Define the loss
Energy, downtime, quality, throughput, asset risk or workflow friction.
Case studies / Industrial proof
Real operating problems.Measured industrial outcomes.
Digi I4.0 starts with a business-critical plant problem, connects the right operating context and proves whether the intelligence creates measurable value before scaling.
PHARMA / CHILLER₹35Lannual savings opportunity
HEAVY INDUSTRY₹52.4Lno-hardware annual savings identified
CLOSED-LOOP CONTROL2.2%plant-wide gas saving
VALUE MODELProblem → Context → Intelligence → Action → Outcome
01 / From pilot to performance
Every case begins with the outcome that must improve.
Connect the context
Use existing plant data first. Add DigiGateway where direct asset connectivity is missing.
Validate the intelligence
Start with open-loop or human-in-the-loop recommendations where appropriate.
Measure the outcome
Scale only after a meaningful operational and financial signal is visible.
02 / Quantified outcomes
Three operating problems.Three measurable value stories.
These featured cases show how data becomes operational context, then decision support, controlled action and measurable impact.
ANNUAL OPPORTUNITY₹35Lidentified savings
Chiller Optimization for Temperature Stability and Energy Savings
Optimize chilled-water and condenser-water flow without putting process stability, energy efficiency or utility reliability at risk.
DigiTwin analyzed the chiller-plant operating context and identified a practical condenser-water optimization opportunity that reduced avoidable over-pumping while protecting critical operating limits.
An opportunity of up to ₹35 lakh per year was identified while maintaining the expected condenser delta-T operating range.
Temperature stabilityCondenser delta-TLoad handlingHuman-in-the-loop
NO-HARDWARE SAVINGS₹52.4Lidentified / year
Optimization Layer for High-Energy, Asset-Intensive Operations
Optimize kilns, furnaces, billet heaters, compressors, pumps, utilities and carbon-capture assets without affecting throughput or quality.
A data-driven optimization layer synchronized process telemetry, energy data, tariff windows, safe operating limits, historical best states and simulated trade-offs into open-loop recommendations validated through supervised A/B testing.
Energy intensity reached 6.77 kWh/billet over 90 days. ₹52.4 lakh/year in no-hardware savings was identified, including ₹21.9 lakh/year from optimized idle and zero-output states.
6.77 kWh/billetHistorical best statesSupervised A/B testingOpen-loop recommendations
PLANT-WIDE GAS SAVING2.2%closed-loop result
Energy Optimization at Brick Manufacturing
Reduce natural gas consumption in brick-kiln operations while maintaining product quality and throughput.
DigiTwin supported industrial closed-loop control for burner-zone gas optimization, making more than 2,000 real-time setpoint adjustments per day and adapting profiles for different brick conditions.
2.2% plant-wide gas saving, translating to 9–10% savings at burner-zone level. The deployment has been operational since November 2023.
2,000+ adjustments/day9–10% burner-zone savingAdaptive profilesClosed-loop control
03 / More operating use cases
Proof growsacross the industrial stack.
These additional examples show how the same problem-first approach can extend beyond energy into quality, maintenance and asset intelligence.
DIGIVISI / PRECISION MANUFACTURING
Computer Vision Inspection for Dimensional Measurement
Automatic image capture, tolerance-based PASS/FAIL decisions and traceable quality reporting reduce manual dependency and inspection inconsistency.
Quality intelligence →
DIGIWARE / SPECIALTY CHEMICALS
Preventive Maintenance and Work Order Automation
Digital checklists, automated maintenance requests, execution notifications and closure tracking improve maintenance visibility and reduce manual follow-up.
Workflow intelligence →
DIGITWIN / ASSET HEALTH PILOT
Conveyor Belt Digital Data Twin Pilot
A focused pilot connects inspection data, operating signals and maintenance history into a defect register, degradation trend and qualified risk horizon.
Asset intelligence →04 / What these cases prove
Build for adoption.Not experiments.
Real industrial problems
Every engagement starts with a measurable operating constraint, loss or risk.
Existing data first
Use current plant systems and feeds before adding unnecessary infrastructure.
People in the loop
Recommendations can be validated by operators and engineers before control authority expands.
ROI before scale
A focused pilot should produce a business signal strong enough to justify what happens next.
CASE STUDIES / DIRECT ANSWERS
What industrial teams usually ask before starting.
Are these case studies based on real industrial use cases?+
Yes. The featured quantified cases represent Digi I4.0 industrial solution work across energy optimization, process intelligence and closed-loop control. Additional pilot and solution examples are identified separately where appropriate.
Can Digi I4.0 use our existing data and systems?+
Yes. DigiTwin is designed to use available data from PLC, SCADA, EMS, MES, databases, APIs, files and other feeds. DigiGateway can be introduced where direct asset-level connectivity is missing.
Do we need to start with a full Digital Twin?+
No. The recommended path is to begin with one measurable use case, prove the operating and financial value, then scale toward broader DigiTwin maturity.
Can an engagement begin in open-loop mode?+
Yes. Human-validated recommendations can be used first. More automated or closed-loop control should follow only after operational validation, safety checks and customer approval.
HAVE A SIMILAR OPERATING PROBLEM?
Bring us the plant problem. Start with the evidence.
We can help identify the data required, the most practical DigiTwin starting point and the outcome that should be proven before anything scales.