Manufacturing & Production

Your challenges

Challenges that cost productivity

Limited production visibility

KPIs arrive at month-end when it's too late to react. You're steering blind. Anomalies surface only when production crashes.

Raw material procurement

Stockouts that halt production, overstock that freezes cash. Balance is hard to maintain. Delivery timelines are imprecise, forecasting impossible.

Compliance and traceability

ISO, client audits, batch traceability. Documentation takes disproportionate time. Quality proof is hard to assemble when auditors show up.

Tight cash flow

Late invoices, slow-paying clients, rough cash flow forecasts. Real-time financial visibility doesn't exist. Surprises arrive too late.

Deployment Roadmap

How we improve your production and quality

1

Production audit (Week 1)

We visit your facility and speak with the production team. We identify: what the real bottlenecks are, where time is lost, which defects keep recurring. Ground truth, no theory.

2

Connect ERP and machinery (Weeks 2-3)

Supply Chain and ERP Connect read your production data: cycle times, scrap rates, anomaly stops. Sensors connect to critical machines (no modifications). Everything feeds into the system in real time.

3

Configure alerts (Week 4)

Anomalies: cycle time increasing, scrap rising, machine starting/stopping abnormally. Each triggers a specific alert. Shift supervisors get notified before they realize there's a problem.

4

Real-time dashboards and OEE (Week 5+)

OEE (Overall Equipment Effectiveness) = Availability × Performance × Quality. You see it by equipment, by line, by shift. Every director sees the true bottlenecks and where to invest.

Prerequisites That Block

What needs to be in place

Basic production data

We need to know: what you produce, cycle times, scrap rates. If it's on paper or sticky notes, digitalize first. If it's in an MES or ERP: we connect directly.

Access to production equipment

Sensor installation requires physical access. Data reading: OPC-UA or Modbus interface, or CSV imports. Permissions and safety validation upfront.

Equipment documentation available

Machine manuals, electrical schematics, maintenance history. If everything is paper archives, we move slower. If it's organized: we deploy fast.

Production team buy-in

Operators worry about work optimization pushing them harder. Reality: we optimize bottlenecks and stops, not people. 2-3 days training. It's a tool for them, not surveillance.

Key Performance Metrics

Manufacturing KPIs that matter

1

OEE (Overall Equipment Effectiveness)

OEE varies by industry and optimization level. Leading factories show substantially higher OEE. Every improvement gains capacity. On a significant production line, OEE gains translate to additional volume and revenue.

2

Scrap rate / Defects per Million (DPM)

High-speed lines: manual inspection misses defects. Defects that pass = customer complaints or rework. Automated inspection + predictive alerts = better detection and higher final quality.

3

Mean Time Between Failures (MTBF)

Reactive maintenance: machine fails, production stops. Predictive maintenance: service before failure, machine keeps running. Result: progressive elimination of unplanned downtime (visible within months).

4

Energy consumption per unit

Old or poorly tuned equipment: abnormal consumption. Consumption alerts + tuning = lower electricity bills. Savings grow with production facility size.

Common Objections

Honest answers

We have an old factory — integration is impossible.

Opposite. Old machines have no sensors: we add them externally. Vibration, temperature, electrical consumption sensors. Cost: 500-1500 euros per machine. Worth it if you have downtime.

My ERP is a black box.

Sage, SAP, Oracle, Odoo: direct connection. Proprietary legacy: daily exports. Slower but works. We discuss feasibility at demo based on your system.

Implementation will be a nightmare.

5 weeks typically. One week per module, one week stabilization. If you have 10 production lines, we onboard them gradually. Weeks 1-2: first line live. Weeks 3-5: the rest.

Our historical data is messy.

We start fresh on day one. By month two, you have quality data. Prediction starts simple (obvious anomalies) and improves with time. You don't need perfect historical records to start gaining insight and making better decisions.

This will slow down our lines.

Zero impact. Sensors don't slow anything. The system runs alongside your production. Alerts only appear if there's a real problem — no false alarms from paranoia.

Frequently Asked Questions

Direct answers

How soon do we see OEE improvements?

As soon as we have one week of data: you see real bottlenecks. First gains: week 4 (anomaly alerts reduce surprise stops). Stable gains: months 3-4 (enough data for reliable patterns).

Can we keep our current systems?

Yes, 100%. You're not forced to replace your ERP or MES. Kaalytics sits alongside and enriches your data. If you change systems later, migration is straightforward.

Who gets the alerts?

You configure it: shift supervisors for production anomalies, maintenance teams for preventive alerts, plant manager for daily summary. No spam — every alert is actionable.

How do you protect proprietary recipes?

We see production data (times, defects, consumption), never recipes or formulations. Data stays with you — no permanent upload to our cloud. Annual security audit included.

What if we're not satisfied after 3 months?

Flexible subscription. Cancel without penalty. But honestly, 9 out of 10 customers see measurable gains by month 2. If nothing works, we learn why together and try a different angle.

Do we need to change our operational procedures?

Minimal. Supervisors and operators receive alerts and can act immediately. No major workflow restructuring required. The system integrates seamlessly into existing production routines and daily operations.