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Manufacturing Technology Insights | Thursday, June 17, 2021
By combining advanced digital and physical technologies, Industry 4.0 can potentially change the chemical industry as the cornerstone of many end-market industries. These technologies enable smart supply chains and factories, creating new business models through dual operations and growth.
FREMONT, CA: Chemical industry contributes to nearly every manufactured product. Industry 4.0 brings together some advanced digital and physical technologies to create a greater physical-to-digital-to-physical connection and potentially transform the chemical industry by promoting strategic growth and streamlining operations. Smart manufacturing combines IT such as IoT, Artificial Intelligence, and advanced OT analytics such as additives, advanced materials, and robotics. Below are some of the processes that can benefit chemical companies in many ways.
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Managing predictive assets
High asset intensity characterizes chemicals. Advanced IT/OT technologies can help businesses optimize maintenance costs and improve asset efficiency through predictive or digital maintenance. Advanced analytics tools can identify patterns for predicting and diagnosing possible breakdowns by continuously feeding sensor data on critical equipment such as turbines, compressors, and extruders. Innovative equipment can send messages to plant operators about any maintenance, potential breakdowns, and ordering and delivery schedules. This can allow manufacturers from scheduled repairs to predictive maintenance. Also, data from similar equipment installed at various sites can be collected, compared, and used for predictive maintenance, performance optimization, and new facility design.
See Also: Top Advanced Materials Solutions Companies ( ONEJOON, Epic Advanced Materials, American Elements )
Process management and monitoring
Industry 4.0 technologies, like real-time analytics and automated control actions, bring together the digital and physical realms—supporting predictions, alerts, and prescriptive responses. This, in turn, enables greater batch consistency and quality control.
Process variability ensues from various factors, from raw material quality to internal process variations. Similar to predictive asset management, process management requires collecting structured and unstructured data from multiple sources such as lab, alarms, and process equipment via sensors. Before they occur, analytics models help identify patterns and deviations in chemical processes, reducing production risks.
Management of energy
Energy costs add significantly to a chemical plant's cost of production. A typical plant demands multiple activities and interactions, and operators struggle to select optimal operating conditions. The chemical industry has bulk automation, and most plants monitor standard variables like temperature, flows, tank levels, and pressures for optimum plant conditions to be derived. Industry 4.0 technologies, includes soft or virtual software sensors, can add additional information to these data points, allowing control of non-standard process variables to improve energy efficiency. Soft sensors are inferential estimators based on neural networks that can process multiple collected variables through standard instrumentation, estimate new process & equipment parameters, and improve operator efficiency & plant efficiency. In addition, soft sensors can help when installing complex or expensive physical instrumentation.
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