Proposal for a Digital OEE Architecture with the Integration of Analysis Parameters of Machines of the Manufacturing Industry

Sudden and unexpected economic changes associated with market competition and short product life cycles have generated significant organizational challenges. Thus improvements in processes and product characteristics can directly interfere with their production capacity. To identify improvements in the process, it is fundamental to analyze how the process is developing and, based on that, make favourable decisions. Today, several companies analyze their data, but most of these are done by manually collected data, which brings much uncertainty and can delay the analysis and decision-making process. The present work aims to propose a digital architecture to calculate the OEE (Overall Equipment Effectiveness) for machines in the manufacturing industry. The relationship between the behaviour parameters of the machines allows for diagnosing critical factors for the production system, namely performance, availability, and quality. The machine parameters presented in a short period allow faster action by operators in cases of failures in the activity, and greater security in the planning of the production process, as well as in the development of products and maintenance schedules, directly impacting the production cost. The project's innovation is carried out through digital data modelling based on the ETL context with parameters derived from the behaviour of a machine, where they are dynamically processed and correlated in the Desktop software to illustrate the calculated OEE value.