AI & IoT Consulting for Manufacturing Co
- AI Consulting Data Annotation Services IoT Development
- Confidential
- Jan. - Dec. 2024
- Quality
- 5.0
- Schedule
- 5.0
- Cost
- 5.0
- Willing to Refer
- 5.0
"The project established a scalable AI foundation for our long-term Industry 4.0 roadmap."
- Manufacturing
- Nunavut, Canada
- 11-50 Employees
- Online Review
- Verified
Infinity Technologies provided AI and IoT consulting services for a manufacturing company. The team built an AI production intelligence platform that combined real-time sensor ingestion and advanced analytics.
Infinity Technologies' work led to a 10-18% increase in OEE on critical lines, a 30% reduction in micro-stops, a 20-25% decrease in unplanned downtime, and a 5-10% decrease in scrap. The team built explainable AI instead of black-box automation, connecting AI insights directly to operator workflows.
The client submitted this review online.
BACKGROUND
Please describe your company and position.
I am the Marketing Manager of North Axis
Describe what your company does in a single sentence.
We operate high-speed, sensor-rich production lines that include:
Cutting and composition stations
Conveyor and transport systems
Heating and glue zones
Storage buffers and lift mechanisms
Multi-point thickness measurement systems
Our profitability depends on:
Stable throughput
High OEE
Low scrap rate
Minimal unplanned downtime
Standardized operator performance
Before the project, PLC-level data existed, but analytics were fragmented. OEE was reported, but without deep visibility into micro-stops, bottlenecks, and predictive insights.
OPPORTUNITY / CHALLENGE
What specific goals or objectives did you hire Infinity Technologies to accomplish?
- We engaged Infinity Technologies to implement a comprehensive Industry 4.0 transformation program focused on: Increasing OEE Reducing micro-stops (<2–5 minutes) Enabling predictive maintenance Improving quality consistency Optimizing buffers and bottlenecks Building an AI-driven manufacturing intelligence layer
SOLUTION
How did you find Infinity Technologies?
Online Search
Why did you select Infinity Technologies over others?
- Great culture fit
- Good value for cost
- Referred to me
How many teammates from Infinity Technologies were assigned to this project?
2-5 Employees
Describe the scope of work in detail. Please include a summary of key deliverables.
Infinity Technologies designed and delivered a unified AI-powered Production Intelligence Platform combining real-time sensor ingestion, advanced analytics, and explainable AI tools.
The solution aligned with Industry 4.0 principles: connected assets, data-driven decisions, predictive capabilities, and human-AI collaboration .
Phase 1 — Automatic Stop Detection & OEE Decomposition:
Using drive status bits, button signals, safety sensors, material presence detectors, and environmental signals, Infinity built a formal state model of the production line:
RUN / IDLE / MICRO-STOP / FAULT / CHANGEOVER
They applied:
Unsupervised clustering
Sequence mining
Event-log pattern recognition
This allowed automatic classification of short stops that were previously invisible in ERP systems.
Impact:
Micro-stop Pareto per shift/product/operator
Hidden OEE losses uncovered
Data-driven root cause analysis
Phase 2 — Full OEE & “Lost Hours” Analytics:
Using material detection sensors and automatic/manual mode signals, they implemented:
Detailed Availability / Performance / Quality breakdown
Detection of “machine ready but no material” scenarios
AI-based classification of lost hours
Example insight:
“The line was technically ready for 22 minutes but no material was loaded — likely upstream supply delay.”
Impact:
Clear separation of planned vs unplanned losses
Objective shift performance measurement
Fact-based production management
Phase 3 — Predictive Maintenance of Drives & Motion Systems:
Using drive status signals, limit switches, temperature indicators, retry patterns, and cycle-time measurements, Infinity built:
Time-to-failure models
Survival analysis
Anomaly detection on mechanical cycle time
The system detects gradual degradation in transport systems, lift mechanisms, and motion axes before breakdown.
Impact:
20–25% reduction in unplanned mechanical downtime
Maintenance planning became predictive
Lower emergency repair costs
Phase 4 — Heating & Process Stability Analytics:
Using temperature zone sensors and pressure measurements, Infinity deployed:
Multivariate time-series forecasting
Drift detection between setpoints and actual values
Correlation of thermal stability with product quality
Early warnings identify heater degradation, pressure instability, or sensor miscalibration.
Impact:
Reduced joint and bonding defects
Fewer temperature-related stops
Increased process stability
Phase 5 — AI-Based Quality Analytics:
Using multi-point thickness sensors and event signals from cutting and handling stations, Infinity implemented:
Regression models linking thickness profiles to scrap
Classification models predicting defect probability
Optimal parameter window recommendations
Impact:
5–10% scrap reduction
Improved product consistency
Reduced customer complaints
Phase 6 — Buffer & Bottleneck Optimization:
Using sensors across input, intermediate transport, storage buffers, and output systems, Infinity created a discrete-event digital twin of the line.
They applied:
Flow simulation
Bottleneck shift detection
Optimization algorithms for buffer policies
The AI suggested speed and policy adjustments to minimize starvation and blocking.
Impact:
Higher throughput stability
Reduced idle time
Better synchronization between stations
Phase 7 — Automatic Parameter Recommendation (Recipe Optimization):
Each production run was treated as a structured data experiment.
Inputs:
Speeds
Temperatures
Pressures
Mode selections
Outputs:
OEE
Scrap rate
Micro-stops
Using Bayesian optimization and regression modeling, the system recommended improved parameter combinations per product type.
Impact:
Up to 12% reduction in micro-stops for specific products
Better balance of quality, throughput, and energy usage
Phase 8 — Safety & Operator Analytics:
Using interlock and protective device signals, Infinity implemented:
Pattern detection for frequent safety activations
Operator behavior clustering
Correlation between manual interventions and performance
Individualized coaching insights were generated for operators.
Impact:
Improved standardization
Reduced operator-induced variability
Safer production environment
Phase 9 — “Explainable Line” AI Copilot (LLM Layer):
Infinity built an LLM-based copilot over:
Event logs
Sensor signals
Machine documentation
The system translates technical PLC signals into human-readable explanations and supports troubleshooting.
Operators can ask:
“Why did the line stop at 13:42 yesterday?”
“What does this fault mean?”
“What should I check next?”
Impact:
Faster incident resolution
Reduced dependency on senior technicians
Improved onboarding of new staff
RESULTS & FEEDBACK
What were the measurable outcomes from the project that demonstrate progress or success?
Within the first year:
OEE improved by 10–18% on critical lines
Micro-stops reduced by ~30%
Unplanned downtime reduced by ~20–25%
Scrap reduced by 5–10%
Maintenance shifted from reactive to predictive
Production flow stabilized
The factory evolved from traditional automation to a fully integrated Industry 4.0 AI-enabled smart manufacturing system.
Describe their project management. Did they deliver items on time? How did they respond to your needs?
The engagement followed:
Structured diagnostics
Pilot validation
AI experimentation with defined KPIs
Production hardening
Scaled rollout
KPIs included OEE uplift, scrap reduction, and predictive accuracy targets
What was your primary form of communication with Infinity Technologies?
Email or Messaging App
What did you find most impressive or unique about this company?
Built explainable AI instead of black-box automation
Connected AI insights directly to operator workflows
Combined digital twin + ML + LLM into one coherent system
Focused on economic value creation through OEE improvement
Are there any areas for improvement or something Infinity Technologies could have done differently?
The project established a scalable AI foundation for our long-term Industry 4.0 roadmap.
We now treat our factory as a self-learning production system, continuously improving through data and AI.
RATINGS
-
Quality
5.0Service & Deliverables
-
Schedule
5.0On time / deadlines
-
Cost
5.0Value / within estimates
-
Willing to Refer
5.0NPS