QMT Features: July 2016
Off-line, in-line, at-line
Dr Kai-Udo Modrich* argues that complexity in measurement does not mean you have to sacrifice quality

The standards for flexibility and productivity in manufacturing continue to rise. On top of this, new versions and models are always increasing the complexity of the processes, especially in the automotive industry. Yet even under these challenging conditions, companies must still meet high quality standards to avoid defects and expensive recalls. Capturing and evaluating measuring data collected off-line, in-line and at-line enables companies to take on these challenges.

The quality assurance system of the future will have to fulfill standards which are far from trivial: the system should capture quality data quickly, flexibly and reliably at different locations – in the measuring lab, near production and as an integral part of the production line. And the system should merge these data centrally and evaluate them. Based on these data, appropriate measures can be taken.

The three pillars in the measuring process

Ultra-fast or highly accurate? 100% inspection or random sampling? In the production hall or in the measuring lab? Everything in good measure – that is the ZEISS motto. In the future, companies will have to sensibly combine different technologies in order to completely and thoroughly utilize the potential afforded by an overall system. This is the only way they can remain competitive when it comes to speed and quality. Three different pillars form the overall system: first, highly precise off-line technologies in the measuring lab; second, in-line measuring technologies integrated into production; and third, at-line technologies in direct proximity to the production line.

Measurements in the climate-controlled measuring lab will also be a part of day-to-day operations in the factory of the future. The reason: when highly accurate measuring machines are protected from vibrations, contamination and temperature fluctuations, they attain a level of precision that will not be achievable either in the manufacturing environment or in the production cycle for the foreseeable future. These machines will be especially sought after when companies require comprehensive analyses and/or highly precise measuring values: Can a quality problem of unknown origins be solved? Is it better to improve the design or to ensure the quality of highly sensitive products? The measuring lab is the right place to answer all these questions. The off-line measurements performed in the measuring lab are then the reference for all other measurements. Yet even off-line measurements are being performed with increasing speed, a development made possible by multi-sensor measuring machines.


Just a few years ago, measuring technology operated separately from the production cycle. In the meantime, however, the importance of in-line inspection in the production cycle has grown as a means of process inspection. For example: 100% inspection integrated into production is currently being used in car body construction. This is a requirement for networked manufacturing in the age of Industry 4.0 because in-line manufacturing is able to prevent production defects before they occur. Inspection data are evaluated in real time and continuously visualized as trends in the data sequences. If statistical abnormalities are found, then the employee or the machine can react quickly to the first signs of defects. For example: a worn cutting tool can be exchanged before there are rejects.
In-line inspection requires relatively high precision and image resolution from the measuring and inspection technology, even though production conditions mean dust and fluctuating temperatures – and this must all happen at a speed suitable for the production line. Currently, it is primarily optical sensors on robots which fulfill these requirements. One example is the ZEISS AIMax sensor which inspects characteristics such as the location of bolts or columns in seconds.


At-line solutions bridge the gap between measuring and inspection technology in the measuring lab and in the production line. At-line technology is used in close proximity to the production line and is often protected by an enclosure. The workpieces can be digitized completely and then flexibly analyzed using these metrology assistance systems designed for the production environment. For example: through random sampling, these technologies quickly and easily provide staff in car body construction with an overview of how an entire part is developing in terms of its form and position tolerances and what the freeform surface actually looks like as compared to its nominal status in the CAD model. These kinds of at-line systems save time and effort in the measuring lab and deliver data on the nominal-actual comparison of the geometry at-line.

One example of this kind of at-line system is the ZEISS AIBox, in which attachments, such as car doors, are scanned optically. In order to protect the required high-resolution measuring technology from the influences of the measuring environment as much as possible, the measuring robot with the sensors is located in a closed enclosure.

Measuring data 4.0

In-line, at-line and off-line – all three technologies will share the measuring jobs in the future and provide a stable base for quality assurance. Metrology providers that want to offer their customer a comprehensive solution will need to make all three measuring technologies available and further evolve them. They will also need to devise customer-specific solutions to effectively combine these three approaches, ensuring efficiency and productivity.
Not only will data capture change in the age of Industry 4.0, but data processing will as well: decentralized intelligent systems will pre-process data in the sensor and reduce them to the most important data before sending them onward. This is how companies will be able to minimize transfer time and prevent the mountains of data from becoming unmanageable.

A steering tool for production

And one other factor will be decisive in the future: using measuring data, manufacturing software solutions will automatically provide instructions. You can already observe the first signs of this development in factories today. For example: numerous automobile manufacturers and suppliers are merging their process and quality information using ZEISS PiWeb, a central software platform.

It is still the employees who decide how, for example, they should adjust the welding robot in response to deviations in the measured values. In the future, the software platform will undoubtedly initiate these adjustments independently. If, for example, measuring data are heading in a particular direction, the system will instruct the robot to change the welding parameters, e.g. the welding current or the electrode force, as stipulated by the intelligent software module. Measuring technology will gradually become a steering tool for production in the smart factory. And it will create the necessary conditions to ensure that quality does not suffer even as companies manufacture more productively and with greater flexibility.
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