Component-adaptive design with AI
WITTE kicks off AI project with a kickoff meeting.
By integrating AI into development processes, companies can operate more efficiently, reduce costs, and bring innovative products to market faster. AI-based technologies already enable machines to learn, analyze, and respond autonomously, leading to more efficient processes, increased productivity, and improved quality standards. To achieve enhanced efficiency in the development and design of mechanical products, the combination of Knowledge-Based Engineering (KBE) and Reinforcement Learning (RL) is advantageous.
WITTE, a pioneering provider in the field of modular, reusable clamping, positioning, and measuring devices, will launch a joint research project in May 2024, in collaboration with the Chair of Manufacturing Technology and Business Organization (FBK) at RPTU Kaiserslautern, as part of a kickoff meeting. The goal of the research project is to make the design process of customized clamping systems more efficient and faster through the use of an ML-based software tool.
Lean and accelerated design process
The design of customer-specific clamping systems becomes significantly easier and more repeatable through the use of standardized modular elements, such as ALUFIX. However, despite the high level of standardization, the design process is still time-consuming and therefore costly. This is due to varying customer requirements and numerous design possibilities, necessitating close coordination between WITTE and the customers. To reduce the time and costs associated with product development—primarily achievable through the automation of repetitive design tasks while simultaneously capturing, storing, and reusing design knowledge—the approach of using artificial intelligence (AI) is a logical choice.
The advantages are clear:
- The use of a design assistance system increases productivity within the design and layout of clamping systems.
- Since AI systems enable precise quality control and contribute to the reduction of errors and waste, significant iterations are minimized. Thus, AI-supported design also leads to early error detection and prevention.
- AI can help explore new avenues in product development by analyzing data and recognizing patterns that engineers may overlook.
- Development of new business models and services through the use of ML-based software tools. Learning systems and AI methods enable the extraction of knowledge from extensive and complex data and generate new insights—which can, in turn, serve as the basis for changed and innovative business models.
Exciting interdisciplinary collaboration
To fully harness the advantages of artificial intelligence in design, close collaboration between researchers, engineers, and manufacturers is essential. Therefore, WITTE has decided to bring together an interdisciplinary collaboration from the fields of ML, design, and expert knowledge surrounding clamping systems, culminating in this research project. WITTE already has experience in developing automated design solutions. In cooperation with the Institute for Integrated Production in Hanover, a proprietary software solution called ALUFIX Expert has already been developed. Georg Wockenfuß, Head of Design at WITTE and coordinator of this project, commented on the idea behind it: “With the right approach and a clear vision for the future, artificial intelligence can usher the design process into a new era. We are curious to see how this project develops and how the collaboration unfolds. Since the FBK can bring expertise from currently ongoing research projects, I am confident that we will develop a system that will make the component-adaptive design of customer clamping systems faster, more effective, and more cost-efficient.”
