ConAct 2023-2025: Expert Congregation of Quality Activities
This project is co-funded by the European Regional Development Fund (ERDF).
Persistently high-quality work is not the final result of using a specific method or procedure. Rather, high-quality work is the result of the continuous pursuit of improvement and adaptation to changing requirements. An excellent illustration of this philosophy is the PDSA cycle (Plan, Do, Study, Act), which allows quality standards to be systematically mapped out (Plan - Quality planning), checked (Do - Quality assurance), any variations investigated (Study - Quality control) and resolved through appropriate actions (Act - Quality improvement).
The development of a multi-criteria decision-making process for clustering detailed activities, taking several criteria into account, is intended to:
- Structure the activities according to the criteria,
- Prioritizing the tasks between the clusters and within a cluster (derived from the artifact criteria as an integral part of the multi-criteria decision-making process),
- Create the best activity clusters for users according to the criteria;
- In addition to the artifact criteria, other criteria (usually use case-specific) can be included in the decision-making process.
The algorithmic development of the processing sequence provides the development projects with high added value, as previous manual prioritizations are replaced by an ideal solution. This solution takes all criteria into account, while simultaneously making these criteria explicit.
Project partner: Model Engineering Solutions GmbH
"We at Model Engineering Solutions (MES) strive for a world of safe technology in mobility. Our tools and expertise ensure the quality and safety of embedded software in a software-driven world to make tomorrow’s mobility safer." We advocate quality assurance in the model-based development of embedded software. Our main focus is static model analysis and model improvement, primarily in MATLAB Simulink, the automotive industry's leading development platform. Implementing the MES Tools MXAM, MoRe , and MQC right from the start ensures that errors are detected and corrected at an early development stage.
Project partner: Technische Universität Berlin
The Production Technology Center at the Technische Universität Berlin has stood for future-oriented research and teaching for a quarter of a century. 25 years of interdisciplinary collaboration have brought Berlin's quality science field into an outstanding position both in the scientific and industrial environment.
The Quality Science Department at the Institute of Machine Tools and Factory Management at the TU Berlin is engaged in the research and development of approaches and methods for model-based, holistic quality description and evaluation, as well as procedures for applying the developed methods in the product life cycle, both in production and service provider companies. Alongside increased product and process quality, the goal here is to improve efficiency in a company's organization.