Relevance
The increasing interdisciplinary nature and division of labour mean that the number of people, departments and various companies involved in the development process is increasing significantly. The number of available - but also used - methods and tools in product development is also steadily increasing. In the various departments, a large amount of data and information is generated which is necessary for the protection or which represents the result. Their availability and coordination is an essential basis for efficient and effective development processes.
To ensure effective and efficient backup, all the necessary data and information must be available in the right place at the right time and in sufficient data quality. Missing data and information, which is also unnecessary and unsuitable or cannot be evaluated, slow down or hinder the hedging process. In the worst case it can lead to misinterpretations and not meaningful results, which can lead to development errors or even defective products.
Problem Definition and Focus
Different departments (e. g. testing and simulation) have different ways of thinking, deal with different phenomena and usually do not use the same tools for their security measures. This leads to unequal data characteristics and data qualities. Different information requirements from the same data record can lead to missing or not being used. Existing or generated data are sometimes not used because the user does not know that this data exists. On the other hand, too little data is collected at one point because it is unknown that this data is needed elsewhere. Development processes in companies are usually described very generically and are often only put into practice theoretically. Existing data and information flows are often documented too imprecisely, insufficiently or not at all.
In this context, we focus on the following research priorities:
- Detailed analysis and presentation of development processes
- Data and information flows in the back-up area
- Simulation and test data management
- Requirements, risk and quality management
- Process parameters in product development