UPLO Manufacturing#

Connects your AI assistant to the structured knowledge layer built from your plant floor documentation — work orders, inspection reports, preventive maintenance schedules, CAPA records, production batch logs, and equipment manuals. When a machine goes down at 2am or a customer reports a defect, you need answers from your own data, not a web search.

Session Start#

Pull your manufacturing context first. This loads your role (maintenance engineer, quality manager, production supervisor), active production priorities, and any open quality holds or equipment issues.

text

use_mcp_tool: get_identity_context
use_mcp_tool: search_knowledge query="open quality holds production line stoppages equipment downtime alerts"

Check directives if you need to understand current throughput targets or quality improvement initiatives:

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use_mcp_tool: get_directives

When to Use#

• Investigating a non-conformance: what were the process parameters for batch #4471 on Line 3?
• Finding the torque specification and calibration schedule for the CNC mill in Cell B
• Pulling the FMEA (Failure Mode and Effects Analysis) for the new product introduction
• Checking if a specific raw material lot passed incoming inspection before it hit the floor
• Reviewing OEE trends for a production line to justify a capital expenditure request
• Locating the lockout/tagout procedure for the hydraulic press before a maintenance window
• Determining which shifts had the highest scrap rate last month and what corrective actions were taken

Example Workflows#

Root Cause Analysis for Customer Complaint#

A customer received parts with dimensional non-conformances. You need to trace back through your process.

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use_mcp_tool: search_knowledge query="part number 7842-A dimensional inspection results CMM data last 90 days"
use_mcp_tool: search_with_context query="work order production batch part 7842-A process parameters tool wear records"
use_mcp_tool: search_knowledge query="CAPA corrective actions dimensional tolerance issues machining"

The structured extraction links inspection data back to specific work orders, machine settings, and operator certifications — giving you a complete traceability chain for your 8D report.

Preventive Maintenance Planning#

You're building next quarter's PM schedule and need to consolidate equipment data.

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use_mcp_tool: search_knowledge query="preventive maintenance schedules all production equipment Q2 upcoming"
use_mcp_tool: search_knowledge query="equipment breakdown history unplanned downtime root causes 2025"
use_mcp_tool: export_org_context

Cross-reference PM intervals against actual failure data to shift from calendar-based to condition-based maintenance where the data supports it.

Key Tools for Manufacturing#

search_knowledge — Query across work orders, inspection records, PM logs, and SOPs simultaneously. The structured extraction means you get typed fields (part numbers, batch IDs, measurement values) not just raw text. Example: "SPC control chart data injection mold press 12 cavity pressure"

search_with_context — Follows the relationships between documents. A work order connects to the BOM, which connects to incoming material certs, which connect to supplier audits. Example: "material traceability lot number RM-2025-0892 from receiving through finished goods"

report_knowledge_gap — Found a machine with no documented setup procedure? A process with no control plan? Flag it. This feeds back into your quality system and ensures gaps get closed. Example: report that the new laser welder has no documented process validation (IQ/OQ/PQ).

propose_update — When an SOP is wrong or a spec has changed, propose the correction directly. It enters the review queue for the document owner. Example: update the anodizing bath concentration range after a process optimization study.

flag_outdated — Critical for manufacturing where revision control is everything. Mark superseded drawings, expired calibration certs, or obsolete work instructions before someone on the floor uses the wrong version.

Tips#

• Search by part number, work order number, or equipment asset ID for the most precise results — the extraction engine indexes these as structured fields, not just text tokens.
• Manufacturing data is deeply interconnected. If a simple search_knowledge doesn't give you the full picture, switch to search_with_context to traverse the relationships (part -> BOM -> supplier -> cert -> inspection).
• Always check document revision levels in results. If you spot an outdated revision, flag it immediately — in manufacturing, the wrong revision can mean scrapped parts or a safety incident.
• When logging conversations about quality issues, include the NCR or CAPA number — it makes the audit trail searchable when regulators or customers ask about corrective actions taken.