Self-optimizing Manufacturing Systems for Laser Cutting
Manufacturing in high wage countries has a growing influence on the local economy. Innovative manufacturing systems are the base of an efficient production of goods which are expected to fulfil increasing customer expectations with respect to quality and delivery time. The market share of laser based manufacturing systems is
facilitated by a continuously increasing level of technology. New drives and faster control systems in combination with enhanced laser sources lead to an overall increase in performance of the systems. Robust manufacturing systems require this advance to go in line with the stability of the process itself, considering all the variations in boundary conditions.
Practical Issues
Quality of laser cut products is defined by the client’s application. If the defined dimensional precision is reached, properties of the cut face come into scope. One prerequisite for a high quality cut is a good command of the laser beam’s focus position. In CO2 cutting, this focus position can be determined by mounting a diagnostic measurement device into the machine and measuring the energy distribution. In the practical application, most industrial cutting machines provide a calibration routine that allows the operator to determine the focus position, and transfer its value to the machine. As the focus position is subject to change over time, the machine is only calibrated when the calibration routine has just been executed. Once the focus position is known, other parameters move to the foreground. The major influences on the process are associated to technical boundary conditions and material compositions which altogether determine the absorption of the laser energy and result in the establishment of the cut front. Laser cutting is an industrially established manufacturing process which is widely adopted with an increasing amount of automation. Future potentials in technological advance of this manufacturing technology are seen in innovative, automated assistant systems based on self-optimizing capabilities.
Approach
In a multitude of cases, process problems cannot be solved by simply adding sensors. The focus position for
example cannot be measured directly during cutting as the relevant part of the kerf is sited in the kerf itself. It is
the width of the kerf that can be measured during processing and fortunately, it can be related to the focus
position. This relationship is embedded into a model which contains expert knowledge. As such, the measurement value of a surrogate criterion like the kerf width can be used to determine the focus position. If this approach
is applied to other “inaccessible” process variables, then information for the determination of the entire manufacturing system’s operating point can be gained. With this knowledge, the system can be optimized on product quality.
Contributions to the solution:
- Development of numerically evaluable surrogate models that describe the laser cutting process
- Implementation of decision units based on embedded process knowledge
- Realization of an information exchange with product planning systems on enterprise level
- Design of interfaces for the interaction between humans and the self-optimizing manufacturing system