Capacity Building for Digital Work – A Case from Sino-German Cooperation

Abstract

AbstractThe way humans work is constantly changing. This has always been the case, especially in dynamic environments. In the context of Industry 4.0 and the Internet of Things (IoT), collaborative platforms, accelerated by Artificial Intelligence (AI) technologies, give rise to new automation opportunities of complex and previously labor-intensive tasks, while also creating new business models for multiple stakeholders.Due to accelerated product innovation, the manufacturing industry needs to be able to generate solutions in a timely manner and quickly move them into production according to customer expectations. Today, machines in an Industry 4.0 factory are collaboratively connected. Such a development requires the application of advanced predictive tools that can systematically transform requirements and data into information and ultimately knowledge to manage uncertainties and make informed ad hoc decisions. In this context, a production system needs to perform rapid self-reconfiguration in response to different product characteristics to achieve an agile transition to the new manufacturing processes. However, a large number of non-standardized device interfaces and communication protocols are currently existing on the shop floor, which leads to high time and capital costs. Furthermore, this leads to insufficient reliability in the configuration of the production system, so that the requirements for customization and rapid adaptation cannot be met. In addition, there is also a large knowledge gap in the academic field of self-configurable intelligent production systems using collaborative engineering and IoT platforms.Therefore, Karlsruhe Institute of Technology (KIT, Germany) and Tongji University (Shanghai, People´s Republic of China) have proposed the collaborative “Construction, Reference Implementation and Verification Platform of Reconfigurable Intelligent Production Systems” and the “Factory Automation Platform”, which meets the challenges of self-configuration, agile response, accumulation of domain knowledge and services, intelligent operation and maintenance of production systems.