Analyze production yield, scrap rates, and downtime to identify root causes
Manufacturers stop guessing about machine downtime and scrap rates with an automated analytics platform that identifies root causes in real time. This allows you to offer a high-value operational service to shop floors that immediately reduces their waste and improves production yield.
The problem today
$100K+
lost annually to unexplained scrap and yield issues
20 hours
wasted per week on manual production data collection
Mike Callahan is the owner-operator of a 28-person CNC and metal fabrication shop in Rockford, Illinois, running five production lines for three automotive Tier 2 customers. He knows his scrap rate is too high and suspects one of his older Mazak cells is the culprit, but every time he tries to prove it, the data trail goes cold in a spreadsheet someone last updated on a Thursday.
01The Problem
Night-shift defects compound for hours while supervisors reconstruct data instead of correcting the line.
Machine drift goes undetected until a full scrap bin confirms it — aluminum stock gone, run restarted from zero.
Root cause investigations consume the production manager's full week and still close with a best guess, leaving the failure free to repeat.
A recurring thermal failure on Line 3 stays invisible behind vague downtime codes while maintenance replaces the wrong parts on a loop.
Three competing OEE figures circulate the floor from a spreadsheet nobody trusts, making every production decision directionally unreliable.
Audit season triggers a two-week scramble to reconstruct records never captured in traceable form, pulling skilled people off the floor.
02The Solution
Solution Brief
Fictional portrayal · illustrative
- Mike runs five CNC lines, two QC techs, one overloaded production manager
- Yield data lives across three systems, an ERP, and a stale shared Excel file
- Suspected Mazak cell scrap problem — data trail goes cold every Thursday
- $12K batches scrapped before drift is confirmed
- $8K/month lost to a thermal pattern no one has named yet
- Production manager doing data archaeology instead of floor management
- Audit prep consumes two weeks of skilled labor — records were never captured
- Connects to existing PLCs and SCADA — no rip-and-replace
- Flags Cell 4 vibration signatures before the next part is cut
- Scrap spike traced to specific mold, shift, and temperature threshold in minutes
- Single OEE number built from live data replaces three competing spreadsheet versions
- MSP recurring engagement at $4,000–$8,000/month — displacing it means dismantling production reporting
“I knew we had a scrap problem. I just couldn't prove where it was coming from. My production manager was spending more time building reports than fixing anything. The first week the system was live, it tied a yield drop on Line 3 to a thermal drift issue we'd been calling 'operator error' for eight months. Eight months.”
— Mike Callahan is the owner-operator of a 28-person CNC and metal fabrication shop in Rockford, Illinois, running five production lines for three automotive Tier 2 customers
03What the AI Actually Does
Anomaly Detection Engine
Continuously watches real-time machine telemetry across every connected piece of equipment and fires an alert when a pattern — vibration, temperature, cycle time drift — matches the early signature of a developing fault, before any bad parts are made.
Scrap Root Cause Analyzer
When yield drops or scrap spikes, this component automatically cross-references machine data, work order history, operator shifts, and material lots to generate a ranked list of probable causes — cutting a week-long investigation down to a morning.
OEE Intelligence Dashboard
Replaces the manual spreadsheet with a live, accurate view of Overall Equipment Effectiveness across every line and shift, pulling directly from machine data so the numbers are consistent, trustworthy, and available before the morning standup.
Compliance Audit Trail
Automatically logs every production event, quality measurement, and machine state change in a structured, tamper-evident record that satisfies ISO 9001 requirements without anyone having to reconstruct history from memory come audit time.
04Technology Stack
MachineMetrics Professional
$200–$400/machine/month; estimate $2,400–$4,800/month for 12 machines ($28,800–$57,600/year)
Cloud-native machine monitoring platform providing out-of-the-box connectivity to CNC machines, injection molders, and stamping presses. Automatically…
KEPServerEX Manufacturing Suite
$2,875 one-time (Manufacturing Suite) + ~$575/year annual subscription; individual drivers from $452
OPC UA/DA server with 100+ industrial protocol drivers for bridging legacy PLCs (Modbus RTU/TCP, EtherNet/IP, PROFINET, FANUC, Mitsubishi) to modern M…
Microsoft Power BI Pro
$14/user/month; estimate 8 users = $112/month ($1,344/year)
Executive and management dashboards showing yield trends, scrap Pareto charts, downtime root cause analysis, shift-over-shift comparisons, and financi…
Azure IoT Hub (S1 Tier)
$25/unit/month; estimate 2 units = $50/month ($600/year) for up to 800K messages/day
Cloud message broker and device management for ingesting production data from the edge gateway. Provides device twins, message routing to Azure servic…
Azure SQL Database (General Purpose)
$150–$300/month ($1,800–$3,600/year)
Cloud-hosted relational database storing aggregated KPIs, downtime event records, scrap summaries, and ML model outputs. Serves as the data warehouse …
Azure Blob Storage (Hot Tier)
$20–$50/month ($240–$600/year)
Cold storage for raw sensor telemetry, historical time-series data beyond 90-day on-premise retention, and ML training datasets. Provides cost-effecti…
TimescaleDB Community Edition
Free (self-hosted); optional Timescale Cloud from $29/month
High-performance time-series database deployed on the on-premise analytics server. Stores 90 days of hot sensor data (vibration, temperature, cycle ti…
Grafana OSS
Free
Shop-floor real-time dashboards displayed on Samsung tablets at workstations. Shows live OEE gauges, current machine status, active alarms, and shift …
Python (Anaconda Distribution)
Free (Anaconda Individual Edition)
Runtime environment for custom ML models performing root cause analysis, anomaly detection, and scrap prediction. Key libraries: scikit-learn, pandas,…
Node-RED
Free
Low-code data integration and transformation running on the edge gateway. Provides visual flow-based programming for bridging OPC UA data from KEPServ…
Eclipse Mosquitto MQTT Broker
Free
Lightweight MQTT message broker on the edge gateway that receives machine data from KEPServerEX IoT Gateway and Node-RED flows, then forwards to Azure…
05Alternative Approaches
Option A: Budget Open-Source Stack
$15,000–$30,000 Year 1 (hardware + KEPServerEX license + MSP labor)
Replace MachineMetrics SaaS with a fully open-source stack: KEPServerEX (or open-source OPC UA client) for data collection, Apache Kafka for streaming, TimescaleDB for storage, Grafana for dashboards, and Python for all analytics. No SaaS subscriptions. All software runs on the Dell PowerEdge T360. Machine connectivity is handled entirely through KEPServerEX and Node-RED. Dashboards are Grafana-only (no Power BI).
Strengths
- 40–60% cheaper than the primary approach in Year 1 due to no MachineMetrics subscription ($28K–$58K/year savings)
- No ongoing SaaS subscription costs
- Full control over all software components
Tradeoffs
- Significantly higher implementation effort — MSP must build machine connectivity, OEE calculation, downtime tracking, and dashboards from scratch
- Requires 2–3x more MSP labor hours
- 5–8 months to initial value vs. 3–4 months with MachineMetrics
- No plug-and-play CNC machine adapters; PLC connectivity must be configured manually for each machine
- No mobile app
Best for: Client has a very tight budget (<$30K Year 1), has in-house IT/OT staff who can assist, or has primarily non-CNC machines that MachineMetrics doesn't natively support
Option B: Full MES Platform (TrakSYS or Tulip)
$60,000–$100,000 Year 1 (MES subscription + hardware + integration labor)
Replace the custom-built analytics stack with a purpose-built Manufacturing Execution System (MES). Use Parsec TrakSYS ($1,999+/month) or Tulip ($1,000+/month) as the primary platform, which provides OEE tracking, scrap tracking, downtime management, quality workflows, and dashboards out of the box. Supplement with Power BI for executive reporting and retain KEPServerEX for legacy machine connectivity.
Strengths
- Lower complexity for MSP — MES platforms provide pre-built templates for OEE, scrap, and downtime
- Similar or faster time to basic functionality (4–8 weeks)
- Much richer functionality including digital work instructions, electronic batch records, quality SPC charts, and scheduling
- Better suited for compliance-heavy environments (21 CFR Part 11, ISO 13485)
Tradeoffs
- 20–40% higher cost than primary approach due to MES subscription costs
- MES implementation requires manufacturing domain expertise
- Full customization takes 3–6 months
- ML/AI capabilities are limited — still requires custom Python models for root cause analysis
Best for: FDA-regulated manufacturers needing electronic batch records, clients wanting comprehensive MES functionality beyond just analytics, or clients with multiple plants that need standardized operations
Option C: Cloud-Native with AWS IoT SiteWise
$50,000–$90,000 Year 1 (cloud consumption + hardware + integration labor)
Replace the on-premise analytics server with a fully cloud-native architecture using AWS IoT SiteWise for industrial data modeling, AWS IoT Greengrass on the edge gateway, Amazon Timestream for time-series storage, Amazon SageMaker for ML model training, and Amazon QuickSight for dashboards. No on-premise server (Dell PowerEdge T360 eliminated).
Strengths
- Unlimited scalability with no on-premise server maintenance
- Built-in ML model hosting via SageMaker
- Well-suited for multiple geographically distributed plants needing centralized analytics
- Similar timeline to primary approach (3–5 months)
Tradeoffs
- Ongoing cloud costs scale with data volume and may increase significantly as more machines are added
- Requires AWS expertise and MSP needs AWS IoT SiteWise and SageMaker certifications instead of on-premise Linux/PostgreSQL skills
- Fully dependent on internet connectivity — if the plant loses internet, real-time dashboards go dark (partially mitigated by Greengrass edge caching)
Best for: Client has no server room or IT infrastructure, MSP has strong AWS expertise, client has multiple geographically distributed plants, or client's IT policy mandates cloud-first architecture
Option D: Existing SCADA Vendor Extension
$20,000–$50,000 Year 1 (module licenses + configuration labor)
If the client already has an Ignition SCADA system or Rockwell FactoryTalk deployment, extend the existing platform with analytics modules rather than deploying a separate analytics stack. For Ignition: add the Reporting Module ($2,400), Perspective Module ($3,800) for web dashboards, and SPC Module ($2,400). For FactoryTalk: add FactoryTalk Analytics Edge or FactoryTalk DataFlowML. Retain custom Python ML models for advanced root cause analysis.
Strengths
- Lowest cost option if the client already owns the base SCADA platform — only incremental module licenses needed
- Fastest time-to-value (4–8 weeks) since machine connectivity already exists
- Leverages existing infrastructure and operator familiarity
- Low complexity for basic OEE dashboards; existing SCADA integrator may handle this
Tradeoffs
- Higher complexity for ML integration — still requires custom Python work
- Built-in analytics are typically simpler than dedicated platforms (basic OEE, trending, SPC) without sophisticated root cause ML capabilities
Best for: Client has an existing Ignition or FactoryTalk deployment with active support contracts, client wants to minimize new technology introduction, or client has an existing SCADA integrator relationship they want to maintain
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