ROI CALCULATOR

See what EdgeBits could save your plant

Two ways to model your savings. Pick the one that matches how you already think about your operation. Figures are in ₹ because that is where we sell first; the platform itself is currency-neutral.

Your plant

All values annual unless noted. Numbers in ₹.

Rule of thumb: 2 to 4 times revenue-per-production-hour. For a ₹200 Cr plant on 2 shifts, revenue-per-hour is about ₹50,000, so a realistic downtime cost sits in the ₹1 to ₹2 L range. Higher for continuous processes with customer penalties.
Most mid-market plants that measure it land in the 10 to 30 hours/month range; world-class TPM sustains under 8. A single busy line at ~90% availability alone loses ~40. Enter your plant's actual figure. If you don't track it yet, that's the first thing EdgeBits gives you.
Roughly 2 to 5% of revenue for light manufacturing (auto parts, FMCG), higher for energy-intensive sectors (textile spinning, foundry, pharma). Default assumes ~3% of a ₹200 Cr plant.
Vendor-hosted dashboards, per-meter or per-tag hosting fees, per-user portal seats. Data goes to their server; EdgeBits keeps it on yours.
AVEVA PI, FactoryTalk Historian, Wonderware, Ignition — Edge Analytics replaces the licence line.
Shift incharges typing daily production numbers into Excel or SAP.
Adds a scrap / rework reduction estimate for process-drift catches.

Your OEE

Speak the language your TPM manager already uses. Availability × Performance × Quality.

30%78%100%
30%82%100%
70%97%100%
A
78%
P
82%
Q
97%
OEE
62%
Operators write reasons on a clipboard next shift. Adds a 100%-capture uplift + Top-Loss-report FTE savings.
AVEVA PI, FactoryTalk, Wonderware — Edge Analytics replaces the licence.

Your annual savings

Live: updates as you type on the left.

Year-1 savings estimate
₹0
Across the buckets below.
Year-1 numbers. Steady state (18–24 months) is usually 1.5–2× this. Plants that install and don't act on alerts save close to 0%. Range depends on baseline maturity, sector, and demand mix — see "How we compute this" below.

Breakdown by bucket

Downtime reduction ₹0
Energy savings ₹0
Vendor-hosted dashboard eliminated ₹0
Historian licence eliminated ₹0
Manual reporting saved ₹0
Quality & scrap reduction ₹0
Typical payback: 6 to 12 months at this savings profile. Exact payback depends on plant size, deployment scope, and which buckets you prioritise. We'll walk through it in the call.
Get a custom proposal See how "Ask Your Plant" works

How we compute this

This calculator is a first-order estimate, not a proposal. The multipliers below sit in the conservative half of the range reported by 2025 industry benchmarks. Every number cited here has a URL you can check. We treat "median-of-vendor-claims" as a red flag, not a source.

What the numbers below represent: year-1 outcomes for a typical mid-market industrial plant that (a) implements EdgeBits, (b) uses the data, and (c) has a maintenance / operations team that acts on the alerts. Steady-state results at 18–24 months are usually 1.5–2× these numbers. Plants that install and don't act on alerts save close to 0%.

General mode · what we use

Downtime reduction 25–35% of unplanned downtime avoided, year 1. Industry range: 30–50% (2026 predictive-maintenance benchmark), 35–45% (US DoE data), up to 70–90% at maturity. We use 25–35% because year 1 rarely hits the ceilings.
Energy savings 5–10% of annual energy bill, year 1. Industry range: 8–25% (2025 monitoring guide); 15–25% with structured programs (sub-metering ROI). We use the low half because sub-metering alone lands ~8%; structured programs take a year to reach 15%+.
Vendor-hosted dashboard eliminated ₹5 L per plant per year, only if you currently pay a meter / historian / MES vendor for a hosted dashboard or portal. Meter-supplier SaaS: typically ~₹1000–1500 per meter per month + per-user portal seats. Twelve meters + a handful of users lands ~₹3 L/yr; twenty-plus meters or multiple sites scales linearly. See Take back your energy data for the worked math. If your dashboard is Grafana / Power BI on infrastructure you already own, untick this.
Historian eliminated ₹15 L per plant per year, only if you currently pay for AVEVA PI, FactoryTalk, Wonderware, or Ignition. Real range varies enormously by tag count and vendor. If you use Grafana + InfluxDB (free), untick this; the saving doesn't apply.
Manual reporting saved 0.4 FTE = ₹8 L/yr, only if shift reports, ERP feeds, or energy logs are typed by hand today. Automated plants: untick.
Quality & scrap 0.3% of annual revenue, only for continuous processes (pharma, chemical, FMCG, food). Genuinely conservative floor. Industry range is 1–3% at steady state; we don't claim that year 1.

TPM · OEE mode · what we use

Availability lift +3 to +5 pp year 1. Industry range: 3–8 pp typical (see 2026 OEE benchmarks). Steady state after 18–24 months is often 2× this.
Performance lift +2 to +4 pp year 1. Once Small Stops and Slow Running are visible in the data.
Quality lift +1 to +2 pp year 1 on plants already > 95% Q. SPC bands on CTQ variables. Bigger lifts happen only when the current Q floor is below 90%.
A / P / Q are not fully independent Fixing Small Stops moves hours between the A and P buckets rather than adding to both. The calculator applies a 15% coupling discount to reflect this; naive addition would over-estimate.
Top-Loss boost 1.3× on the component that owns your declared Top Loss. Focused Improvement teams reliably outperform generic-lift assumptions on the one loss they attack. No academic single-number source; this is directional.
OEE → ₹ conversion New output value = revenue × (new OEE ÷ old OEE − 1) × 12% contribution margin. Standard TPM finance framing. See caveat below.
Reason-code capture ₹6 L/yr per plant. Manual logs miss ~30% of stop events; automated capture ≥ 50% more accurate (2025 downtime-tracking benchmark). Poor OEE data quality costs plants 8–15 pp of recoverable efficiency (iFactory 2025).
Historian eliminated ₹15 L/plant/year. Same as general mode.
Two honest caveats

Contribution margin varies by sector. Default 12% (mid-market industrial). FMCG and pharma see 20–40%; steel and commodity plants see 5–15%. Your proposal uses your actual margin.

The OEE-to-₹ math assumes you can sell the extra output. Demand-limited plants (order book full at current pace) convert OEE lift to cost reduction rather than revenue growth. Same rupee number, different lever.

Not modelled: EdgeBits licence + AMC + implementation cost, ramp-up curve, and implementation risk (~30% of industrial-IoT pilots stall). This is a first-order savings estimate, not a payback calculator.

Every multiplier above ties back to a dated 2025–2026 source, linked inline where it is used. If a number changes here, the source changes first — we treat “median of vendor claims” as a red flag, not a citation.

Abbreviations used on this page
pp — percentage points. The absolute gap between two percentages. Availability going from 78% to 82% is a +4 pp lift, not a "+4%" lift.
FTE — Full-Time Equivalent. One person working full-time for a year. "0.4 FTE" = the labour hours of one person 40% of the time (roughly 2 days a week).
OEE — Overall Equipment Effectiveness. A × P × Q. The one number TPM programs live by.
A · P · Q — Availability × Performance × Quality. The three components of OEE.
TPM — Total Productive Maintenance. Nakajima's 1988 framework; still the industry standard.
CTQ — Critical To Quality. A process variable whose drift moves the defect rate (temperature, fill weight, coating thickness, viscosity, conductivity).
SPC — Statistical Process Control. Continuous monitoring of CTQ variables against control bands.
₹ L / ₹ Cr — Lakh (1 L = 100,000) / Crore (1 Cr = 10,000,000). Indian numbering.
THE ASSISTANT ON TOP

Ask your plant in plain English

The number above is what EdgeBits saves you on the P&L. The reason it works: your team stops digging through dashboards and starts asking questions in the language they already use.

"Which plant had the worst OEE last week?" · "Why is line 3 slower today?" · "Show me pump current just before the outage."

Role-scoped Audit-stamped answers Cloud or self-hosted AI Data stays with you
See how it works

Talk to us

Show us the numbers you put in the calculator and we'll build a pilot-scope proposal for one of your plants. No pitch deck, no pressure.

  • 30-minute call with an industrial IoT engineer
  • No credit card, no commitment
  • We'll walk through your specific plant and show the payback line by line

Or reach us directly at

hello@edgebits.io