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Event-Driven Manufacturing Relies On Real Time

The critical component of this process is the access, aggregation and analysis of data emanating from the production process.

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As discrete manufacturing moves into an event-driven, real-time economy, collaborative production environments are required to move information across all tiers of the enterprise. Business throughout the enterprise will be conducted in close concert with factory operations, as the production facility becomes the centerpiece in this shift to event-driven integration. In order to run event-driven manufacturing, it is essential to access events occurring in real time.

Information that originates on the factory floor as a part of the production process will drive Real-time Performance Management (RPM) applications. Today, manufacturing intelligence and visibility represents collected data that is aggregated, compiled and analyzed to drive RPM, asset management and continuous process improvement. In an event-driven manufacturing environment, the more prevalent use of data is the real-time snapshot of the production process. This snapshot provides information critical to highly optimized systems that require more dynamic and relevant information. Supply chain execution, product lifecycle management, continuous process improvement, operations asset management, production execution systems and quality assurance are all functions within manufacturing that directly benefit from receiving timely information. Enterprise-level systems, such as supply chain management, enterprise resource planning and customer relationship management, can be driven with the real-time events occurring at the assembly line, machine and device levels.

Intelligence at the device

It is now possible to place a high degree of intelligence at the equipment level, enabling processing for complex logic, signal conditioning and analysis directly at the device. Based on the degree of embedded intelligence at the device level, processed information—rather than just raw point data—can be provided to the business systems. Meaningful information can be moved to the production management and enterprise tiers across the interoperable environment of the Internet. Processed data now arrives with content, context and contact information that can interact with higher-level applications and serve to optimize that part of the process.

Shop-floor equipment can be linked peer-to-peer and upward to machine state and condition monitoring applications, as well as to enterprise asset management applications. RPM as a concept translates to the availability of real-time metrics that provide operational visibility to enable a fact-based decision process. However, the critical component of this process is the access, aggregation and analysis of data emanating from the production process, which results in the actual information that implements RPM. This means that data is collected from programmable logic controllers, computer numerical controllers, automated assembly equipment, quality assurance and manual entry points to be used across a broad range of production management and enterprise level systems. This would include custom databases, enterprise resource planning (ERP) modules, plant historians, Web content for visibility, real-time enterprise metrics, asset management systems, manufacturing portals and overall continuous process improvement.

A cross section of providers in this space use Web-based technologies and production management applications to access device-level data, along with data collection, connection and collaboration methods, manufacturing process planning and execution, and simulation and data collection methods.

Manufacturers need to be aware that one of the basic tenets of RPM is to provide visibility and usable metrics that represent a real-time snapshot of the production processes. RPM depends upon the access and collection of data at the point of the event.

A collaborative manufacturing environment requires the use of factory floor data as the source of information.      

Dick Slansky,  

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