Modern manufacturing operations rely on accurate, real time data for efficient operation and control of the production process. Many small and medium sized enterprises (SMEs) still operate with legacy assets, limiting their access to a clear data picture. This thesis research and its design solutions help SMEs gain real time insights into their manufacturing process, resulting in production efficiency gains and helping identify process improvements. These factors help manufacturing SMEs stay competitive in an ever-increasing competitive global business climate.

The primary objective was to identify the requirements for enabling real-time insights into SME manufacturing operations. Findings suggest that in-house infrastructure can facilitate the required transparency, provided it is lightweight and minimalistic. The essential factor is to transform machine-generated data into insightful metrics for relevant stakeholders. A significant aspect to consider is the human element— the adoption and commitment of employees towards the technology.

Upon analyzing the benefits, the research underscores that real-time insights lead to enhanced production efficiency. By offering an objective view into production data, SMEs can quickly identify and rectify bottlenecks. Moreover, such transparent insights improve communication within teams, empowering employees by showing the direct impact of their performance on overall production, thus boosting their morale and productivity.

The study also evaluates the key features needed to make these real-time insights actionable. Contrary to initial assumptions that a single KPI would suffice, it became evident that a more comprehensive view—incorporating metrics such as Overall Equipment Effectiveness (OEE)—was necessary. For SMEs with diverse product portfolios, additional parameters like average batch size, cycle time, and machine power-on time provide valuable context.

Lastly, the implemented design framework showcases the positive impacts of real-time insights on production. Access to objective metrics aids in performance evaluation, problem identification, and the formulation of improvement strategies. An essential feature highlighted is the predictive capability that guides resource planning, thus minimizing errors.

This research emphasizes that manufacturing SMEs with legacy assets can achieve real-time insights into their processes through cost-effective, lightweight solutions. The proposed methods and guidelines, as discussed in detail in the design section, are foundational for SMEs aiming to modernize their operations and bridge the knowledge gap in implementing real-time monitoring. By offering universal access to transparent production metrics, SMEs can optimize their processes, ensuring better efficiency and communication at all levels of operation.