Drive innovation, foster creativity, and unlock new revenue streams by leveraging emerging technologies and digital capabilities.
Stay ahead of the competition by embracing digital transformation, leveraging Industry 4.0 technologies, and continuously evolving to meet market demands.
Enhance security, compliance, and risk management practices to safeguard against cyber threats, regulatory challenges, and operational disruptions.
Acquire Utilize sensors, IoT devices, and advanced machinery to capture real-time data. Monitor equipment performance, track inventory levels, and analyze customer preferences. Digitize Transform raw information into a digital format that computers can process and analyze. Streamline the flow of data, enabling efficient access to critical information across the organization.
Normalize Standardize data formats, units of measurement, and structures to ensure consistency and uniformity. Harmonize disparate datasets to unlock valuable insights hidden within the noise. Analyze Employ advanced analytics techniques such as machine learning and predictive modeling. Extract actionable insights, identify emerging trends, and anticipate future challenges with unprecedented accuracy.
Normalize Standardize data formats, units of measurement, and structures to ensure consistency and uniformity. Harmonize disparate datasets to unlock valuable insights hidden within the noise. Analyze Employ advanced analytics techniques such as machine learning and predictive modeling. Extract actionable insights, identify emerging trends, and anticipate future challenges with unprecedented accuracy.
Industrial IoT refers to interconnected devices, machines, and/or processes that are linked by data communication systems to facilitate the exchange and the use of data between people and machines. Typically, these instruments have sensors that collect meaningful data points on a cloud or off-line database for tracking and identifying ways to improve the manufacturing process. Industrial IoT enables operational efficiency, control, and visibility into actionable key metrics.
Cloud Computing allows smart factories to store, process, and share data with greater flexibility at a lower cost than traditional on-premise alternatives. Interconnected devices and machines on the shop floor benefit from being able to quickly upload large amounts of data that can be distilled to provide feedback and make decisions near real-time.
Sensors attached to devices and machines help collect distinct data points at specific stages of the manufacturing process, providing instant visibility into various layers of the shop floor. For example, temperature sensors in a cleanroom can track and detect the climate in a lab and share that data through an IoT gateway. The data can then be used to self-correct with AI (Artificial Intelligence) or alert relevant team members for review.
This is likely the current status of most factories. Data is available, but not accessible. Sorting and analyzing data requires manual work and can be highly time-consuming, adding more inefficiencies to the production improvement process than intended or needed.
At this stage, data is presented in a more digestible form. Data is structurally organized and sorted properly in one location with additional systems that help visualize data and display dashboards. The factory is able to perform proactive analysis, although this may still require some time and effort.
Active data means data that can perform proactive analysis using machine learning and artificial intelligence to generate insights without much human supervision. The system can pin key issues and anomalies to predict failures with high accuracy and inform relevant people with valuable insights at the right time.
At this stage, machine learning can generate actionable solutions to the issues that are identified in the earlier stages. The manufacturing machines and devices that are connected to this module or system can then execute those changes with no human intervention. Collecting data, identifying issues, and generating solutions happen in sequence with little to no human input.
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