Monitoring production systems is a key element for identifying waste and production efficiency, and for this purpose, the calculation of the Key Performance Indicator (KPI) Overall Equipment Effectiveness (OEE) is validly recognized in the scientific literature. The collection and analysis of the cause of the interruption of the plants is particularly useful in this sense. The use of Internet of Things (IoT) technology in order to automate data collection for the purpose of calculating the OEE and the causes of interruption is effective. Furthermore, the existing literature lacks research studies that aim to improve the data quality of important process data that cannot be collected automatically. This study proposes the use of IoT technologies to request targeted and intelligent information inputs from the operators directly involved in the process, improving the completeness and accuracy of the information through the real-time and smart combination of manual and automated data. The Business Process Model and Notation (BPMN) methodology was used to analyze and redesign the collection data process and define the architectural model with a deep knowledge of the specific process. The proposed architecture, designed for application to a plastic injection molding production line, comprises several elements: the telemetry of the injection molding machine, an intervention request system, an intervention tracking system, and a human–system interface. Furthermore, a dashboard was developed using the Power BI software, 2.122.746.0 version, to analyze the information collected. Reducing the randomness of manual data makes it possible to direct production efficiency efforts more effectively, helping to reduce waste and production costs. Reducing production costs appears to be strongly linked to reducing environmental impacts, and future studies will be able to quantify the benefits obtained from the solution in terms of environmental impact.

Purpose: This article presents a procedure for assessing the maturity of maintenance management information practices and defining improvement actions. It focuses on supporting companies, small and medium enterprises (SMEs) in determining their information technology (IT) needs and introducing suitable informative infrastructures. Design/methodology/approach: A comprehensive procedure for assessing the maturity of maintenance management information practices and defining improvement actions is proposed. It consists of five steps: designing the current state of maintenance, identifying IT needs based on maintenance goals, applying an assessment model to identify weaknesses and strengths, proposing improvement actions based on maturity level and enabling continuous improvement. The procedure provides the applicability of the assessment model to evaluate the maturity levels of different databases: Equipment, Maintenance Personnel, Work Order and Report. Findings: The model was applied to a company’s maintenance process. Improvement actions focusing on enhancing the informative infrastructure and improving information management practices have been designed based on the current maturity assessment. The findings and recommendations provide valuable insights for SMEs seeking to enhance their maintenance effectiveness and adopt appropriate IT solutions. Originality/value: The proposed procedure and the maturity model contribute to the field of research by addressing the specific needs of SMEs in assessing their maintenance management information practices. The model provides a roadmap for SMEs to identify weaknesses, prioritize improvement actions and enable continuous improvement. By leveraging the benefits of information systems, SMEs can enhance their maintenance processes, increase competitiveness and achieve higher maturity levels in maintenance management.