About us
So production pays off again.
We make sure manufacturing companies always know what their work actually costs and whether they're on target — because no one can run a business well on a number that's only approximate.
Where we come from
2021
The question
At the Institute of Production Engineering and Machine Tools (IFW) at Leibniz University Hannover, researchers studied how reliable operational data actually is in mid-sized contract manufacturers. Sixteen companies, one sobering result.
2019–2022
The answer
A research project develops a method that derives what's actually happening in production from machine and localization data — without anyone entering anything by hand.
2022
The founding
The method became a product, and the product became a company.
Today
In active use
Three contract manufacturers, more than 50 machines, more than 1 million events processed — including in aerospace and machinery/plant engineering.
The founders
Dr.-Ing. Siebo Stamm
Market & Sales
Studied mechanical engineering and industrial engineering at TU Braunschweig, then worked in PLC programming and project management in renewable energy. Went on to research capacity-oriented production planning and fine-scheduling of machining processes based on machine data at IFW Hannover. Later led operations in the aerospace sector.
During my time as plant manager, reliable data was scarce. A lot was captured, almost none of it connected. Searching and waiting were part of daily work. I still made decisions — just from gut instinct. That works, often — and you never notice when it didn't. That's exactly what I wanted to stop doing.
Dr.-Ing. Daniel Arnold
Technology & Software
Studied mechatronics and mechanical engineering at Leibniz University Hannover, then worked as a research associate at the Industry 4.0 Competence Center, followed by the project "Localization and Communication System for Concurrent Manufacturing Planning and Control" at IFW Hannover.
I worked with machine data early on. Getting access was never the problem. The problem was that a signal alone means nothing: it says a spindle was running, not for which order or at what cost. That link was always made after the fact — from reports and memory, exactly when it's worth the least. The question never let go of me: why not connect the data right where it's generated?
The people who'll be on your shop floor
Oqbah Abbas
Software Engineer
Turns ideas into working, scalable software
Christian Heller
Solution Engineer
Brings the solution to companies and looks after customers end-to-end
How we think
Most vendors come from one direction: from software, from consulting, or from mechanical engineering. We know all three. The problem we solve sits exactly in between.
The shop floor
We've worked in production companies, not just read about them. We know why bookings get batched at the end of a shift, and why nobody fills out a form that gives them nothing back.
The IT
Grown system landscapes, aging controllers, an ERP with fifteen years of customizations. We build for reality, not the ideal case.
The research
Two dissertations and a study across sixteen companies, before the first line of code existed. We measured the problem before we solved it.
First, we get more out of what's already there. Digitalization isn't an end in itself. We don't digitalize everything — only what makes a decision better. So the first step is almost always the same: getting more out of the data your business is already generating. Only after that do we talk about anything new.
And everything depends on one condition: the data has to be correct. That's our actual job.
We're at home anywhere from the shop floor to the balance sheet. Honestly, though — if we had to choose, we'd choose the shop floor.
Knowledge transfer isn't a bonus. It's the requirement.
Software alone doesn't change a business. Deciding based on data and running paperless production is a way of working, not an installation. It only takes hold once the people in your business understand where a number comes from and why it's correct. That's why we pass on what we know. What's in our dissertations and research projects doesn't stay in the publications — it reaches your people: on the shop floor, in the office, in production planning. We want to enable businesses.
Dissertation
Automatisierte Betriebsdatenerfassung mittels ereignisgesteuerten Fertigungsinformationen aus Lokalisierungs- und Maschinendaten
Arnold, D. · 2025 · Dr.-Ing. Dissertation, PZH Verlag, Garbsen
Dissertation
Integrative Prozessfeinplanung zur prädiktiven Toleranzeinhaltung basierend auf maschinenspezifischen Daten
Stamm, S. · 2025 · Dr.-Ing. Dissertation, PZH Verlag, Garbsen
Research and publications
- 01Islam, R., Wand, A., Röder, Ch., Stamm, S., Dayeg, A., Winter, F., Salaj, L., Noske, H., Denkena, B., Diedrich, Ch. (2023): Erfahrungsbericht bei der Umsetzung der VWS Type 3 Interaktionen in einer Maintenance-Anwendung, Kommunikation in der Automation: 14. Jahreskolloquium, 21./22.11.2023, Magdeburg: Tagungsband (Jumar, Ulrich et al.).
- 02Denkena, B., Wichmann, M., Arnold, D. (2022): Erfasste Betriebsdaten und ihre Qualität, ZWF, Vol. 117 (2022), Nr. 12, S. 847-850.
- 03Denkena, B., Dittrich, M.-A., Arnold, D. (2021): Auftragslokalisierung erhöht die Fertigungstransparenz - Hybrides Datenerfassungskonzept berechnet Betriebsdaten und Fertigungskosten, VDI-Z, 163 (2021) Nr. 4, S. 59-62.
- 04Arnold, D., Wilmsmeier, S., Denkena, B., Dayeg, A. (2021): Betriebsdaten und ihre aktuellen Potenziale, ZWF, 116 (2021) 11, S. 852-855.
- 05Denkena, B., Dittrich, M.-A., Stamm, S., Wichmann, M., Wilmsmeier, S. (2021): Gentelligent processes in biologically inspired manufacturing, CIRP Journal of Manufacturing Science and Technology, Vol. 32 (2021), S. 1-15.
- 06Arnold, D., Rehe, M. (2020): Retrofitting einer Wasserstrahlanlage, Digitalisierung erfolgreich umgesetzt, 2019, Ausgabe Nr. 3, S. 8-13.
- 07Arnold, D. (2020): Transparenz in der Produktion, phi, Produktionstechnik Hannover informiert, 19.05.2020, S. 3.
- 08Stamm, S., Denkena, B., Dittrich, M.-A., Krause, R. (2020): Wissensbasierte Prozessfeinplanung bei Drehprozessen - Expertenwissen digitalisieren und aus vergangenen Prozessen automatisiert lernen, VDI-Z BD., 162 (2020) Nr. 4, S. 18-20.
- 09Denkena, B., Dittrich, M.-A., Wilmsmeier, S., Stamm, S. (2020): Optimization of delivery adherence based on capacity planning and bid pricing, Production Engineering Research and Development (WGP), 14 (2020) Number 3, April 2020, S. 309-318.
- 10Stamm, S., Arnold, D., Rehe, M. (2019): Licht im IIOT-Dschungel: Plattformen für produzierende KMU - Potenziale und Nutzen, Mittelstand-Digital Magazin, Ausgabe 12, S. 13-18.
- 11Stamm, S., Arnold, D., Rehe, M. (2019): IIOT Plattformen für produzierende KMU, Schriftreihe des Mittelstand 4.0-Kompetenzzentrums Hannover, Ausgabe 2, S. 16-21.
- 12Denkena, B., Arnold, D., Sperling, M. (2019): Perspektiven vernetzter Systeme für die Intralogistik, Logistics Journal, 2019, S. 9.
- 13Arnold, D., Lorenz, L., Asche, E. (2019): Windkraft: mobile Endgeräte zur Inspektion, Schriftreihe des Mittelstand 4.0-Kompetenzzentrums Hannover, Ausgabe 2, S. 4-9.
- 14Denkena, B., Dittrich, M.-A., Stamm, S.C., Prasanthan, V. (2019): Knowledge-based process planning for economical re-scheduling in production control, 52nd CIRP Conference on Manufacturing Systems, 12-14 June 2019, Ljubljana, Slovenia, Procedia CIRP 81 (2019), S. 980-985.
- 15Denkena, B., Grove, T., Stamm, S., Vogel, N., Nordmeyer, H. (2019): Verzug additiver Bauteile. Einfluss der Nachbearbeitung auf den Eigenspannungszustand, Konstruktion, Ausgabe 3, S. 11-13.
- 16Denkena, B., Grove, T., Vogel, N., Stamm, S. (2018): Additives Potenzial für die subtraktive Prozesskette, MM – Maschinenmarkt, Ausgabe 15 (2018), S. 32-36.
- 17Denkena, B., Grove, T., Stamm, S., Vogel, N. (2018): Additive Fertigung mittels Lichtbogenauftragschweißen, World of Metallurgy - Erzmetall 71 No. 3, S. 161-164.
- 18Denkena, B., Dittrich, M.-A., Stamm, S. (2018): Dynamic bid pricing for an optimized resource utilization in small and medium sized enterprises, 11th CIRP Conference on Intelligent Computation in Manufacturing Engineering, Procedia CIRP 67, S. 516-521.
- 19Stamm, S., Winter, F., Keunecke, L. (2018): Dynamische Kapazitätsplanung und -steuerung mittels ERP und MES, VDI-Z, 160, Nr. 6, S. 24-26.
Open positions
Solution Engineer, Production Data
You connect machines, understand production processes, and translate between the shop floor and software.
Nothing that fits? If you can think in both production and software, write to us anyway.