Markets, stakeholders and information technologies will constantly evolve making it challenging for a single organization to keep up with the competition. Modern production enterprises are responding to this challenge with industries 4.0 and interoperable solutions in collaborative networks to become more reactive and innovative for their organization and their production systems. The International Conference on Enterprise Interoperability (I-ESA 2018) is presenting interoperable solutions for enterprises from a research and business impact point of view. The workshops address Smart Services and new technologies like the Next Generation Internet (Internet of Things, Cloud-based platforms, and Artificial Intelligence) applied in Future Manufacturing systems using Digital Transformation. The proceedings contain short papers from eleven workshops and from a Doctoral Symposium. One particular method used for each workshop has been to exchange knowledge about actual research and applications and to interactively discuss issues and new ideas between the presenters and the audience of experts from research and industry. Because the growth of internet of things (IOT) technology, stakeholders who come from different research areas (information modeling area, dynamic process modeling area, and so on) will very easily and simultaneously evaluate and control the manufacturing process from all over the world. Therefore, there is an urgent need for a comprehensive enterprise modeling methodology with the integration of information modeling and dynamic process modeling method. However, it is known that there is limited research on the realization of a modeling methodology that can simultaneously handle information modeling and dynamic process modeling. The method for object-oriented business process optimization (MO2GO) system performs modeling in terms of information and process. However, the process modeling part in this system is static. Meanwhile, the Petri net mathematical modeling language has strong dynamic simulation capability. Thus, our main contribution is to analyze the characteristics of Petri net, which would be helpful to the dynamic process modeling realization in the MO2GO system, and integrate Petri net engine into the MO2GO system to allow a static process model to become dynamic. In here, the system can not only display a simulated manufacturing process but also calculate actual information (time and cost) for a final manufactured product. Therefore, it is possible for the system to handle both information modeling and dynamic process modeling. Finally, the MO2GO system will be more competitive in the future industry.