The Business Case for TSN over 5G: From Deterministic Networks to Measurable Productivity Gains
Cumucore’s TSN over 5G solution has been shortlisted for the MWC GLOMO Awards, marking an important industry validation of our work in industrial connectivity. At the same time, Time-Sensitive Networking (TSN) over 5G is generating significant momentum across the manufacturing and automation ecosystem. Often described as the “holy grail” of factory communications, TSN over 5G addresses one of the most critical gaps in Industry 4.0: deterministic, time-synchronized wireless connectivity suitable for mission-critical control systems.
With 2026 emerging as the inflection point for broader commercial adoption, TSN over 5G is no longer a research topic or pilot exercise it is transitioning into scalable, production-grade deployments.
However, rather than focusing on technology alone, it is worth asking a more important question: what is the actual business case, and why should industrial decision-makers pay attention now?
TSN is commonly described as a deterministic network. In simple terms, this means that key network characteristics, latency, jitter, and packet delivery, can be precisely defined and reliably guaranteed. Determinism clearly improves reliability and reduces packet errors, but this alone does not justify the investment. High reliability is a baseline requirement in industrial environments; it does not, by itself, unlock significant productivity gains or cost savings.
The real business value of TSN over 5G lies elsewhere. When combined with accurate, shared time across all devices, TSN enables tightly synchronized industrial operations. In practice, this allows factories to move away from conservative, event-driven automation toward fully time-coordinated processes. Multiple studies and real-world deployments indicate that this shift can deliver up to 30% productivity improvement on the factory floor compared to traditional automation architectures.
Traditional factory automation with best effort communication
Traditional factory automation is fundamentally event driven. Sensors periodically report values and based on these inputs the PLC adjusts the manufacturing process according to predefined control logic. Each device operates on its own local clock, which inevitably drifts over time. As a result, control decisions are made based on message arrival order and handshake signals such as “ready,” “load,” and “done”, rather than on a shared and precise timeline.
Because there is no common notion of time, actions cannot be scheduled deterministically. Instead, systems must wait for confirmation that the previous step has been completed. To remain safe, automation engineers compensate for uncertainty by adding conservative margins and guard times. This approach works, but it is inherently inefficient.
In our simple example, a robot loading an autonomous mobile robot (AMR), this uncertainty becomes very visible:
- The loading robot waits for confirmation that the AMR has fully stopped.
- The AMR waits for the robot’s confirmation before unlocking the cargo platform.
- Additional guard times are added to avoid collisions and near-miss situations.
None of this waiting adds value. Delay exists solely to compensate for the lack of deterministic timing.
Where is the time lost?
In best-effort communication systems, the following guard times are typically introduced per loading cycle:
| Source of delay | Typical guard time |
|---|---|
| AMR full stop confirmation | 100–300 ms |
| Robot approach delay | 100–200 ms |
| Safety interlock confirmation | 50–150 ms |
| Vision revalidation | 50–200 ms |
| Communication jitter margin | 50–100 ms |
Total artificial delay per cycle: 350–950 ms.
This delay is not caused by slow robots or limited mechanics. It is pure coordination overhead introduced to handle uncertainty in communication and timing. When multiplied across hundreds or thousands of cycles per day, these milliseconds translate directly into lost throughput, underutilized assets, and higher cost per produced unit.
TSN over 5G Reduces Waiting Times Through Deterministic Coordination
In a TSN-enabled 5G system, waiting times can be significantly reduced because the robot and the AMR operate on a shared, highly accurate clock. From a control perspective, they can be treated as a single, time-coordinated logical system rather than two independent machines exchanging transactional messages.
Because actions are scheduled against a common timeline, the loading robot and the AMR no longer need to rely on request–response handshakes. Instead, both sides commit to time-based behavior:
- The AMR commits to being fully stationary at T = 12.000000 s.
- The robot starts its approach at T = 12.000500 s.
- Load transfer occurs at T = 12.004000 s.
This approach replaces uncertainty with predictability. Guard times are no longer needed, because each component knows when the other will act, not just that it has acted.
Eliminating Guard Times
With accurate timing and scheduled control, conservative margins can be removed and replaced by deterministic commitments. Typical reductions per operation are shown below:
| Operation | Typical improvement |
|---|---|
| AMR stop, robot approach | −100 to −250 ms |
| Robot gripper synchronization | −50 to −150 ms |
| Safety zone transitions | −50 to −100 ms |
| Vision alignment | −50 to −150 ms |
Recovered time per cycle: 250–650 ms.
System-Level Impact on Cycle Time
At the system level, the improvement can be even greater. Deterministic timing does not only remove waiting; it also allows:
- Earlier robot prepositioning.
- Faster but controlled AMR deceleration.
- Tighter safety envelopes without reducing safety integrity.
As a result, a full loading cycle may look as follows:
| Loading process | Cycle time |
|---|---|
| No accurate timing | 6.0–8.0 s |
| Accurate timing (TSN over 5G) | 5.2–6.5 s |
Net Productivity Improvement
Based on figures above:
- Absolute cycle time reduction: 0.8–1.5 s.
- Relative improvement: approximately 10–30% per cycle.
TSN over 5G does not make robots mechanically faster. It removes uncertainty, allowing machines to act with confidence instead of waiting for confirmation. The business impact comes from turning milliseconds of wasted time into productive motion, cycle after cycle, across the entire factory floor.
What Does This Mean for Productivity and Throughput?
In our example, the loading and unloading operation becomes one to two seconds faster per cycle because guard times can be significantly reduced. On its own, this may sound incremental. The key question, however, is whether this improvement is meaningful at the system level and whether it justifies investment in TSN over 5G.
To answer that, we need to look at throughput rather than individual cycle time.
For a simplified but realistic scenario, let us assume:
- One AMR loading per cycle.
- Continuous 24/7 operation.
- Cycle time reduced by 1.2s from 7.0 s to 5.8 s.
Throughput Impact:
| Metric | Traditional OT | With TSN over 5G |
|---|---|---|
| Cycles per hour | ~514 | ~621 |
| Gain | — | 21 % |
| Extra loads per day | — | ~2,600 |
What is important to note is that this gain comes without increasing robot speed, payload, or mechanical stress. The improvement is achieved purely by removing waiting caused by uncertainty. From “Wait and See” process model to “Predict and Execute” process model. In a robot–AMR loading scenario, accurate timing fundamentally changes the control model:
- Traditional systems operate on “wait and see” logic.
- TSN-enabled systems operate on “predict and execute” logic.
A couple of seconds saved in a single cycle may appear small, but when multiplied across thousands of cycles per day, it becomes a material productivity improvement. Delay is not productive motion – it is pure waiting. From this perspective, TSN over 5G delivering 20–30% faster loading cycles is a realistic and defensible claim for many industrial use cases.
Additional Operational Benefits
The business case does not stop at raw throughput. Accurate timing also enables several secondary benefits that further improve overall equipment effectiveness (OEE):
- Fewer emergency stops.
- Typically, 5 – 15% availability improvement, as timing-related false positives are reduced.
- Lower mechanical wear.
- Smoother motion profiles and fewer micro-stops lead to longer maintenance intervals.
- Higher repeatability.
- Better synchronization reduces misalignment, scrap, and rework.
When these effects are included, overall cell productivity can improve by 20–35%, not just through faster cycle times but through higher availability and quality.
A Final Note on Real-World Results
This example is intentionally generic. Actual savings depend at least on:
- The degree of coordination between machines.
- Safety and vision system involvement.
- Current levels of conservatism in control logic.
That said, the underlying principle remains the same: TSN over 5G turns lost time into productive time and that is where the business case comes from.
Conclusion: Determinism is the value, not the optimization
TSN over 5G should not be viewed as a marginal optimization to existing OT systems. It is a foundational enabler of deterministic automation. The value does not come from making individual machines faster, but from removing uncertainty from how machines coordinate, interact, and make decisions.
Traditional OT architecture is built around best-effort communication and local clocks. To remain safe and reliable, they compensate with conservative margins, guard times, and reactive control logic. This approach works, but it hard-codes inefficiency into the system. Time is treated as an approximation rather than a guaranteed resource.
TSN over 5G fundamentally changes this model. By providing a shared, accurate time base and deterministic communication characteristics, it allows automation systems to move from event-driven waiting to time-based execution. Machines no longer need to ask whether something has happened, they know when it will happen. This shift enables tighter coordination, higher throughput, improved safety, and better use of existing assets without increasing mechanical stress.
From a business perspective, this is why TSN over 5G matters. The measurable gains, 20–30% faster cycles, higher availability, and improved quality, are not the result of incremental tuning. They emerge because determinism removes structural inefficiencies that could not be addressed before. In many cases, these gains are achieved with the same robots, the same AMRs, and the same factory layout.
As factories become more autonomous, mobile, and software-defined, the need for deterministic behavior will only increase. In that context, TSN over 5G is not a “nice-to-have” feature or a future optimization. It is the architectural foundation that enables scalable, predictable, and economically viable automation.
In short, without deterministic timing, advanced automation cannot reach its full potential and TSN over 5G is what makes deterministic automation possible in modern factories.
CONTACT US to get a TSN over 5G system for your company
