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Robotics Tech Papers

Accurate Automated Measurement Integral to Industry 4.0

Perceptron, Inc.


Automated measurement for automotive body dimensional control was introduced in the mid-1980s by Perceptron with the invention of cost-effective, non-contact laser optical sensors and image processing techniques. This innovation combined with newly available CPUs, data storage, and graphical user interfaces enabled non-contact, 100% measurement of critical checkpoints on every assembly produced. The new automated measurement paradigm was an alternative to sampling at off-line gauges and Coordinate Measuring Machines (CMMs). The 100% sampling provided data insights for process control strategies 25 years before this was considered a critical element of Industry 4.0.

Surprisingly, while the use of off-line gauges in the automotive body shop has greatly diminished, the use of CMMs has persisted. To a large degree this is due to the desire to have traceability of the automated gauges, but also due to the CMMs’ more dependable accuracy and flexibility. However, recent breakthroughs enabling traceable accuracy and efficient programmability of automated measurement cells has finally closed the gap. Traceable, flexible, and efficiently programmable, the new generation of automated measurement is now deployed in-line, near-line, and off-line in the body shops and at tier suppliers. In 2020, led by Perceptron, automotive manufacturers and suppliers are now realizing the full potential of automated measurement as the principal measurement standard and an integral part of their industry 4.0 initiatives.


The Coordinate Measuring Machine process has always been labor intensive. The process typically entails safely extracting parts out of the production line, transporting them to the measurement room, soaking to measurement temperature, loading into fixtures, and then running a lengthy CMM measurement program. After the program is completed, the part is taken back to the line and re-introduced into production. CMM programs can take hours to run, resulting in small sample sizes. The small sample size coupled with the high labor to operate the machines, as well as logistics and safety management, makes the CMM a very unproductive measurement tool. Attempts to automate CMM loading and unloading as well as locating the temperature controlled and isolated measurement rooms near the line have not proven cost-effective.

However, while CMMs are slow and expensive to operate, they do have critical attributes that have not been available, or reliable enough, in automated, non-contact measurement cells.

Historically, CMMs produced measurements traceable to calibration standards in true part coordinate space—so-called “absolute accuracy.” Absolute accurate measurement produces results that accurately indicate the deviation of the measured part from the design intent. Due to their absolute accuracy, the CMM has been the master reference to which in-line measurement stations were compared and correlated.

CMMs also offered great flexibility and efficient programmability to add checkpoints as desired. This is particularly important during a new product launch where the mix and number of checkpoints may need to quickly change to focus on problem areas or specific validations.

CMMs were also not limited by station cycle time, thus allowing parts to be held for hours so that specific investigations can be conducted as needed. Finally, CMMs have been standardized and were familiar to trained metrology specialists who operate and follow traditional procedures.


It has long been a goal of automotive manufacturers to reduce the financial investment of dedicated climate-controlled rooms, isolation foundations, and measurement machines as well as reducing daily operation and staff costs of off-line measurement.  The old paradigm of sampling parts, however, has not been able to keep up with the increased number of car models produced from one body shop. Production automation has transformed factories from producing one or two car models and associated model variants such as 2-door and 4-door, to lines that often produce five different models with many more variants.

Meanwhile, new Industry 4.0 goals, as well as the drive for higher efficiencies and higher productivity, have put pressure on quality departments to automate and on automated measurement suppliers to close the gap on critical CMM attributes—particularly precision and absolute accuracy.

In some instances, CMMs are being replaced in the measurement room with off-line optical scanners that are either manually or robotically positioned or scanned. These optical CMMs are flexible and can capture dense data sets more rapidly than touch-probe CMMs. However, they still carry the inefficiencies and operating costs of an off-line measurement room.


Even as efficiency and productivity needs change, the typical automotive build tolerance remains +/-1.0mm. Meaning the 6-sigma variation of the production process is managed to within +/-1.0mm and the product dimensions compared to design intent are managed to within +/- 1.0mm.

Per Measurement System Analysis (MSA) guidelines, measurement system error is evaluated from Accuracy and Precision. Accuracy describes an automated system’s linearity and bias compared to true actual values and Precision describes the repeatability of the measurement. For a capable absolute measurement system, the percent error attributable to the measurement equipment should be less than 10 to 20% of the target total error tolerance (upper limit – lower limit). In addition, for traceable absolute accuracy the calibration or reference process uncertainty must be included in the error budget. Therefore, for assembly tolerances of +/-1.0mm, and a 10% maximum error budget, the measurement equipment should have an absolute accuracy and precision of less than 0.20mm.

Automated measurement technology is shifting the paradigm by achieving traceable absolute positional accuracy in the manufacturing process. In addition to the accuracy and precision, virtual Digital Twin technology applied to automated robot programming and automated checkpoint programming has greatly improved the flexibility and efficiency of operation for automated in-line systems.

The recent technology-driven breakthrough of in-line absolute accuracy is allowing manufacturers to realize desired manufacturing process productivity and efficiency gains. This transformation in the traditional dimensional quality strategies is reducing or even eliminating the use of off-line CMMs and the related labor and expenses. And the role of automated in-line, non-contact measurement has now expanded from a process-variation reduction and defect-containment tool, to a tool depended upon for maintaining and improving productivity by assuring both process and product compliance. Before exploring the new absolute measurement paradigm further, it is helpful to have some perspective on the evolution of automated in-line auto body measurement.


Prior to the advent of automated in-line measurement, the traditional dimensional quality control strategy in the automotive body shop relied on sampling production with off-line CMM machines in temperature-controlled measurement rooms. The metrology science and techniques for touch probe contact measurement were developed in the 1970s by metrology engineers in collaboration with the CMM companies. The quality engineers operating the CMM machines were highly trained metrology specialists. The absolute accuracy of the typical CMM machine in the automotive body shop could reach 0.010mm in a local area, but when assessed throughout the machine volume, a more typical accuracy of 0.100mm maximum error was more often the reality with dual horizontal arm configurations.

When Perceptron introduced plant floor hardened automated in-line measurement in the mid-1980s, the focus was on 100% measurement data and statistical process techniques for process variation reduction. The repeatability of the Perceptron technique was typically less than 0.100mm 3-Sigma. The systems were good for relative measurement typically achieving relative accuracy error on the order of 10% due to crudely measured relation from sensor coordinates to part coordinates.

And the debate over 100% vs sampling began. One big question was what to do with the overload of data? Another was how much is enough accuracy? Data confidence also became a big challenge as the laser optical technique applying image processing were subject to influences that affected the results differently than the CMM touch probes. The desire to have traceability of the in-line measurements drove a process of correlating and offsetting the in-line measurements relative to the CMM and this became a major effort for the quality engineers in the measurement rooms.

In the late 1980s, Perceptron invented and patented a technique for calibration of the in-line measurement stations directly into absolute coordinates. The technique made use of theodolites referenced to the part coordinate origin and a calibration target measurable by both the theodolites and the measurement sensor’s laser. The relation from sensor coordinates into absolute part coordinates was generated for each sensor and stored and applied to the measurements. This technique typically achieved absolute accuracy within 0.250mm when applied to fixed mounted sensors. This reduced the CMM correlation and offset process, but the differences between optical and touch probe techniques remained.

In the early 1990s, interest in flexible automation and measuring with robots positioning sensors, rather than fixed mounted sensors, for each checkpoint was growing—particularly in Japan and Korea. This was driven partly by the desire to run multiple models on a single line rather than single model dedicated tooling.

Error from robot repeatability and thermal drift had to be overcome, and Perceptron and Nissan developed high-accuracy measurement robots with rectilinear axes to allow straight forward linear thermal drift error correction. The measurement data was processed to optimize the numerically controlled tooling—an early instance of Industry 4.0 level of automation and information exchange. This was followed by techniques for applying kinematic model-based thermal compensation to standard industrial robots to reduce measurement error caused by robot thermal drift. Absolute accuracy was initially still achieved by reference measurement techniques at each checkpoint, such as the theodolite or eventually laser tracker, but results were never as accurate as with fixed-mounted sensors.

During the early 2000s, techniques to calibrate robots into absolute coordinates and sustain that calibration were developed and refined with a goal to simplify the use of measurement robots and increase the flexibility of the in-line measurement stations. The robot kinematic models and compensation techniques became more sophisticated and accurate. The industry-leading techniques developed by Perceptron to compensate for the absolute error of the robot TCP position and the relation from sensor coordinate to TCP coordinate to part coordinate could be relied on to achieve an absolute volumetric accuracy approaching 0.250mm. Standards were also developed and adopted for validating and comparing volumetric accuracy of the automated systems, such as the ISO 10360-8.

More recently, Perceptron has pioneered major advances such as optical measurement techniques and 3D point cloud laser sensors, such as the Helixevo sensor family. Helix was developed to produce measurements that exactly match the CMM touch probe techniques, virtually eliminating this long-standing correlation error factor. Perceptron developed self-learning software for compensating measurements such that plant floor temperature-induced dimensional changes of the measured part do not influence the measurement results. Software for split cycle configurations where different checkpoints are measured on different cycles have been introduced to maximize the in-line checkpoint coverage. And off-line programming techniques, including the use of Digital Twins to fully simulate automated systems, have simplified the programming and maintenance of the automated systems. 




Perceptron has introduced an advanced industrial plant floor hardened optical tracking technique called AccuSite, using multiple precision-calibrated, large-volume optical tracking sensors installed in the station to create a super-volume of precision coverage throughout the measurement station. Active illuminators provide a robust and precise tracking performance of less than 0.100mm throughout the entire volume. When combined with the sub 0.050mm Perceptron Helix laser point cloud sensor, the total station volumetric accuracy is under 0.150mm maximum error. As noted earlier, the generally accepted threshold for eliminating the need for a “master” CMM in an automotive body shop is automated in-line absolute accuracy under 0.200mm.

These highest-performance automated measurement systems are now achieving this level of in-line absolute accuracy and stability with techniques for referencing station fiducials frequently and, in some systems, for simultaneously measuring checkpoints. The fiducials in the station are installed at stable tooling positions and referenced to the part-coordinate system via a one-time measurement with an external tool such as a laser tracker or portable CMM.

Ease of use

Despite off-line simulation and programming, automating measurement with industrial robots has always carried the challenges of hiring and training high-skilled programming talent; and laborious optimization efforts to achieve the maximum number of checkpoint measurements within the minimum cycle time. System installation effort is measured by time per checkpoint and labor expense is one of the largest components of overall system expense.

To address these challenges, Perceptron has introduced a virtual Digital Twin and automated programming capability which with very little user skill enables rapid, optimized robot path generation. The paths generated consider all the parameters, requirements, and constraints of the sensors, robots, and station. The user simply loads their list of checkpoints into the software or they can pick the points visually from the software CAD model. Measurement programs are fully generated, simulated, visualized, and then downloaded to the measurement station. One crucial capability is a “true-up” function to exactly match the virtual and actual system. At the actual station, a technician only needs to validate the system program update. 

Data analytics

Perceptron’s Vector software provides a central database to aggregate and mirror all the data in distributed automated in-line measurement stations throughout the production facility. Measurement data from upstream systems can be virtually combined with downstream systems for analysis of variation and trends. Multivariate analysis tools, called Argus AI, are applied to uncover patterns among measurement points to identify root causes and generate 3D CAD overlay visualizations.

In early 2020, Perceptron is introducing an AI powered plant floor intelligence software called PRISM that goes beyond analytics of dimensional data to include all connected process data sources such as robots, PLCs, welding controls, dispensing controls and cameras, and sensors distributed throughout the production lines. The PRISM intelligent algorithms search for correlations and patterns between all the production data sources and the dimensional data results to recognize potential threats and alert process owners to action before the threats result in unplanned production stoppages.

These sophisticated technologies innovated by Perceptron specifically for the factory floor environment incorporate the many years of lessons learned with a focus on the user experience. They are transforming the automotive body shop and tier supplier measurement strategies, and how automated measurement is being applied, resulting in cost savings for facilities and operations while improving the productivity of the production engineers.


The Perceptron vision for the future of body shop dimensional control is a completely automated strategy aligned with Industry 4.0 smart factory goals of flexibility, automation, and intelligence. The Digital Twin adoption will increase measurement station confidence, reliability, and flexibility. The stations will be fully programmable from office-based workstations and optically referenced to maintain the virtual to actual link and achieve accuracies of under 0.100mm.

Using the Perceptron Digital Twin software, quality or production engineers will be able to simulate and update measurement plans on the fly from their workstations in order to focus on specific variation reduction efforts or investigate deviations from design intent. The measurement data will be immediately available and AI models and machine learning will highlight data patterns and associated root causes for process engineers to act on threats before production is affected.

As tooling becomes more intelligent, adaptable, and connected; and intelligent sensors are distributed throughout more of the production line, the potential for self-learning and self-optimization will be realized and production lines will autonomously diagnose maintenance needs and adapt themselves to incoming material variation. Higher productivity, more consistency, and higher quality are the deliverables of more intelligent tooling.

There have been many small steps and innovative leaps since Perceptron introduced the innovation of automated, non-contact measurement to automotive body shops in the mid-1980s. Throughout the decades, Perceptron has stayed passionately focused on this narrow but rich area of automotive body dimensional control. And now, technology innovations have caught up to Perceptron’s vision of traceable, flexible, and efficiently programmable automated measurement, to the benefit of automotive manufacturers around the world.

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