In the modern manufacturing industry, the continuous optimization of assemblies is a decisive factor for competitiveness. Many of our customers have potential for optimization in their assemblies, which primarily means combining existing components. The main aim of these optimizations is to minimize the number of individual components and thus reduce production costs and manufacturing time. This can be achieved by eliminating necessary joining and assembly production steps.
Identification of optimization potential
Identifying optimization potential is the first step in this process. As soon as we determine that an assembly can be optimized, we contact the customer to discuss the possibility of a so-called "hybrid optimization". This is a combination of our digital and fully automated AI-supported digital service and a manual analysis and optimization of the specific assembly. However, this hybrid method is only used if the optimization makes economic sense, which is usually the case for large production quantities.
The hybrid optimization process
To make a well-grounded decision about the optimization, we need specific data about the assemblies from our customers. Important information includes the mounting set-up, the orientation of the components and the forces that occur and their direction of action. This data is essential to determine which parts can be optimized and how this optimization should be carried out.
Before starting the actual optimization, we create a workspace. Within these limiting parameters, the prioritized mounting holes and other relevant parameters are taken into account. The components are then redesigned within these restrictions, resulting in a cost-optimized assembly.
Advantages of hybrid optimization
The advantages of hybrid optimization are versatile. We combine the efficiency of AI-driven potential recognition with the individualization and advice provided by a manual optimization process. By reducing the number of individual components and avoiding unnecessary processes, production costs are significantly reduced. Production time is also shortened as fewer components need to be manufactured and assembled. An additional advantage is that our Optimate app recognizes the possibility of optimization of the assembly in the control process and continuously provides information on potential without this having to be initiated individually.
Conclusion
The hybrid optimization approach is an efficient method for improving assemblies economically and functionally. By combining AI-supported analysis and manual fine-tuning, we can ensure that our customers benefit from lower production costs and increased product quality. If you have the feeling that there is potential for optimization in your assemblies, do not hesitate to contact us. Together we will find the best solution for your requirements.
