A Successful AMR Demo Is Not Acceptance How to Prove the System Is Ready for Production

A mobile robot can complete a perfect demonstration and still be unready for production.

The vehicle may travel from Point A to Point B, avoid a person, dock at a workstation, and return to its charging station while managers watch. The demonstration looks successful. The robot moves smoothly. The software dashboard shows a completed mission. Everyone can see that the technology works.

But a production acceptance decision asks a much harder question.

Will the complete system continue to deliver the required material flow when the factory is busy, when several robots request the same resource, when docking conditions vary, when a station is unavailable, when communication is interrupted, when batteries are at different energy levels, and when operators respond to abnormal situations?

This is the real purpose of AMR acceptance testing.

Acceptance is not a ceremonial final demonstration. It is a structured process for converting design assumptions into measurable evidence.

The distinction is important because mobile robot projects contain several layers that can succeed independently while the complete operation still fails. A vehicle can navigate correctly while the production interface is unreliable. A fleet manager can dispatch correctly while charger congestion reduces capacity. Docking can work in an empty test area but become inconsistent under real load conditions. Individual robots can meet their specifications while the fleet misses the required production response time.

A mature acceptance process therefore evaluates the system as production infrastructure, not only as a collection of robots.

Acceptance Should Be Defined Before the First Robot Is Built

One of the most expensive acceptance mistakes occurs when buyers wait until the end of the project to decide what “passed” means.

At that point, the supplier has already designed the system, the integration architecture is largely fixed, the fleet has been configured, and commissioning resources are on site. If the buyer then introduces new performance expectations, disagreement is almost inevitable.

The supplier may argue that the system meets the original technical specification. The buyer may argue that production still cannot rely on it. Both positions can be reasonable because the project never translated business expectations into testable requirements.

This is why fleet acceptance criteria should be established during the specification and design phase.

The acceptance plan should answer four questions before testing begins:

• What operating condition is the system expected to support?
• Which measurable outcomes define acceptable performance?
• How will those outcomes be tested and recorded?
• What evidence is required before final approval?

This article begins after the earlier project-feasibility question. If the project team is still deciding whether the proposed mobile robot architecture can be delivered at all, that belongs in the AMR/AGV delivery feasibility stage.

Acceptance begins when the intended solution is already sufficiently defined to be verified.

A Demonstration Proves Capability; Acceptance Proves Repeatability

A demonstration usually shows that a function can happen.

An acceptance test should show that the function happens reliably within defined operating conditions.

This difference sounds small but changes the entire test design.

Suppose an AMR successfully docks with a conveyor once.

The demonstration has proven that docking is technically possible.

Acceptance still needs to answer:

• Does docking remain reliable across repeated attempts?
• Does payload influence alignment?
• What happens when the robot approaches from slightly different positions?
• Does the station correctly detect arrival?
• Does the robot correctly detect transfer completion?
• What happens after a failed first attempt?
• Can the system distinguish a docking error from a station error?
• Does recovery preserve the correct mission state?

The same logic applies to navigation, fleet dispatching, charging, traffic coordination, wireless communication, and external equipment integration.

The purpose of acceptance is not to collect successful screenshots.

It is to show that production behavior is predictable.

Build the Acceptance Envelope Before Writing Test Cases

A test result is meaningful only when the test conditions are defined.

If a supplier says a mission took four minutes, the buyer should know:

• which route was used;
• what payload was carried;
• how many robots were active;
• whether other traffic was present;
• whether charging was occurring;
• which software version was installed;
• which station configuration was active;
• and whether the result represents one run or a larger sample.

This collection of conditions can be treated as the system's acceptance envelope.

Define the Physical Envelope

Record:

• robot models;
• payload range;
• load dimensions;
• center-of-gravity assumptions;
• floor conditions;
• aisle widths;
• station geometry;
• door and elevator interfaces;
• charging locations;
• and any temporary infrastructure used during the test.

Define the Operational Envelope

Document:

• production shift pattern;
• mission types;
• expected mission frequency;
• peak demand periods;
• task priorities;
• fleet size;
• human and forklift interaction;
• planned waiting conditions;
• and business-system dependencies.

Define the Software Envelope

The acceptance record should identify:

• robot firmware version;
• navigation software version;
• fleet-management version;
• maps;
• traffic rules;
• mission definitions;
• PLC programs;
• integration middleware;
• and relevant configuration files.

Without a frozen baseline, a passed test can become impossible to reproduce after the configuration changes.

Use Four Acceptance Gates Instead of One Final Test

For practical project management, the acceptance process can be divided into four gates.

These gates are not presented here as a universal industry definition. They are a useful engineering structure for separating different kinds of evidence.

This approach prevents one successful final demonstration from hiding unresolved problems that should have been detected earlier.

FAT Should Test More Than Whether the Robot Moves

AMR FAT is most valuable when it removes technical uncertainty before equipment reaches the customer site.

The supplier environment may not reproduce the entire factory, but it can still verify a significant portion of the system.

Verify Vehicle Functions

Depending on the application, FAT may include:

• normal travel;
• turning behavior;
• load handling;
• lift or conveyor operation;
• manual and maintenance modes;
• charging functions;
• alarm behavior;
• local recovery;
• and emergency functions.

The vehicle should be tested as the supplied configuration, not as a generic base platform if the project includes an application-specific top module.

The reason is explained in the AMR/AGV working unit guide: the production machine is the combination of the mobile base, top module, sensors, controls and surrounding workflow.

Verify Interface Behavior Before Site Installation

If the final system communicates through APIs, PLC signals or a fleet-management interface, the project should test as much interface logic as possible before delivery.

Useful questions include:

• Can a mission be created correctly?
• Can the robot reject an invalid request?
• Can a mission be canceled?
• Are task states reported consistently?
• Are action results clearly distinguished from transport results?
• Are alarm codes understandable?
• Can logs identify the event that caused a failure?

Do Not Pretend the FAT Environment Is the Factory

A controlled FAT area cannot fully reproduce:

• real wireless roaming;
• production traffic;
• metal storage density;
• real doors and elevators;
• operator behavior;
• actual charging congestion;
• or the complete WMS/MES environment.

These items should be explicitly deferred to site testing rather than marked “passed” by assumption.

The Site Integration Gate Prevents SAT From Becoming Debugging

Many projects go directly from equipment delivery into SAT.

That can make the test period inefficient because SAT becomes a mixture of installation, configuration, fault finding and formal acceptance.

A separate readiness gate is useful.

Before formal AMR SAT begins, verify that the site itself is ready.

Navigation Environment Ready

Confirm that:

• maps are approved;
• routes reflect the final layout;
• restricted areas are configured;
• speed zones are defined;
• docking points are surveyed;
• and temporary construction obstacles have been removed or documented.

The navigation technology itself belongs in the AMR/AGV navigation guide; acceptance should instead verify that the selected navigation solution performs correctly in the final site.

Wireless Infrastructure Ready

The robot may navigate onboard while still depending on network communication for fleet control and production integration.

Therefore site readiness should confirm route-level wireless performance, especially at:

• handover areas;
• doors;
• elevators;
• dense racks;
• charging areas;
• and major production transitions.

The full network-engineering logic is covered separately in the AMR industrial wireless network guide.

External Equipment Ready

Confirm that conveyors, PLCs, elevators, automatic doors, machine stations and chargers are available for integrated testing.

If an external machine is not ready, the related SAT test should be marked blocked or deferred rather than simulated and silently counted as passed.

SAT Should Follow the Material, Not Just the Robot

AMR SAT should evaluate complete production missions.

The test boundary should begin where the business process requests transport and end where the physical delivery has been confirmed.

This creates a different test from simply commanding the robot to travel between coordinates.

A complete mission may include:

1. production demand created;
2. mission generated;
3. robot selected;
4. route permission granted;
5. robot travels to pickup;
6. station confirms readiness;
7. robot docks;
8. load transfer occurs;
9. load possession is confirmed;
10. robot travels to destination;
11. delivery station becomes available;
12. robot docks again;
13. unloading occurs;
14. physical completion is confirmed;
15. business system closes the transport transaction.

If only steps 5 and 10 are tested, the project has verified mobility but not material flow.

An AMR Docking Test Should Measure Repeatability, Not One Perfect Alignment

Docking is one of the clearest examples of why acceptance must be statistical and operational rather than visual.

An AMR docking test should define:

• target position;
• allowed positional tolerance;
• allowed angular tolerance;
• payload condition;
• approach direction;
• station condition;
• successful transfer definition;
• retry logic;
• and failure classification.

Separate Positioning Success From Process Success

A robot can arrive inside the required position tolerance while the material transfer still fails.

Conversely, a station with mechanical compliance may complete a transfer even though positioning performance is degrading.

The acceptance record should distinguish:

• navigation arrival;
• fine positioning;
• mechanical engagement;
• load-transfer confirmation;
• and business completion.

This creates much better diagnostic evidence.

If your project requires deeper analysis of charger or station alignment mechanics, the existing AMR precision docking and autonomous charging guide covers that engineering topic separately.

Test More Than the Nominal Approach

Acceptance should include representative variation:

• different payloads;
• repeat approaches;
• normal floor variation;
• different vehicle units;
• and realistic station operating conditions.

The goal is not to deliberately create unrealistic abuse.

The goal is to prove that normal production variation does not turn docking into a manual adjustment task.

A Fleet Acceptance Test Must Create Competition for Resources

One robot operating alone proves very little about a fleet.

Fleet performance becomes visible when robots compete for the same infrastructure.

Fleet acceptance criteria should therefore include scenarios involving shared resources.

Intersections

Several robots should approach a shared intersection under realistic timing.

Verify that:

• priority rules are applied;
• robots do not create unnecessary blocking;
• the system avoids persistent deadlock;
• and waiting time remains visible in system data.

Narrow Aisles

Test opposite-direction demand where the site includes constrained aisles.

Acceptance should show which vehicle receives access and how the other vehicles wait without blocking upstream traffic.

Shared Stations

Generate concurrent requests for a station and verify reservation logic.

Elevators and Automatic Doors

Test resource requests, delays, cancellation and unavailable-resource behavior.

Charging Resources

Acceptance should include enough energy demand to verify charger allocation rather than demonstrating only that one robot can charge.

The energy side is treated in detail in the AMR charging strategy and fleet availability guide.

Performance Acceptance Needs a Measurement System Before It Needs KPIs

Many acceptance plans contain KPI targets but fail to define how the measurements will be generated.

Before selecting AMR performance metrics, decide how data will be captured.

Synchronize Time

Robot logs, fleet logs, PLC events, WMS transactions and network logs should use sufficiently consistent timestamps to reconstruct a mission.

If different systems disagree on time, root-cause analysis becomes difficult.

Assign a Test ID

Each test run should have a unique reference connected to:

• mission ID;
• robot ID;
• software version;
• test condition;
• payload;
• result;
• and any deviation.

Keep Raw Evidence

Do not rely only on a presentation dashboard.

Important acceptance tests should preserve enough source data to investigate unexpected results.

Do Not Accept Average Cycle Time Alone

Average performance can hide instability.

Imagine one hundred missions.

Most complete quickly, but a smaller group suffers major delays caused by congestion or repeated docking attempts.

The average may still appear acceptable even though production regularly experiences long interruptions.

Useful AMR performance metrics can therefore include both central tendency and distribution.

No single KPI should be treated as universally mandatory.

The correct acceptance metrics depend on the production service the system is expected to provide.

Mission Success Rate Needs a Precise Definition

“99% mission success” sounds impressive until the team asks what counts as success.

Does a mission count as successful if:

• the robot required one automatic retry?
• an operator pressed resume?
• a station had to be reset?
• the fleet manager reassigned the mission?
• the robot delivered successfully but exceeded the required cycle time?

The acceptance plan should define categories before data is collected.

For example:

• completed without intervention;
• completed after automatic recovery;
• completed after operator intervention;
• failed because of robot system;
• failed because of external equipment;
• invalid test due to site condition.

This prevents performance statistics from being improved by changing the interpretation after the test.

Test the System Under Degraded Conditions on Purpose

A production AMR system will eventually experience abnormal conditions.

Acceptance should therefore prove that failures remain controlled.

This does not mean intentionally damaging equipment.

It means creating safe, planned fault scenarios.

Blocked Route

Place an approved obstacle or close a route in a controlled manner.

Verify whether the robot:

• waits;
• replans where permitted;
• reports the correct state;
• and returns to normal operation correctly.

Station Unavailable

Make a destination temporarily unavailable.

Verify whether the fleet holds, redirects or reschedules the mission according to design.

Communication Interruption

Create a controlled loss of relevant non-safety communication where the system architecture permits such testing.

Verify:

• robot local behavior;
• fleet state;
• resource reservations;
• mission preservation;
• and reconnection behavior.

The network failure model should be consistent with the architecture described in the industrial wireless network guide.

Low-Energy Robot

Introduce a robot near its configured charging threshold while mission demand remains active.

Verify that the scheduler does not assign work that violates the intended energy policy.

Charger Unavailable

Remove one charger from service and verify fleet response.

Robot Removed From Fleet

Take one robot offline and confirm that remaining mission capacity and task reassignment behave as expected.

Recovery Is Part of the Acceptance Result

A mature system is not defined by never encountering faults.

It is defined by failing in understandable ways and recovering predictably.

Every injected exception should answer:

• Did the system detect the condition?
• Did it classify the condition correctly?
• Did it enter the intended safe or controlled state?
• Did operators receive useful information?
• Was the mission state preserved?
• Could the system recover automatically where intended?
• If manual recovery was required, was the procedure clear?
• Did the business system remain consistent with the physical load state?

This is especially important in multi-vendor systems, where different robots may report similar conditions differently. The integration issues are discussed more deeply in the multi-vendor AMR/AGV interoperability guide.

Safety Validation Is Part of Acceptance, but Acceptance Is Larger Than Safety

An AMR project cannot be accepted simply because throughput targets are met.

Safety requirements must also be validated for the actual installed application.

ISO 3691-4 addresses safety requirements and verification for driverless industrial trucks and systems, including vehicles commonly described as AGVs and AMRs.

ANSI/A3 R15.08-2 addresses safety requirements for industrial mobile robot systems and applications, including system integration.

These standards do not replace the project acceptance plan.

They define important safety responsibilities that must exist alongside performance and operational testing.

The site-specific safety logic is addressed separately in the AMR/AGV mobile base safety guide.

An acceptance project should keep the distinction clear:

Safety acceptance proves acceptable risk; production acceptance proves the system delivers its required operational service.

Both matter.

Cybersecurity Acceptance Should Not Be Hidden Inside IT Handover

Modern mobile robot systems depend on networked software, remote access, APIs and servers.

Before final approval, the project should verify that the agreed cybersecurity architecture has actually been implemented.

Relevant checks may include:

• required accounts established;
• temporary commissioning accounts removed;
• remote-access method validated;
• network segmentation implemented;
• backup procedures tested;
• software baseline recorded;
• and security logging available where specified.

The deeper OT-security architecture is covered in the AMR cybersecurity and OT security guide.

Operational Acceptance Is Where the Project Meets Production

A system can pass FAT and SAT and still behave differently after production begins.

This is why an operational acceptance test should use realistic material demand over a sufficiently representative operating period.

The exact duration depends on the application. There is no universal number of hours or missions that proves every system.

The test should instead be long enough to expose the operating patterns that matter.

Include Different Demand Periods

Where relevant, include:

• shift startup;
• steady-state production;
• peak replenishment periods;
• breaks;
• changeovers;
• charging cycles;
• and shift handover.

Include the Full Fleet

A system designed for twenty robots should not receive final fleet acceptance based entirely on two robots running demonstration missions.

Measure Material Service, Not Robot Activity

The operational question is not:

How many kilometers did the robots drive?

The better question is:

Did the production process receive the required material at the required time with acceptable reliability?

This connects acceptance to the business logic described in the AMR/AGV material-response guide.

Operational Acceptance Should Expose Manual Work Hidden by Commissioning Teams

Commissioning engineers are very good at keeping systems running.

That becomes a problem if their constant presence hides weaknesses that normal operators will later inherit.

During operational acceptance testing, record every manual action that would not exist in normal autonomous operation.

Examples include:

• manually releasing blocked traffic;
• restarting a station;
• resetting a robot;
• editing a task;
• moving material manually;
• adjusting a docking position;
• forcing a charger assignment;
• or manually correcting business-system state.

These actions are not necessarily automatic failures.

But they must be visible.

If the system achieves its throughput target only because engineers continuously intervene, production has not received the system that was measured.

Human Intervention Rate Is One of the Most Valuable Acceptance Metrics

Robot utilization attracts attention because it looks like productivity.

Human intervention rate often tells more about operational maturity.

A useful project-specific metric is:

Interventions per 100 valid missions

The exact acceptable value depends on the application.

The important point is consistency of definition.

Interventions can be classified as:

• robot-related;
• fleet-related;
• station-related;
• network-related;
• operator-process-related;
• or external equipment-related.

This makes the acceptance data useful after go-live because the factory can continue tracking the same categories.

Do Not Let External Equipment Become an Unlimited Excuse

AMR projects are integrated systems, so some failures genuinely belong to external equipment.

But an acceptance process becomes meaningless if every failed mission is excluded as “not the robot.”

The better approach is to measure both:

• system-level service result;
• and component-level root cause.

If an automatic door fails twenty times, the robot supplier may not own the door fault.

However, production still experiences twenty interrupted transport missions.

The acceptance report should show both facts.

This preserves accountability without hiding operational reality.

Use a Nonconformance System Instead of Arguing Test by Test

Large acceptance programs inevitably produce deviations.

A structured nonconformance process is more effective than treating each problem as a new negotiation.

Each issue should record:

• unique issue ID;
• test reference;
• observed behavior;
• expected behavior;
• operational impact;
• temporary workaround;
• responsible party;
• planned correction;
• retest requirement;
• and closure evidence.

Separate Severity From Difficulty

A problem may be technically difficult to solve but have little production impact.

Another problem may be easy to fix but completely prevent safe operation.

Prioritization should consider operational consequence, not engineering inconvenience.

Every Retest Must Preserve Traceability

Suppose a docking test fails.

The supplier adjusts a navigation parameter and the next attempt passes.

The project should record:

• what changed;
• which version now applies;
• whether related stations are affected;
• and which earlier tests may need to be repeated.

This prevents one local fix from silently invalidating previously accepted behavior.

Commissioning Is Not Complete Until Normal Staff Can Operate the System

Mobile robot commissioning is often treated as a technical configuration activity.

Production commissioning is broader.

The system is not truly commissioned if only supplier engineers know how to recover it.

Before final acceptance, normal operating and maintenance staff should demonstrate that they can perform the responsibilities assigned to them.

Operator Capability

Operators may need to understand:

• normal robot states;
• mission status;
• approved pause and resume actions;
• basic alarm meaning;
• safe interaction rules;
• and escalation procedure.

Maintenance Capability

Maintenance teams may need:

• diagnostic access;
• fault-code interpretation;
• maintenance-mode procedures;
• inspection points;
• spare-parts information;
• and escalation to supplier support.

System Owner Capability

The internal owner should understand:

• software and configuration baseline;
• map ownership;
• user permissions;
• backup location;
• approved change process;
• and responsibilities between internal teams and external suppliers.

The Handover Package Is Part of the Product

A successful technical test is not enough if the factory cannot maintain the accepted state.

The robot handover checklist should therefore be treated as an acceptance deliverable.

System Baseline

• robot inventory;
• software versions;
• firmware versions;
• fleet configuration;
• approved maps;
• station coordinates;
• traffic rules;
• and charger configuration.

Interface Documentation

• WMS/MES interface;
• PLC communication;
• door interfaces;
• elevator interfaces;
• station handshake;
• API definitions;
• and responsibility boundaries.

Operations Documentation

• operator procedures;
• fault recovery;
• manual intervention rules;
• startup and shutdown;
• charging procedures;
• and escalation contacts.

Maintenance Documentation

• maintenance schedule;
• inspection requirements;
• replaceable components;
• spare-parts list;
• diagnostic procedure;
• and supplier support process.

Acceptance Evidence

• FAT report;
• SAT report;
• operational test report;
• open-issue list;
• closed nonconformance records;
• training records;
• and approved deviations.

A robot handover checklist prevents knowledge from disappearing when the commissioning team leaves the site.

Final Acceptance Should Freeze a Known-Good Baseline

When the system is accepted, the project should identify exactly what configuration was accepted.

This known-good baseline becomes the reference for future troubleshooting.

If performance degrades six months later, engineers can compare the current system against:

• the accepted software version;
• the accepted map;
• the accepted traffic configuration;
• the accepted station geometry;
• the accepted network environment;
• and the accepted KPI baseline.

Without this reference, troubleshooting becomes an argument about whether the system has changed.

Acceptance Criteria Should Become Operations KPIs After Go-Live

The best acceptance measures do not disappear after project closure.

If mission success rate mattered during acceptance, continue monitoring it.

If docking retries mattered during SAT, trend them after go-live.

If charger queue time was a fleet constraint, continue measuring it.

If human intervention rate was used for operational signoff, make it an operating KPI.

This creates continuity between project delivery and lifecycle management.

It also prevents a common problem:

The system receives a detailed acceptance test, but nobody notices gradual degradation later because normal operations monitor completely different metrics.

Standards Provide the Safety Framework; the Contract Defines Production Success

Several standards are relevant to the acceptance environment, but buyers should understand what those standards do and do not provide.

ISO 3691-4:2023 addresses safety requirements and verification for driverless industrial trucks and their systems, including vehicles commonly called AGVs and AMRs.

ANSI/A3 R15.08-2-2023 addresses safety requirements for industrial mobile robot systems and applications and their integration.

ANSI/A3 R15.08-3-2026 addresses safe use of IMR applications during normal operation and lifecycle management.

These references are important for safety.

They do not automatically define whether a specific factory has received the production throughput, docking reliability, intervention rate or material-response performance it purchased.

Those expectations belong in the project specification and acceptance agreement.

A Practical Acceptance Matrix

Focused FAQ

What is the difference between FAT and SAT for an AMR project?

AMR FAT normally verifies as much vehicle, software and interface functionality as practical in a supplier or controlled environment before final site operation. AMR SAT verifies the installed system in the customer's actual environment, including real routes, stations, infrastructure and integrations. The exact scope should be defined by the project contract.

How many missions should be tested before AMR acceptance?

There is no universal number that proves every system. AMR acceptance testing should use enough repetitions and operating conditions to demonstrate the required reliability for the application's risk and production profile. A low-frequency laboratory transport application and a high-throughput automotive line should not use the same acceptance logic simply because both use AMRs.

What should an AGV acceptance test include?

AGV acceptance testing should include vehicle functions, navigation or guidance behavior, station interfaces, load transfer, traffic coordination, charging, abnormal-condition recovery, production performance and applicable safety validation. The test should evaluate the complete application rather than only vehicle travel.

What is the most important AMR KPI during acceptance?

There is no single universal KPI. Useful AMR performance metrics commonly include mission success, cycle-time distribution, docking reliability, human intervention rate, traffic waiting time, recovery time and production-response performance. The best KPI is the one directly connected to the material service the factory purchased.

Should docking accuracy be measured during SAT?

Yes when accurate station interaction is part of the application. An AMR docking test should define both positioning tolerance and successful process completion. A robot being physically close to the target does not prove that the conveyor, lift, charger or other workstation interaction will operate reliably.

Should AMR acceptance include network failures?

If fleet control or production integration depends on wireless communication, controlled degraded-condition testing can be valuable. The test should be planned safely and verify robot behavior, fleet state, resource reservations and mission recovery. It should not interfere with safety-related functions or create uncontrolled operating risk.

How should multi-vendor AMR fleets be accepted?

Fleet acceptance criteria should verify shared-resource coordination, normalized states, mission ownership, traffic rules, error behavior and recovery between vendors. Protocol compatibility alone is not enough evidence that a mixed fleet will behave predictably in production.

When is mobile robot commissioning complete?

Mobile robot commissioning should not be considered complete merely because supplier engineers can run the system. The required production staff should be trained, normal fault recovery should be documented, configurations should be baselined, and the system should operate inside the agreed acceptance criteria.

What belongs on a robot handover checklist?

A robot handover checklist should include system inventory, software and map versions, interface documentation, operating procedures, maintenance instructions, backup information, training records, acceptance evidence, unresolved deviations and support responsibilities.

What is an operational acceptance test?

An operational acceptance test verifies that the installed AMR or AGV system can provide the required production service under representative operating conditions. It extends beyond individual functional tests and evaluates sustained fleet behavior, material response, interventions, charging, exception recovery and real system dependencies.

The Final Question Is Not Whether the Robots Work

At the end of an automation project, asking “Do the robots work?” is no longer specific enough.

The robots may move.

The fleet manager may dispatch.

The stations may communicate.

The chargers may charge.

All of those functions can be technically operational while the factory still lacks a dependable production system.

The real acceptance question is:

Can the complete mobile robot application repeatedly deliver the required production service inside a defined operating envelope, with measurable performance, controlled failures and a maintainable handover baseline?

That is the purpose of operational acceptance testing.

It transforms project completion from an opinion into evidence.

It protects the buyer because expectations are measurable.

It protects the supplier because the definition of success is agreed in advance.

It helps the integrator because failures can be traced to defined system boundaries.

And it helps operations because the metrics used to accept the project become the metrics used to maintain it.

A successful demo proves that a mobile robot can work.

A successful acceptance program proves that the factory can depend on it.

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