MedTech manufacturing operates differently from traditional high-volume production. Numerous variants, high quality requirements, and strict regulatory guidelines make processes complex. This is precisely why automation is often immediately perceived as a disproportionately large investment project and thus quickly dismissed out of hand.
In day-to-day operations, however, the greatest effort is often required elsewhere. Paper-based work and inspection plans, manual signatures, Excel add-ons, incomplete traceability, and lengthy search paths during audits or when dealing with deviations cost time and tie up skilled personnel. This is particularly significant in small-batch production.
Small production runs, therefore, are not a reason to rule out automation. They simply require a different approach.
Where the Actual Costs Arise Today
Many manufacturing operations underestimate how expensive non-standardized processes really are in day-to-day business. This becomes particularly critical in four areas:
- Documentation and record-keeping: When information is maintained manually or scattered across multiple systems, search times increase and audit risks rise.
- Traceability: Without a clear link between material, serial number, test results, and process steps, every deviation requires a time-consuming root cause analysis.
- Media breaks: Paper, Excel, scanned PDFs, and manual data transfers create sources of error, duplicate work, and a lack of transparency.
- Approval and inspection processes: When data is not generated directly within the process, it leads to longer wait times for clarifications, rework, and approval loops.
These cost drivers do not depend on high production volumes. They occur even when only a few dozen or a few hundred units are produced. This is precisely why a digital and partially automated approach can pay off early on.
A practical approach: transparency first, then stability, then automation
Anyone who jumps straight to discussing cobots or robotic cells at this stage is usually getting ahead of themselves. In regulated manufacturing environments, the transition only works if the sequence is correct. In practice, a three-step approach has proven effective.
1. Establish transparency and an audit trail
Scanners, barcodes, and digital data collection points ensure that materials, serial numbers, process steps, inspections, and approvals are traceably consolidated. This step alone reduces search times and provides greater certainty during audits and complaint resolution. A central data platform integrates the collected information into a coherent context, thereby laying the foundation for transparency, traceability, and future automation.
2. Establish Digital Assistance and Standardization
Digital work and inspection plans replace paper. Required fields, validity checks, and the automatic assignment of measured values stabilize the workflow. This reduces the stress caused by variations, shortens the training period, and increases process reliability.
3. Automate in a Targeted Manner
Once the data foundation and processes are stable, automation becomes practical—targeted specifically where it delivers measurable benefits: in repetitive inspection steps, in parts handling, or in ergonomically demanding tasks. In this environment, modular cells and cobots are generally better suited to small batch sizes than rigid, fully automated systems.
Here’s what a sensible first use case looks like
Starting point: In MedTech final assembly, many variants are handled using paper-based and inspection plans. Measurement values are transferred manually afterward, and approvals are handled via signatures. This leads to data discontinuities, follow-up inquiries to quality assurance, wait times, and gaps in traceability.
First step: It’s not about the robot, but about clean data in the process. Specifically: track-and-trace plus digital inspection plans. Serial numbers and lots are scanned, inspection characteristics are recorded directly at the workstation, critical testing equipment is integrated, and approvals are documented electronically with roles and timestamps.
Result: fewer mix-ups, shorter approval loops, a continuous audit trail, and—for the first time—reliable process data. On this basis, targeted decisions can be made about which activities can be economically automated in the next step—such as repetitive inspections or parts handling.
Why Production, QA/RA, and IT/OT Must Make Decisions Together
When projects in this environment stall, it is rarely due solely to the technology. Most often, it is because the parties involved have different priorities. Production wants stable processes. QA and RA focus on documentation, approvals, and audit compliance. IT and OT consider integration, security, data consistency, and maintainability.
Only when these perspectives are brought together does a discussion about technology turn into a sound decision. Then it’s no longer just a matter of whether an automation module makes economic sense, but rather what contribution it makes to quality, compliance, and efficiency.
Three Quick Wins to Get Started
- Standardize scanners and labels: Serial numbers, batches, and material flows are systematically recorded and linked in an audit-traceable manner.
- Introduce digital work and inspection plans: Employees receive version-controlled instructions directly at their workstations, including required fields and validity checks.
- Integrate critical test equipment: Measurement values are automatically assigned to the product instead of being transferred manually later.
These measures often yield results faster than a large-scale automation project. At the same time, they lay the foundation that makes subsequent automation modules economically viable.
Conclusion: It’s Not the Volume That Matters, but the Order
Small production volumes are not an argument against automation in the medtech industry. The starting point is more crucial. Those who first create transparency, eliminate data silos, and streamline processes lay the foundation for meaningful automation.
That’s why the discussion shouldn’t start with robotics. It should begin with how data, quality, and processes can be integrated in such a way that the next step in automation is truly successful.
If you have any further questions about automation for small batch sizes in medtech production and structured digitization (traceability, digital inspection plans), please feel free to contact our expert Michael Kelnberger, Sales Manager, Technical Sales, EDAG Engineering GmbH, or download our white paper “The Path to Meaningful Automation in Three Steps,” right here.
