Modelling a Big Data-based Analytical Process: an Aerospace Case Study

Industry 4.0 experienced a wide range of cutting-edge technologies, including Big Data Analytics (BDA). BDA plays a key role in extracting value from industrial Big Data to uncover hidden patterns, correlations and market trends. In smart manufacturing, it also supports the improvement of operations and production, the reduction of machine downtime, the enhancement of product quality and a more efficient supply chain. When approaching with BDA project, it is important to accurately model and design the entire process for achieving a specific analytical goal. This paper aims to understand how to model a big data-based analytical process within manufacturing environments. To achieve this goal, starting from a theoretical background on standards for modelling analytical processes, the paper proposes the BigDAM (Big Data Analytics Modelling) framework, as an integrated conceptual representation of the key steps to consider in modelling a BDA path. Also, the framework is contextualized within an aerospace case study.