC charts and the QMS, and engineers spend hours stitching it together by hand. FreeSeek builds agents that query these systems directly, assemble the evidence and draft the next action. Quality, process and maintenance engineers review and approve each output before it reaches the shop floor.

Systems we connect to
MESSCADASAP PP/QMQMSOPC UAHistorianPLM
Application scenarios Case studies
Agent run · examplerun_7f3a21
TaskFirst-pass yield on Line 4 dropped from 97.8% to 93.1% since Tuesday. Find the likely cause.
  1. mes.query()
    Pulled 186 lots from Line 4 since Monday and split them into passing and failing groups by defect code.
  2. historian.read()
    Found reflow zone 6 running 4 °C above setpoint on 81% of failing lots, starting after Tuesday's maintenance.
  3. qms.search()
    Matched the pattern to a 2025 8D on the same oven, where a replaced thermocouple was miscalibrated.
Result · Ranked hypothesis report and verification plan sent to the Line 4 quality engineer for approval.
Industry context

Where plant operations stand today

Most plants have digitized the shop floor over the past decade. Machines stream data through OPC UA into historians, the MES records every lot and genealogy step, and SAP PP/QM holds orders, routings and inspection lots. The data exists. Connecting it still depends on a few experienced engineers who know which tables to join, which tags matter and which deviations are normal for a given line.

Product mixes are widening and batch sizes are shrinking, so changeovers and new part introductions happen more often. Each change creates quality risk and paperwork. Customer audits under IATF 16949 expect traceable root-cause analysis, current PFMEAs and controlled SOPs. Teams keep these documents up to date in spreadsheets and Word files, and the backlog grows faster than headcount.

Scarce process expertise

Senior engineers who can read SPC trends and MES genealogy together are retiring or stretched across several lines. Their knowledge rarely lives in a system.

High-mix, low-volume demand

More variants and shorter runs mean more changeovers per shift. Scheduling under material and tooling constraints becomes a daily puzzle.

Audit and documentation load

IATF 16949 and customer-specific requirements demand 8D reports, PFMEA updates and SOP revisions after every significant defect. Writing them takes days.

Alarm fatigue in maintenance

Condition monitoring produces thousands of alarms a week. Planners struggle to separate real failure precursors from noise and open the right work orders.

Application scenarios

Four workflows, analysed step by step.

Each scenario shows how the work is done today, what the agent takes over, where a person signs off, and what we measure.

MFG-1Yield-drop root-cause analysisMFG-2Production scheduling and changeover planningMFG-38D, PFMEA and SOP drafting from defect recordsMFG-4Maintenance work-order triage from sensor alarms
MFG-1

Yield-drop root-cause analysis

The agent correlates a yield drop with process, material and equipment data and proposes ranked root-cause hypotheses.

Integration depth Deep integration
Typical pilot8–10 weeks
How it works today

When first-pass yield falls, a quality engineer exports lot data from the MES, pulls SPC charts, checks the historian for parameter drift and asks the warehouse about material lots. Each source has its own identifiers and time stamps. Aligning them in Excel takes one to three days, and the investigation often stops at the first plausible cause. Meanwhile the line keeps producing scrap or the parts go to containment.

Systems used
MESSAP QMHistorianSPCQMS
What the agent does
  1. Pulls affected lots, routing steps and defect codes from the MES and SAP QM inspection lots.
  2. Aligns lot genealogy with historian tags and SPC data for the same time window and equipment.
  3. Compares good and bad lots across material batches, tools, shifts and process parameters to rank candidate causes.
  4. Checks each hypothesis against past 8D records and known failure modes in the PFMEA.
  5. Delivers a short evidence report with charts, ranked hypotheses and suggested verification tests.
Human checkpoint
The quality engineer reviews the ranked hypotheses, chooses which verification tests to run and decides on containment. The agent does not change process parameters or release material.
What we measure
  • Time to confirmed root cause
  • Scrap cost per incident
  • First-pass yield recovery time
  • Repeat defect rate
MFG-2

Production scheduling and changeover planning

The agent builds a feasible shift schedule that sequences changeovers around material availability, tooling and due dates.

Integration depth Moderate
Typical pilot6–8 weeks
How it works today

Planners take the MRP output from SAP PP and rebuild the sequence by hand each morning. They check material on hand, tool and die availability, operator qualifications and customer due dates across several screens. When a material shipment is late, they reshuffle the plan on a whiteboard. Changeover sequences are chosen from habit, and the cost of a poor sequence shows up later as overtime or missed deliveries.

Systems used
SAP PPMESTooling databaseWMS
What the agent does
  1. Reads planned orders, routings and due dates from SAP PP and current WIP status from the MES.
  2. Checks material availability, open purchase orders and tooling status against each order.
  3. Generates two or three candidate sequences that minimise changeover time while protecting due dates.
  4. Explains the trade-offs of each option, including at-risk orders and required overtime.
  5. Writes the approved sequence back to the MES dispatch list.
Human checkpoint
The production planner selects the sequence and confirms it with the shift supervisor before release. Any order that misses its due date requires planner approval and a customer service note.
What we measure
  • Changeover hours per week
  • On-time delivery rate
  • Schedule adherence
  • Planner hours spent on rescheduling
MFG-3

8D, PFMEA and SOP drafting from defect records

The agent turns defect records and investigation notes into draft 8D reports, PFMEA updates and SOP revisions.

Integration depth Quick win
Typical pilot4–6 weeks
How it works today

After a customer complaint or internal nonconformance, the quality team must produce an 8D report within tight deadlines. Engineers copy data from the QMS, photos and meeting notes into a template. They then update the PFMEA and affected SOPs, often weeks later. Documents drift out of sync, and auditors find PFMEA ratings that do not reflect recent failures. Experienced engineers spend a large share of their week on writing.

Systems used
QMSPLMDocument control systemMES
What the agent does
  1. Collects the nonconformance record, containment actions, test results and investigation notes from the QMS.
  2. Drafts the 8D disciplines D1 to D8 in the customer's required template, citing the evidence for each step.
  3. Identifies the PFMEA lines and control plan entries affected and proposes updated severity, occurrence and detection ratings.
  4. Prepares redlined SOP revisions for the affected work instructions.
  5. Routes the package into the document control workflow for review.
Human checkpoint
The responsible quality engineer edits and approves the 8D before it goes to the customer. PFMEA rating changes and SOP revisions follow the plant's normal document control approval.
What we measure
  • 8D cycle time
  • On-time 8D submission rate
  • PFMEA update lag
  • Audit findings on document control
MFG-4

Maintenance work-order triage from sensor alarms

The agent groups sensor alarms, matches them to known failure patterns and drafts prioritised work orders.

Integration depth Moderate
Typical pilot6–8 weeks
How it works today

Condition monitoring and SCADA raise alarms on vibration, temperature and current. Many are transient or duplicates. Maintenance planners scan alarm lists, check the asset history in the CMMS and decide what needs a work order. Real precursors get buried in noise, so some failures arrive unplanned, while technicians are also sent to inspect machines that were fine.

Systems used
SCADAHistorianOPC UASAP PMCMMS
What the agent does
  1. Collects alarms from SCADA and the historian and groups them by asset and time window.
  2. Compares alarm patterns with the asset's maintenance history and past failure records in the CMMS.
  3. Scores each group by likely failure mode, urgency and production impact using the current schedule.
  4. Drafts work orders with probable cause, suggested checks, required spare parts and a proposed time slot.
Human checkpoint
The maintenance planner approves, merges or rejects each draft work order. Any action that requires stopping a line needs sign-off from the production supervisor.
What we measure
  • Unplanned downtime hours
  • Share of alarms converted to work orders
  • Mean time to repair
  • False-dispatch rate
Case studies

How engagements in this field have played out.

Illustrative cases: composites of typical deployments with client details removed. Figures show the range our pilots are designed to reach.

Root-cause time cut on an SMT line

Client: Tier-1 automotive electronics supplier, 3 plantsRegion: East Asia
−41%time to confirmed root cause
−23%scrap cost on the pilot line
100%8D reports submitted on time during the pilot
Challenge

Solder defects on an engine control unit line caused recurring yield drops. Each investigation took quality engineers several days because MES lot data, reflow oven historian tags and AOI results lived in separate systems. Customer 8D deadlines under IATF 16949 were often met with incomplete analysis, and the same defect returned twice in one quarter.

What we built
  • Connected the agent read-only to the MES, oven historian and AOI database through existing interfaces.
  • Built a lot genealogy model that aligns board serials with oven profiles, paste lots and stencil IDs.
  • Added a hypothesis report and an 8D draft step reviewed by the line quality engineer.
Timeline: 10-week pilot on one line, rollout to 3 plants in month 6

Changeover planning for a high-mix machining shop

Client: Precision machining supplier for industrial equipment, 2 plantsRegion: Southern Europe
−27%changeover hours per week
+9 ptson-time delivery
−35%planner time spent rescheduling
Challenge

The plant ran over 400 active part numbers on 30 CNC centres. Planners rebuilt the schedule daily in spreadsheets, and late bar stock deliveries forced frequent manual reshuffles. Changeovers consumed a large share of machine hours, and on-time delivery had fallen below customer targets.

What we built
  • Read planned orders and routings from SAP PP and machine status from the MES.
  • Modelled fixture and tool families to group jobs with shared setups.
  • Generated daily schedule options with a trade-off summary for the planner.
  • Wrote approved sequences back to the MES dispatch list.
Timeline: 8-week pilot, production use in month 4
Risk and compliance

Risk, compliance and data on the plant floor

IATF 16949 and ISO 9001 traceability

Every agent output cites the source records it used, so 8D reports and PFMEA changes remain auditable. Approved documents pass through the plant's existing document control process.

OT network segmentation

Agents read OT data through a DMZ or historian replica and never write to PLCs or SCADA. Deployments follow the zone and conduit model of IEC 62443.

Human authority over process changes

The agent can propose parameter changes, schedules and work orders but cannot release them. Release requires a named engineer or planner in the MES, QMS or CMMS.

Data residency and IP protection

Process recipes and drawings are core intellectual property. Models and data stay in the customer's region or on premises, and no customer data is used to train shared models.

Questions we hear
Does the agent need write access to our MES or SCADA?

No. Most pilots run read-only against a historian replica and MES reporting views. Write-back, such as a dispatch list update, is added later through an approved interface with user-level permissions.

How does it handle our plant-specific defect codes and terminology?

During the pilot we map your defect catalogue, tag names and routing structure into the agent's context. Engineers review the mapping, and the agent cites its sources so errors are easy to spot.

Will auditors accept documents drafted by an agent?

Auditors assess the content and the approval trail. Each draft records its evidence sources and the approving engineer, which supports the traceability IATF 16949 expects.

What does a typical pilot need from our side?

One line or cell, read access to two or three systems and a process or quality engineer for a few hours each week. We define success metrics with you before the pilot starts.

Have a workflow like these?

Send us a short description of how the work is done today. We reply within two business days.

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Other industries
MATNew Materials R&DENGEngineering DesignMEDHealthcare ServicesFINFintechMKTMarketing