Data-driven transformation: a structured approach to digitalisation in industrial processes

Nowadays, in the industrial sectors, technical and management teams understand that data means knowledge about the product or the process. The digital transformation has boosted the ability to obtain previously invisible information, with increasingly simple data acquisition methods, advanced analytics, and better connectivity. It is now possible to achieve greater knowledge over the manufacturing process than ever before. For this, it is essential to have an effective strategy to harvest and use the data, implementing a standard procedure in technological interventions on different equipment. This work presents a proposal to implement a data operationalisation strategy for new or already in use industrial machinery, based on five steps that range from hardware selection to the implementation of an automatic data analysis solution. The required effort is also reflected in an iterative process where each step requires a validation method that represents a decision point between moving forward in the strategy or going back, ensuring that the main goals remain solid, as well as presenting specific approaches to face the challenges, the needed resources, and identifying expected restrictions or difficulties. This is a methodology focused on the specifics of the process under analysis that foresees a technological intervention over an equipment, guiding the architecture towards the expected results and identified objectives.