Inter-Data Analytics for Optimization of Offshore operations and planning
Knowledge Management (KM) has provided many positive aspects for an organization to achieve better performance. There are various ways of managing the knowledge, however new challenges continually arise and new strategies need to be adopted to solve these challenges. The major challenge of KM is on leveraging of big data and its link with it. Big data analytics help in understanding and extracting valuable knowledge from the huge volume of data and this knowledge then can be used for enhancing the performance of many different processes in an organization. In organizations, big data is especially important as massive amounts of data are generated during the many different process.
In recent years, with the development of diversity of marine data acquisition techniques from marine vessels, marine data grow exponentially in last decade, which forms marine big data. This big data from marine vessels, can then be widely used for performance monitoring, condition monitoring, environmental forecasting, critical situation visualizations, modeling of equipment shutdown/ failures etc., These information from the analysis of big data helps vessel operators to optimize their vessels day-to-day operations.
However, some organization who charter vessels from different companies for their operations finds it difficult to have the complete picture of all these vessels performance. It is therefore essential to solve this gap and where by big data from different vessels can be integrated and analysed on the same platform. This is a great challenge for organization as marine big data involves privileged, confidential and strategic data, making it vigilant for cyber threat. Therefore, security of data is imperative when it involves more than one data owner. Data security involves in all the process of marine big data management, security in data storage, data access, data computation , data sharing and data supervision must be considered all over marine data management.
The latest improvement in technology has helped organization to deal with the challenges of marine big data such as availability, storage, accessing and sharing in an efficient manner. Thus KM, with assets of such big volume of inter-data from various similar type of marine vessels has the possibility to identify interrelationship between the big data. Deep Learning algorithm has proven to be an effective tool for big data analytics. The deep learning algorithm extracts high-level, complex abstractions as data representations through a hierarchical learning process. Complex abstractions are learned at a given level based on relatively simpler abstractions formulated in the preceding level in the hierarchy. A key benefit of deep learning is the analysis and learning of massive amounts of unsupervised data, making it a valuable tool for big data analytics.
The information retrieval from the online stream of marine big data with the help of deep learning algorithms, provides us the knowledge for optimizing operations. The knowledge gained from a particular process in a vessel can then be transferred over to other similar vessels. This helps in inter-cross knowledge transfer across similar marine vessels systems. For example, voyage of a vessel which resulted in good fuel performance index can be applied while planning a similar voyage for another vessel, a predicted environmental loads on a vessels can be used applied for another vessel to minimize the effects.,
Thus with the help of deep learning technique for marine big data, it is possible to have knowledge transfer which will be help for optimization of offshore operations and planning.
