Case Study openmaind Planning Manufacturing · SMT

4 robots. 642 transports a day.
Payback in 9.4 months.

How a Spanish SMT electronics manufacturer used openmaind Planning to model 642 daily transports, size an AMR fleet, and calculate a real ROI — without a single vendor bias.

Planning is one of three openmaind modules — built specifically to size, simulate, and justify AMR deployments before any vendor is involved.

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642
transports per day — one every ~2 minutes
24/7
operation · 350 days/year · five SMT lines
9.4 month
payback period on a €229k AMR investment
01 — The situation

642 transports a day.
The data was there. But no tool to model it.

A five-line SMT electronics plant running 24/7, 350 days a year. 13,200 PCBs per day — the equivalent of 300,000 placed components per hour. Every day: 1,900 component reels replenished, 264 magazine changes, 286 KLTs moved across the facility.

Ten full-time workers handled nothing but internal transport. Annual personnel cost: €313,500. The question wasn't whether this could be automated. It was how many robots, what kind, what they'd cost, and when it would actually pay back.

Nobody in the plant could answer that.

13,200
PCBs / day
1,900
reels / day
264
magazines / day
286
KLTs / day
02 — Why this matters for manufacturers like you

If you know you need automation but don't know where to start, you're not alone.

Most manufacturers facing cost pressure already suspect intralogistics is the right place to automate. What they're missing is a neutral, data-based answer to the questions:

Without those answers, every conversation with a vendor becomes a pitch. openmaind Planning is built to answer them before any vendor gets involved.
natural language
VDA 5050 ready
Hardware-agnostic
03 — The openmaind approach

Three steps. Infrastructure-free.
Vendor-independent.

No system being sold on the side. No retrofit required. No production downtime.

01

Capture the current state

We record every transport movement in your plant without touching your infrastructure or interrupting production. Sources, lines, buffers, finishing — all movements, cycle times, and distances.

02

Simulate with AI

Run "what-if" scenarios on your actual flow to:

  • Evaluate new layouts or conversions
  • Change fleets
  • Reorganize traffic flows
  • Prepare or secure automation
03

ROI and roadmap

A clear decision basis — savings potential, payback period, fit-for-purpose technology, phased implementation plan. All based on your actual operating data — not on assumptions.

See it in action — openmaind Planning demo

Simulate your own plant — in natural language.

Watch how openmaind Planning models a real warehouse, sizes a fleet, and returns a payback answer — from a plain-language question.

04 — The results

What came out of it.

Spanish SMT Electronics · operational improvements
4

AMRs replaced 10 internal-transport workers.

2 magazine-carrier AMRs + 2 KLT-carrier AMRs, fully orchestrated across the five production lines.

Investment (CapEx)

2× KLT-carrier AMRs€70,000
2× Magazine-carrier AMRs€90,000
Fleet software + WMS integration€34,000
Engineering + commissioning€25,000
Infrastructure (charging, WiFi, markings)€10,000
Total CapEx€229,000

Savings & payback

10 workers × €31,350€313,500 / yr
− AMR operating costs−€20,800 / yr
Net annual savings€292,700
Payback period9.4 months
Conservative scenario
250 operating days/yr → payback extends to 14 months
05 — Why neutral matters

openmaind holds zero partner agreements with AGV or AMR manufacturers.

Our analyses and simulations are independent — because they have to be. That's the only way we can deliver what manufacturers actually need: an honest assessment, without hidden interests.

openmaind Planning is our AI platform for infrastructure-free transport analysis and scenario simulation. Built from the factory floor up, for manufacturers who need real, decision-grade answers before they buy anything.

We had the feeling for years that more was possible. But nobody could tell us what exactly, and what it would bring — without trying to sell us a system at the same time. openmaind delivered exactly that.
Dr. Michael Reip and Christoph Zehentner — co-founders of openmaind
The team behind openmaind

Built by people who've spent careers on the factory floor.

openmaind was founded by Dr. Michael Reip and Christoph Zehentner — two engineers with a combined background in industrial AI, simulation, and intralogistics operations spanning academic research, plant-floor engineering, and enterprise software.

Their shared view: most manufacturers don't fail at automation because the technology isn't ready. They fail because nobody gives them a neutral, data-based answer to the questions that actually matter — before the first robot is bought.

DR. MICHAEL REIP · CHRISTOPH ZEHENTNER · CO-FOUNDERS

Ready to find out what's possible in your plant?

A neutral first look at where automation actually pays off in your operation — before you invest a euro.

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30 minutes · no pitch · no commitment