Companies today face a wide range of challenges: Increasing cost and competitive pressures, new regulations, and geopolitical uncertainties demand a completely new level of agility and adaptability from manufacturing companies. Factories must go smart as manual optimizations and isolated solutions are no longer sufficient to meet new and changing requirements.
The Smart Factory approach brings together cutting-edge technologies and methods. At the core: Seamless data integration – from market demand and production processes to supply chains and energy procurement. This creates the foundation for holistic digitalization and optimization, as well as for the implementation of AI technologies to enable agile and highly efficient production.
Using a Data Intelligence Platform, Gerolsteiner has succeeded in achieving real-time transparency across its entire production process. This enables the market leader to perform quick and flexible data analyses, identify the need for action early, and plan production processes based on data insights.
A leading German automotive manufacturer utilizes a solution developed by Device Insight to collect and analyze energy and machine data in real-time. This enables predictions and recommendations that make energy management smarter and more efficient. Peak loads can be minimized, and the integration and utilization of PV systems and battery storage significantly improved.
Based on a data platform that captures over 50 data points per machine in real time, automated analysis and visualization of OEE data and machine downtime have been achieved. Reports that previously had to be created manually are now available within minutes. This enables early identification of potential issues, accelerates decision-making, and improves the efficiency of operations management.
To identify parameters responsible for quality deviations, real-time production data is linked with operational processes and continuously analyzed for anomalies using ML models. This enables early detection of quality issues and significantly reduces rejects.
In the food & beverage industry, many manufacturers face similar challenges: complex production processes, heterogeneous system landscapes, and a lack of transparency across machine and process data. Three leading producers from the brewery, confectionery, and food processing sectors partnered with Device Insight to find a way to consolidate their production data from various sources and make it centrally available for analysis.
For a major brewery group, the focus was on harmonizing a fragmented IT/OT landscape. Using a horizontal Data Intelligence Platform based on a Data Lakehouse architecture and Microsoft Azure, production data from four sites was integrated to establish unified KPIs for brewing process reporting.
A confectionery manufacturer began with an IoT-based proof of concept to achieve full data transparency in production. Using OPC UA, machine and environmental data were integrated into Azure and visualized in CENTERSIGHT scale. For the first time, the company could clearly understand how batch characteristics, ambient temperature, and machine parameters influence product quality – the first step toward data-driven process optimization and reduced energy consumption.
A food producer with a complex production structure also relied on Device Insight to integrate data from various systems, including Simatic WinCC and ProLeit, into a centralized platform. The goal was to create full transparency across all machine states – from “running” to “maintenance required” – and to evaluate process data for efficiency improvements. Technologies such as Azure IoT Edge, IoT Hub, and ADX were used in the process.
The result: Across all three projects, a robust data foundation for the Smart Factory was established — from unified data acquisition and visualization to the groundwork for advanced analytics and AI-based optimization.
The core of a Data-Driven Factory is a central data platform that continuously processes data from across the entire production and beyond to monitor operations in real-time, detect issues early, and increase efficiency through data-driven insights. Smart Factories combine the strengths of IoT and AI in a holistic approach by integrating IoT-based data collection with AI analytics, thereby enhancing the AI readiness of companies..
Learn how leading companies leverage data to improve efficiency, quality, and sustainability – following a proven 5-step approach to the Smart Factory.
A successful transformation into a smart factory requires a structured and holistic approach. Device Insight has developed a 5-step approach that combines expertise in data architecture and data science. We guide you step by step, from identifying suitable use cases and conducting a proof of concept to rolling out the solution across your entire production.
Let’s talk about your challenges and craft the right solutions together.
