More Data Value Creation: Increasing Productivity in Manufacturing
By networking machines and equipment, large amounts of data are generated that can improve efficiency and quality in production. However, many industrial companies have limited insight into their value creation processes. Sight Machine on Microsoft Azure provides a holistic view of all manufacturing processes, allowing companies to visualize and analyze their operational data.
The challenge: Industrial companies have limited insight into their value creation processes
The digitalization of industrial production is progressing, with numerous machines and equipment now connected through the Industrial Internet of Things (IoT). More modern machines generate extensive status data ex works, and existing machines can very easily be retrofitted with sensors and an IoT connection. In addition, there are numerous process data from programmable logic controllers (PLCs) and industrial PCs, as well as data from ERP and MES solutions.
But it is not enough to simply generate data. Many organizations struggle to manage these volumes of data. They lack real insights into production throughout the entire company and transparency in the value chain. The data is often unstructured, its integration is often still done manually, and resources for analysis on the shopfloor are limited. Companies therefore need an integrated solution that converts data from different sources into a standardized data foundation.
The solution: Holistic insight into all manufacturing processes
Sight Machine on Microsoft Azure continuously analyzes all plant data from across the company. The platform is hardware agnostic and can integrate data from machine controllers, sensors, ERP and MES applications, and other industrial technologies. It leverages the IoT capabilities of Azure, utilizing Azure IoT Hub and Azure Stream Analytics for real-time data processing and storage in Azure Blob Storage. Sight Machine then consolidates this data.
With the platform, industrial companies are able to integrate machine, quality and downtime data and convert it into a structured database. This provides them with a common data foundation for analysis. It allows visualizing, analyzing and exchanging all operational data with other applications.
The new concept of the "Operational Digital Twin"
Usually, a digital twin is the virtual and dynamic representation of assets, products, processes or systems. It models the properties and condition of its real-world counterpart using various data sources and is updated on a regular basis. A company can thus display the current working status of individual machines or processes.
Sight Machine’s “Operational Digital Twin” extends the concept of the digital twin by linking real-time Industrial IoT data with other information on Azure. Machine learning (an application of artificial intelligence) and advanced data modeling techniques give the company a digital twin of its entire manufacturing operation. This creates a holistic view of a production system with all the dependencies between the individual assets and processes.
Sight Machine applications
Overall, this technology offers numerous opportunities to continuously improve manufacturing. Some examples include using Sight Machine on Microsoft Azure to detect deviations in manufacturing quality, identify malfunctions early and reduce downtime, determine and reduce energy consumption, or synchronize the cycle times of multiple machines.
Another option is to test hypotheses: For example, it is possible that production quality decreases with higher machine speed. The analysis functions make it possible to determine a statistical correlation between machine speed and scrap rate. Through comprehensive evaluation, the platform provides insight into the entire value chain, including all upstream and downstream supply chain processes.
The result: Continuous improvement of manufacturing
Sight Machine on Microsoft Azure provides insights into the entire value chain with a comprehensive analysis of all data sources Greater visibility leads to more efficient problem resolution and an increase in overall plant effectiveness. In this way, the platform enables continuous improvement in manufacturing. System-wide analysis with the platform results in productivity gains of up to 10 percent in some cases.
Click here to find the app in the Microsoft Azure Marketplace: Sight Machine on Azure
