| dc.description.abstract | This thesis investigates a theoretical framework for the synchronization of production and maintenance activity planning by implementing Industry 4.0 technology digital twin in the continuous production system of the oil and gas industry, to improve performance in production efficiency, reliability, and cost. In the oil and gas industry, a high degree of equipment maintenance is essential along the entire route from the source to the customer, to ensure product quality and to meet demand. Maintenance activities account for almost a quarter of the cost in the product life cycle, in the competitive market. To minimize this outlay, unnecessary maintenance activity could be reduced by finding a better solution for synchronizing with production activity. Industry 4.0 represents a new kind of industrial revolution, promising increased flexibility in manufacturing, and better product quality, where digital twin plays an important role in the simulation of physical assets, and the use of digital analytical models can provide more detailed insight into the manufacturing process and allow more efficient maintenance decisions. With the implementation of a digital twin, information shared between maintenance activity and production activity will benefit production planning and maintenance planning. This project has identified levels of integration, planning horizons, and production systems as factors that have to be considered, while also describing a procedure for data exchange and collection in the production system. The numerical modeling in this project demonstrates how a natural gas production system can benefit from predictive data informing production and maintenance planning. A recommendation for future work is to focus on a real-time data transmission model, and to determine which data collection and exchange procedures are best suited for preventive maintenance strategy. | |