Humanoid robots like Figure 02 are the next evolutionary step in manufacturing. They can:
grasp and manipulate a wide variety of parts,
perform tasks at existing workstations,
take over ergonomically demanding or repetitive activities.
In other words: they are designed to take over work that used to be “too unstructured” or too complex for classic industrial robots.
But on their own, humanoid robots are just highly advanced, very expensive standalone devices. They only become economically meaningful when they are embedded into a digital, controllable and feedback-driven environment.
That is exactly where a Manufacturing Execution System (MES) comes in. The MES becomes the central coordinator between:
Traditional robot cells work in a highly standardized way: fixed grippers, defined positions, tightly programmed motion sequences.
Humanoid robots, by contrast, are designed to replicate human work:
handling different containers, parts and tools,
operating existing machines and equipment,
carrying out ergonomically critical tasks (overhead work, heavy lifting, awkward postures),
working in environments that were not built specifically for robots.
For such a “digital worker” to deliver sustainable value, it needs:
a clearly defined job (task, context, target state),
continuous data from production,
standardised interfaces to shop-floor IT and OT,
integrated safety and quality logic.
The system that provides all of this is the MES.
A humanoid robot doesn’t just need low-level motion commands. It needs context-aware work instructions.
The MES takes over the role of a dispatcher:
Job and task models, for example:
“Pick part X from buffer Y and place it in fixture Z.”
“Perform activity A at station B as long as line C is overloaded.”
Resource selection:
The MES decides whether a task is performed by a human operator, a classic robot, a humanoid robot – or a combination – based on availability, capability, safety rules and bottlenecks.
Event-driven reactions:
Quality deviation? → MES creates a task for the humanoid robot to separate suspect parts.
Line down? → MES reallocates the robot to material supply or rework.
A cloud-native MES like SYMESTIC already provides this orchestration layer through production control, order tracking and real-time KPIs. Humanoid robots simply become additional resources in this orchestration.
Humanoid robots operate inside a process – not in a vacuum. They require access to:
product data (BOMs, variants, characteristics),
process steps and work instructions,
limits, tolerances and quality rules,
takt times, OEE information and current line status.
The MES provides exactly this process context in real time – via shop-floor clients, dashboards and APIs.
For the robot this means:
It receives not just movements but semantic tasks (“Assemble component X into product Y in variant Z”).
It can align its actions with current process and quality specifications.
It returns feedback to the MES (status, duration, success, deviations).
Many humanoid robots are still in pilot phases, and not every vendor has a full, public interface specification yet. From an MES perspective, however, the requirements are clear:
Industrial protocols: OPC UA, MQTT, REST, potentially fieldbus/real-time Ethernet for tighter integrations.
Status and error reporting: runtime status, task progress, error codes, alarms.
Command interfaces: start, stop, pause, task assignment, parameterization.
A cloud MES like SYMESTIC already provides a connectivity layer:
OPC UA gateways for PLCs and machines,
digital I/O and edge connectivity for signals, alarms, energy and process values,
REST APIs to integrate robots, vision systems or external AI services.
Humanoid robots plug into this layer as one more data source and one more “actuator” in the system.
In regulated industries and complex supply chains, it isn’t enough that a task was done. It must be provable:
Which part was processed?
Where, when and how was it processed?
Under which parameters and by which resource (human, machine, robot)?
The MES is the backbone for this:
part-level and batch-level traceability,
digital inspection records and QA gates,
rework, scrap and deviation management.
The humanoid robot becomes part of this traceability model:
Every step executed by the robot is linked to a specific order, product, batch or serial number.
Process values, camera results and robot actions are stored directly in the MES.
Later, you can answer questions like:
“This product was assembled by robot R at station S under process parameters P, Q, R.”
In a modern MES, a humanoid robot is simply another resource – next to machines, lines, tools and human workers:
availability (shifts, planned downtime, maintenance),
utilization and performance (productive vs. non-productive time),
energy consumption and operating hours.
This enables:
task prioritization based on bottlenecks and due dates,
load balancing between humans, classic robots and humanoid robots,
what-if analysis (e.g. impact of adding another robot to a constrained line).
SYMESTIC already supports such views with modules for OEE, line performance and headcount monitoring. Humanoid robots can be modeled as additional segments/resources inside this framework.
Humanoid robots typically work very close to humans. That requires more than just certified safety hardware on the robot itself. It needs process-level safety:
access and authorization rules (“Who is allowed to release or configure the robot?”),
clearly defined handover scenarios between humans and robots (e.g. tools, parts, trays),
automatic reactions to safety events (emergency stop, zone violation, collision, quality problems).
The MES ties this together:
receives safety signals from PLCs and safety relays,
embeds them into workflows (e.g. tasks blocked until a human confirmation is recorded),
triggers alarms and notifications (andon, e-mail, mobile messages).
This way, safety is not just a hardware concern but an integrated part of the overall process logic.
Without an MES, a humanoid robot tends to become an isolated automation project. It works in one cell, for one use case, with a lot of custom code.
With an MES, the robot becomes part of an end-to-end production flow:
Orders start in ERP → go to the MES → are broken down into tasks, including robot tasks.
Robot actions feed back into the MES in real time.
KPIs and analytics cover the entire process, not just the robot cell.
Business impact:
less idle time and waiting,
faster ramp-up for new products and tasks,
better asset utilization across shifts, lines and plants.
Humanoid robots are particularly attractive for:
variant-rich assembly,
frequent changeovers,
processes that are difficult to fully standardize but still repetitive.
The MES makes this flexibility manageable:
rules and workflows per product variant,
task logic instead of hard-coded robot programs,
KPIs showing which product/variant combinations are handled most efficiently by the robot.
This is where small and mid-sized manufacturers can gain a real competitive edge: flexible automation without having to rebuild the entire line around classic robotics.
Because all robot actions and process values are logged in the MES:
processes become fully traceable,
quality and compliance requirements (e.g. automotive, medical devices, food & beverage) are easier to prove,
audits and certifications become significantly less painful.
Instead of manually piecing together data from robot controllers, PLC logs and Excel sheets, everything is consolidated in one system of record: the MES.
Humanoid robots bring repeatability. The MES turns that into stable processes:
monitoring patterns in defects and deviations,
triggering automatic counter-measures (additional inspection, temporary blocks, updated limits),
correlating robot behavior with quality outcomes (e.g. grip patterns, process times, micro-stoppages).
Over time, you build up a data set that clearly shows where robots add the most quality and productivity – and where humans are still superior.
One of the strongest arguments for humanoid robots is ergonomics:
repetitive, monotonous work,
heavy lifting and carrying,
awkward or hazardous environments (heat, cold, noise, confined spaces).
The MES can decide – on a task level – when a robot takes over from a human and vice versa:
tasks are assigned based on rules, skills, availability and safety constraints,
operators get transparency on who (or what) is doing what and why,
ergonomics improvements become tangible via KPIs (e.g. fewer manual heavy-lift tasks per shift).
Humanoid robots like Figure 02 rely heavily on onboard AI for perception and decision-making. Combined with a cloud MES, this allows:
pattern detection in downtime, alarms, quality issues and cycle times,
predictive maintenance, using robot sensor data and MES process data together,
adaptive workflows where the system dynamically chooses the best “agent” (human, classic robot, humanoid robot) for a given task based on performance history.
A cloud MES becomes the data platform on which higher-level AI services can run: identifying productivity, quality and energy potentials across the entire manufacturing system – not just in one robot cell.
To avoid getting stuck in endless proof-of-concepts, manufacturers should treat humanoid robots as part of a structured transformation roadmap:
Capture OEE, downtimes, quality and process data in a standardized way.
Build transparency across lines and resources.
Identify real bottlenecks and ergonomically critical tasks.
Choose tasks with clear business logic and measurable impact (ergonomics, quality, throughput).
Limit the scope, but ensure it’s a real production scenario – not a lab demo.
Define success criteria: KPIs, safety requirements, operator acceptance.
Which communication protocols and APIs does the humanoid robot support?
How are status, errors and traceability data sent into the MES?
How are safety and authorization embedded into the workflows?
Who owns which part of the solution (robot vendor, MES provider, internal OT/IT)?
Track performance and impact in the MES: OEE, quality, ergonomics metrics.
Standardize the most successful workflows into templates.
Scale to additional lines, plants or use cases – without starting from scratch every time.
Humanoid robots like Figure 02 are not a “metallic replacement human.” They are a new type of shop-floor resource – one that is powerful but also data-hungry and context-dependent.
They only reach their full potential when:
tasks are orchestrated centrally in an MES,
real-time data and process context are available,
quality and traceability are built in,
safety and collaboration with human workers are part of the workflow logic,
and the solution can be rolled out across lines, plants and countries.
In this setup, the MES becomes the key platform that turns humanoid robots from impressive demos into sustainable, scalable and auditable production assets.