Rapidly evolving market requirements and fast technological changes force enterprises to target-oriented implementation of smart production and organizational solutions. The continuous evaluation of new business models and according production processes or the modernization of existing production facilities are the foundation for future competitiveness. Therefore, a holistic approach involves modern production technologies, simulation tools, data analytics and continuous optimization of value creation processes.
Target-oriented implementation of industrial robots, machine vision and automation are key factors for the development of new – or the modernization of existing – manufacturing facilities. Real offline simulation tools help to evaluate performance and potential flexibility or to optimize final software parts – even before real hardware is purchased.
Rapid advancement on all technological levels – e.g. collaborative robot systems, automated guided vehicles (AGVs) or computer vision systems based on machine learning – constantly change the opportunities at production facilities. Feasibility studies, technological concepts or function prototypes evaluate these technologies and facilitate their company-specific integration.
Operations research methods as well as computer based simulation studies are widely used to enhance the design of production and logistic systems. Furthermore, this studies support the decision making process for production planning and control. On the backdrop of integrated data processes and stochastics, the aim is to explore relationships and effects systematically.
Collecting, storing, collating and analyzing of data from production processes or products can be used for process or product improvements and for evaluating useful industrial internet of things (IIoT) scenarios. In-depth data analysis can be used to establish a monitoring system for processes or products and thus help to reduce response times to unplanned events.
Production Optimization within the context of lean and six sigma aims at an increase in efficiency and quality while simultaneously reducing cycle time. This can be achieved by either the application of analytical methods or by empowering the organization to execute the efforts by itself.
The development and introduction of new products and (production) technologies is a major change for many companies, and especially SMEs, in their existing processes, strategies and business models. Holistic analysis and solution approaches consider the potentials of new (production) technologies and smart value-added processes for companies. Based on this, we develop a roadmap for successful implementation and the successful achievement of strategic goals which, if required, is divided into agile sprints.
Technological progress causes big changes both on the individual and on the organizational level. Sustainable and ongoing transformation is only possible if individual employees and the entire organization go along with this transition. By using qualitative research methods, company-specific challenges are analyzed in detail, appropriate success factors are developed and obtained findings are transferred into implementation recommendations.
At the intersection of new technologies and human behavior, (production) assistance systems as well as different interaction strategies and their effects on business processes are examined. Resulting studies investigate the acceptance, usability and ergonomics of technology, as well as the optimal transfer of necessary competences – transferred into company-specific training concepts.
Modern production facilities are strongly based on software and automation systems. For defining company-specific and target-oriented actions, an analysis of processes and according software systems must be carried out. By the development of a holistic approach and an according system respectively software design short-, medium-, and long-term expansion stages can be defined. This may include concepts and designs of new methods, tailor-made algorithms, and software modules – e.g. for operating and machine data logging, for integrating automated guided vehicles (AGVs), or for using machine learning algorithms. Furthermore, retrofitting – target-oriented modernization – of existing machines and plants can enable integration in existing software systems or into the industrial internet of things (IIOT).
Research areas at a glance
Research Areas at a glance