The Importance of Automation for Networked Manufacturing and Digitization

Automation allows for a straightforward interaction between administrator and operator.  It facilitates intuitive order management, provides accurate measurements and enables integration with existing production systems, including connection to an ERP and QM system. Bruker Alicona offers tried and tested solutions for this.

The demands on measurement systems have changed with a movement towards implementing quality assurance and metrology as an integral part of the production. Full automatable measuring systems are now required so that they can be operated at any time. Systems that provide robust, traceable and repeatable measurements are needed for complex components with tight tolerances. Finally, to ensure networking and communication between all systems in a production chain, an industry-standard interface technology is essential. Rejects can then be prevented at an early stage as manufacturers receive real-time data on production trends.

Implementing a Smart Manufacturing production concept brings about many demands, all of which are intensively dealt with by the optical metrology supplier, Bruker Alicona. Using Focus-Variation technology, the company now offers tried and tested solutions.

From "simple" automated measurement up to the realization of Smart Manufacturing, below is an overview of the range of available automation options.

Automatic Measurement of Dimension, Position, Shape and Roughness

Automation interfaces allow for micro-precision parts on large surfaces to be measured automatically and independent of operators. The interaction between an administrator who works on the teach-in of measurement programs and an operator who starts the measurement forms the basis for taking measurements of shape. This includes distances, roundness, flatness, shape deviation and positional relationships. Measurements also include roughness parameters and cutting-edge parameters (radius, contour, angle etc.).

Implementation takes only a few steps and programming knowledge is not required for the teach-in as it is designed for ultimate user-friendliness. A drop-down menu or barcode identifies the component to be measured and the corresponding measuring program begins automatically. A measurement protocol, including ok/not ok data, is then sent to the machine operator.

Digital Measurement Planning

Measuring points, measuring directions, etc. already in the CAD file of the reference part can be defined through a CADCAM. Automatic calculation and synchronization of tilting angles, travel ranges in XYZ and rotation angles are then possible.

Reliable measurement planning is supported through a simulated preview of the planned measurement process. As such, users no longer need to spend time defining measurement positions on the real component – an attractive solution for those who are required to define and teach over 100 measuring positions.

Extended Database Management

A barcode scanner can automatically recognize the measuring programs stored for a single component or a whole batch and can, therefore, assign each measurement according to the respective order. Furthermore, freely editable and configurable fields allow for the addition of information such as end-user/customer, operator, machine tool, etc. User-specific reports are then able to check for continuous quality production along with other things. It also facilitates the early detection and correction of deviations.

Connection to a QM and/or ERP System

ERP and QM systems can be connected through an option in Bruker Alicona measuring system. As such, the ERP via DMC or RFT can be accessed by measuring systems to obtain the nominal values, tolerances and measuring strategies stored within them. Production managers can access all production data from their global locations as measurement results are fed into the QM system. This enables them to react immediately to negative and positive trends. The autonomous, user-independent creation of measurement programs can also enable the networking of measurement data, ERP and QM systems.

Machine to Machine Communication

Adaptive production planning and self-optimized production are usually targeted by modern production facilities. Such facilities are typically based on connected, networking machines and measuring technology. Integration of measurement technology directly into manufacturing is required for this. It also needs to be part of a networked production chain. If a faulty component is detected by the measuring sensors then this information is automatically fed into the production cycle, which, in turn, automatically adapts or corrects itself.

With minimal programming effort, measuring systems can be flexibly integrated into existing production systems through industry standards such as TCP/IP, Modbus TCP or Remoting. Pre-defined measuring and testing programs are carried out by fully automatic measuring equipment and machine tools.

Automatic clamping/unclamping of components and equipping measuring systems with a robot (“Pick & Place”) are also carried out in this way. It is even possible to measure without clamping, for example, directly in the machine tool. This is possible by combining a measurement sensor with a collaborative robot arm. In this situation, the sensor is manipulated automatically to the workpiece in a machine tool.

Intelligent Algorithms for Automatic Segmentation and Classification

The automation options are finished off with a selection of expansion options for automatic segmentation and classification of surface features. Intelligent, self-learning algorithms provide a smart method to characterize, segment, analyze and classify surfaces. At the same time, relevant parameters for surface evaluation are derived and evaluated automatically. Grain size distribution on grinding tools can be analyzed through solutions offered by Bruker Alicona. Similarly, solutions are also available for the evaluation of sandblasted and laser-machined surfaces.

This information has been sourced, reviewed and adapted from materials provided by Bruker Alicona.

For more information on this source, please visit Bruker Alicona.

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