Biointelligence is one of the most noted technological innovation paths. In the future, biological and technical systems are expected to interact and learn from each other to optimally solve a given production task. Therefore, a data driven monitoring of both the biological and technical system is just as essential as ensuring interoperability between different manufacturing systems and across enterprise boundaries. In this context, the Digital Twin concept is a promising approach for physical production environments. However, in order to transfer the concept to a biological subsystem of a production process several hurdles have to be taken. Among others, these include the hitherto distinct interpretation of the concept in the life sciences and the corresponding pre-structuring of living systems. In this paper we present basic considerations for a transfer of the asset administration shell and the RAMI4.0 architecture to biological subsystems. We develop the fundamentals of an integrated scalable model which will ensure the interoperability of biointelligent manufacturing systems. As such, the paper is to be understood as a contribution to clarification between approaches from production research and the life sciences. Its primary aim is to initiate a scientific discourse across disciplinary boundaries.

生物智能是最著名的技术创新途径之一。将来，人们期望生物和技术系统相互交流并相互学习，以最佳地解决给定的生产任务。因此，对生物和技术系统进行数据驱动的监视与确保不同制造系统之间以及跨企业边界的互操作性一样重要。在这种情况下，Digital Twin概念对于物理生产环境是一种很有前途的方法。然而，为了将概念转移到生产过程的生物子系统中，必须采取几个障碍。其中包括迄今为止对生命科学中的概念的独特解释以及对生命系统的相应预构造。在本文中，我们提出了将资产管理外壳和RAMI4.0架构转移到生物子系统的基本考虑。我们开发了集成可扩展模型的基础，该模型将确保生物智能制造系统的互操作性。因此，该论文应被理解为对生产研究方法和生命科学方法之间澄清的贡献。其主要目的是启动跨学科界限的科学论述。该论文应被理解为对生产研究方法和生命科学方法之间澄清的贡献。其主要目的是启动跨学科界限的科学论述。该论文应被理解为对生产研究方法和生命科学方法之间澄清的贡献。其主要目的是启动跨学科界限的科学论述。