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IoT Intelligence and its potential in a real-world use case

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IoT Intelligence

In the landscape of modern industry, IoT Intelligence represents a fundamental approach for companies looking to enhance and manage their production processes. One of the most significant challenges for businesses is fully leveraging the potential of the Internet of Things (IoT) to gain tangible competitive advantages.

This entails effectively integrating sensors, devices, and digital platforms to acquire and analyze data in real-time, enabling companies to make the best possible decisions in short timeframes.

In this article, we will examine a real-world use case that highlights the effective application of IoT Intelligence in an industrial bakery. By utilizing a network of sensors installed at various stages of the production process, the company gained a detailed and instantaneous view of its operations. For example, temperature sensors constantly monitored the baking environments, ensuring compliance with quality standards and reducing the risk of waste or defective products.

In addition to improving internal efficiency, the deployment of IoT Intelligence has opened up new service opportunities for the bakery. Through the analysis of consumer data and market trends, the company personalized its product offerings and launched targeted promotions, thereby increasing customer loyalty and expanding its customer base.

Industrial Bakery Production Process with IoT Intelligence

As anticipated, the context is that of a cutting-edge industrial bakery, where automation and technology drive every phase of production, from mixing to baking, packaging, and distribution. This bakery represents a tangible example of the application of Industry 4.0, where smart machinery and IoT systems work together to ensure efficient and high-quality production.

The first step in optimizing any process is to fully understand how it works.

Process Schematization

As illustrated in the preceding figure, the process begins with a dosing machine that accurately weighs and doses the raw materials needed for dough preparation. Once the ingredients are measured, they are transferred to industrial mixers, where they are blended until they achieve a homogeneous and perfect consistency.

Subsequently, the dough is sent to specialized machinery that gives the desired shape to the products, which can be bread, baguettes, or other baked goods. These machines are equipped with IoT sensors that constantly monitor parameters such as temperature, pressure, and processing speed, ensuring unprecedented precision and uniformity.

Once formed, the products are placed in controlled proofing chambers, where they are exposed to optimal conditions to develop their flavor and texture to the fullest. Even at this stage, IoT sensors play a crucial role in monitoring and regulating proofing conditions, ensuring consistent and high-quality results.

After proofing, the products are ready for the baking phase. The industrial ovens, also equipped with IoT sensors, can precisely regulate temperature, humidity, and baking time to ensure optimal results in terms of browning, consistency, and taste.

Once baked, the products undergo a rapid cooling and freezing process, which preserves the freshness and quality of the products until the time of distribution. Finally, packaged products are stored in refrigerated storage cells, ready to be shipped to end customers.

Application and Benefits of Using PlugAIn for the Industrial Bakery

To optimize and effectively manage this complex production process, we used the PlugAIn platform. The PlugAIn Big Data processing architecture is distinguished by its ability to model production processes (thanks to its BPM component) in detail, allowing seamless integration of data from Industry 4.0 machinery with those related to various process stages.

Process Modeling in PlugAIn

The use of PlugAIn has brought numerous benefits to the industrial bakery. First and foremost, data analysis has identified areas of inefficiency and improvement in every phase of the production process. For example, downtime in machinery has been identified, allowing the team to plan preventive maintenance interventions to minimize unplanned downtime.

One of the analysis dashboards created in PlugAIn

Furthermore, IoT Intelligence has enabled greater traceability and quality control of products. Each batch of products can be monitored and traced through all stages of production, ensuring compliance with safety and quality standards.

Thanks to the PlugAIn platform, the bakery has also implemented a more efficient inventory management system. Integrated IoT sensors have provided real-time data on the status of ingredient and material stocks, enabling more precise production planning and minimizing waste.

Finally, the adoption of PlugAIn has promoted transparency and communication within the company. All employees involved in the production process can easily access relevant data and information through an intuitive interface, facilitating collaboration and coordination between teams.

In summary, the integration of PlugAIn and the use of IoT Intelligence have radically transformed the operations of the industrial bakery, improving efficiency, quality, and overall production process management.

Conclusions

The industrial bakery use case clearly illustrates the transformative potential of IoT Intelligence in industrial contexts. By integrating and analyzing IoT data with those related to the production process, it is possible to gain a detailed insight into operations and identify significant optimization opportunities.

For companies operating in complex sectors such as food, IoT Intelligence offers a crucial competitive advantage.

In addition to optimizing the production process, IoT Intelligence has significant impacts on other key aspects of the company. For example, the ability to monitor real-time data related to raw materials and the supply chain enables:

  • More efficient stock management;
  • Better demand forecasting.

This leads to reduced storage costs and increased responsiveness to market fluctuations.

Furthermore, IoT data analysis can be extended to predictive maintenance of machinery. By using advanced algorithms, early signs of impending failures can be identified, and preventive maintenance interventions planned, thereby reducing unplanned downtime and further optimizing overall operational efficiency.

In conclusion, IoT Intelligence is a key element in the transformation of modern industry, enabling companies to achieve new levels of efficiency, quality, and competitiveness in the global market.

Author: Massimiliano Ruffolo