5 Key Factors for a Successful Machine Acceptance Runoff

Everything You Need to Know When Implementing an Assembly Automation Process

When a company decides to invest in automation, it is making a big investment. This means that by the time manufacturing begins in earnest, they need to be absolutely confident everything is working to expectations. So how does a company ensure that their automation equipment manufacturer is giving them a functional machine? The answer is machine acceptance runoff testing.

In performing this test, manufacturers are essentially confirming three basic things. First, that the parts and assemblies meet specifications, and can reliably identify passing and failing pieces. Second, that the machine can run without issue for the necessary amount of time, at the production speed required by the company. Finally, the machine conforms to safety requirements, all features are functional, and the process is durable against crashes.

In order for integrators to trust that these three criteria are met, a runoff needs to include comprehensive tests for every aspect of machine function. Here are the five key factors for a successful machine acceptance runoff.

Validation Run

Also known as a Factory Acceptance Test (FAT), this test occurs in the facility of the automation equipment supplier long before installation at the site. At this stage, exhaustive static and dynamic testing is conducted on every major system to ensure they meet the specifications agree upon by the client.

Data-Driven Validation

Measurement Systems Analysis (MSA)

Manufacturing processes have natural variation, but the same is also true of measuring processes. An MSA is a mathematical and experimental method to analyze the test procedure and equipment on a process, allowing manufacturers to estimate the error in their measurement data. This allows assembly automation companies to create better data streams, improving quality management.

Type I Gage Study (CG/CGK)

This statistical test is a component of an MSA that concerns the repeatability (known as Cg) and bias (known as Cgk) of a gage with respect to one operator and one reference part using mathematical models. Cg measures the variance of repeated measurement of a single part. Cgk measures the difference between the average gage measurement and the official reference value. A Cg and Cgk of 1.33 each indicate capable, acceptably unbiased gages.

Gage Repeatability and Reproducibility Study (GR&R)

This test is also a component of MSA, using mathematical models to estimate variation. However, instead of testing the gage itself, it tests the effect of human operators on measurement variation. Repeatability, like in the Type I study, refers to the variation of a single operator measuring a single part multiple times. Reproducibility refers to the variance between the repeatability curves of two or more operators. Fortunately, the issues of reproducibility can be eliminated when implementing integrated metrology solutions, which avoid the issue of multiple operators.

Technician inspecting a new system of robotic arms for industrial automation Process Capability Index (CPK)

This test measures the variation in parts in relation to the upper and lower limits of the specs. By calculating the standard deviation of these measurements, which allows manufacturers to estimate the likelihood of a piece being rejected. While an index of 1.0 technically indicates a ‘capable’ process, advanced statistical process control activities can result in indexes as high as 5.0.

Safety Validation

Undoubtedly, one of the most important concerns when dealing with automation equipment suppliers is certainty in the safety of the machine. This obviously applies to the physical well-being of the operators, but also the safety of the other machines in the process. If safeguards fail to stop a catastrophic machine failure, the result could be tens of thousands of dollars in repairs and weeks if not months of downtime. As such, runoff tests need to include comprehensive validation that all safety features work correctly.

Example of this can include:

  • Intentionally severing a connection to trigger a safety feature
  • Removing power to ensure a machine moves to its safe positions, and that stopping distance falls within regulations
  • Testing functionality of e-stop buttons for operators
  • Removing network connection to verify that safety features function independently

Fault Recovery

A major selling point for automation equipment manufacturers is the ability of their machines to minimize downtime. This happens in two ways. The first is creating a rugged machine that avoids breaking down in the first place. The second is how quickly a process can be brought up and running again after a crash occurs. This second part is where fault recovery testing comes in. Recovery testing is not a functional test, but one that measures the speed of recovery after a hardware or software failure. Examples of testing could include suddenly removing a network connection, or a forced machine crash.

Dry Cycle Testing

Once everything else is complete, a final test of the system is needed to make sure all of the different components can work together in harmony. This ‘dry run’ intentionally mitigates potential sources of failure, as those have been individually addressed in previous tests. Instead, this acts as a final verification of function before full production can finally begin.

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    Brandon White

  • DATE

    April 23, 2021

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