Over the past month, we had the pleasure of hosting a series of webinars in which we highlighted the main challenges and needs of Italian manufacturing companies, sharing best practices for industrial plant and factory department monitoring. 

In each webinar session of this series, a selected industry expert guest speaker described the path that companies must embark on to embrace Industry 4.0, with a particular focus on key data for optimizing production processes, how to extract them, and why.

A brief demo of the Zerynth Platform concluded each meeting, leaving space for questions and discussions.

Missed one of our sessions? You can watch recordings of all our past webinars on-demand, whenever and wherever you prefer.

Optimizing your industrial production processes. Interview with an expert.

In our latest webinar we addressed the challenges that Italian manufacturing companies face in streamlining production from an efficiency standpoint. The webinar was introduced by Mario Rapaccini, Associate Professor at the Department of Industrial Engineering at the University of Florence and instructor at the Industry 4.0 Master’s program. Throughout the event, Mario shared best practices and solutions for transforming data into actionable insights for strategic decision-making.

During the interview, Mario answered important questions that companies encounter on their path towards industrial digitization. For example, we discussed how to manage the enormous amount of data generated by production processes, sharing common insights and best practices for turning this data into meaningful information for decision-making at a strategic level.

Another crucial topic discussed was the importance of intuitive and effective industrial plant monitoring tools for the production process. Mario emphasized the need for simple, immediate, and intuitive tools that enable companies to effectively monitor production and identify any inefficiencies or anomalies. These tools allow companies to make timely and targeted decisions, and improve overall production efficiency.

The webinar concluded with a demo of the Zerynth Platform, an advanced solution for extracting and visualizing machinery data on dashboards. During the demonstration, we illustrated how machinery data (alarms, produced parts, machinery availability, and performance) can be leveraged to calculate Overall Equipment Effectiveness (OEE) and estimate overall production efficiency. The ability to measure and optimize efficiency contributes to increased final revenues for manufacturing companies.

Improving production efficiency and overall processes.

One of the key topics we addressed during our recent webinars was the necessary balance between energy efficiency and production efficiency. Leveraging Industrial IoT, companies can achieve real-time and remote monitoring of their industrial plants and optimize production. Through data analysis and the implementation of intelligent solutions, it becomes possible to identify potential inefficiencies, improve resource utilization, and reduce operational costs.

How to achieve overall production efficiency?

  • Extracting data related to machinery energy consumption to identify inefficiencies.
  • Real-time monitoring of performance metrics (such as availability and quality) or energy consumption to make immediate decisions.
  • Integrating OEE data on a single dashboard.

By implementing these practices, companies can gain insights into energy consumption patterns, identify areas for improvement, and make data-driven decisions to enhance overall production efficiency. The integration of key metrics on a unified dashboard provides a comprehensive view of the production line, allowing for better analysis and optimization efforts.

Figure 1. Production Insights – Zerynth for production efficiency

Maintenance is a crucial aspect to ensure the proper functioning of industrial plants. 

During the webinars, we explored the importance of predictive and condition-based maintenance, which allows companies to anticipate failures and plan preventive maintenance interventions based on the actual conditions of their machines. Industrial IoT provides real-time data on the status of assets, enabling the mapping of sudden stops or any emergencies.

What are the key points to consider for condition-based or predictive maintenance?

We’re referring to:

  • Continuous monitoring of machinery performance KPIs and production parameters within industrial plants.
  • Identification of trends, patterns, and anomalous parameters that hinder optimal performance.
  • Immediate alarms and notifications to alert maintenance teams or production managers, enabling prompt actions in case of issues.