Make Every Machine Smarter. Every Shift More Productive.
Monitor production, predict failures, trace quality, and track remote assets in real time—without replacing a single machine.
Why Choose S2R2 ?
Because you don’t just need visibility—you need measurable improvements
We help you solve real shopfloor challenges: untracked downtime, operator inefficiency, and slow decisions. Here’s how S2R2 makes a difference
Smart Integration
No replacements needed—we connect directly to your existing setup. Most clients see a 10–30% boost in utilization within weeks
Quick Setup. Fast ROI.
Live in 2–3 weeks, with visible impact in the first 30 days—reduced idle time, faster shift planning, and better output control
Insights That Drive Action
Get real-time visibility into top losses, OEE, and operator performance. Our clients have improved throughput by up to 18%
Hands-On, Local Support
We stay involved post-deployment—resolving issues, fine-tuning systems, and helping you scale. 94% of clients expand to more machines within 6 months
Powerful Solutions for Smarter Manufacturing
S2R2 delivers modular, scalable IoT solutions designed to reduce downtime, ensure compliance, and optimize every stage of your operations.
0
+
Factories Enabled with Smart Manufacturing
0
+
Machine Hours Monitored Monthly Across Clients
0
%
Average Throughput Improvement Reported by Clients
0
%
Clients Who Expanded to More Machines After Phase 1
Take a look at some of our deployments
Industry: CNC Job Shop / Precision Components
Challenge: No visibility into part counts, machine idle times, or cycle time delays across 10+ CNCs with varying OEMs.
S2R2 Solution: Installed non-intrusive production monitoring system capturing part count, run-time, and downtime metrics across all CNCs.
Outcome:
– Live part counts across machines
– 18% reduction in idle time
– Shift-wise output reports and operator performance insights
Industry: Pharma Equipment / Blister Packing Line
Challenge: Unplanned machine stoppages due to undetected motor heating and mechanical vibration on packing lines.
S2R2 Solution: Vibration + temperature sensors with real-time alerts, without modifying OEM systems.
Outcome:
– Early warnings on abnormal vibration and heat
– 23% drop in unplanned downtime
– Improved OEE and uninterrupted batch production
Industry: Sealing Systems Manufacturing
Challenge: Manual forklift dispatching led to missed calls, delays, and material flow disruptions.
S2R2 Solution: Push-button-based forklift call system with automated queuing and driver routing.
Outcome:
– Cut wait times by over 40%
– Improved driver accountability
– Material flow became fully traceable and system-driven
Industry: Foundry / Core Shop
Challenge: Rejected cores due to undetected temperature mismatch and aging PLCs.
S2R2 Solution: Custom CBM module integrated with legacy PLC for real-time current and temperature tracking.
Outcome:
– Real-time temperature balancing
– Reduced rejection at source
– Accurate part counts and predictive heating system insights
Trusted By Industry Leaders
What our customers are saying
–Supervisor, Auto Components Plant
We track 120+ DG sets live across cities. Service now runs on data—not complaints.
–Operations Head, Equipment Rental Company
We isolated a faulty batch in 10 minutes during an audit. Complete logs, zero stress.
–Quality Head, Auto component manufacturer
See What Real-Time Visibility Can Do for You
No pressure. Just a walkthrough of how your machines can start talking back.
Resources 38% Downtime Reduction in 30 Days
Case Study
Plant Engineer, Automotive Components Unit, Chennai
S2R2’s condition monitoring gave us real-time visibility into vibration and temperature issues. We now detect faults early, plan maintenance better, and prevent breakdowns before they affect production or quality.
White Paper
–Maintenance Head, Precision Components Manufacturer, Pune
After implementing S2R2’s Condition Monitoring, we reduced unplanned breakdowns by 40% in just 90 days. Our maintenance team now acts on early alerts, not emergency calls.
Within couple of weeks, we got insightful data about machine downtime occreances and real reasons. After acting upon those reasons we could improve machine utilization by 15 to 20 percent