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How Intelligent Automation is Transforming Manufacturing Processes

The explosive growth of the cloud has made on-demand processing more accessible, more efficient and relatively lower-cost. All of these things make adoption of intelligent automation a no-brainer for manufacturers.

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The explosive growth of the cloud has made on-demand processing more accessible, more efficient and relatively lower-cost. All of these things make adoption of intelligent automation a no-brainer for manufacturers.

Many manufacturing companies utilize a robust assortment of control systems, MRP solutions, and warehouse management systems. The amount of data collected by these systems makes manufacturers well-poised to take advantage of the recent advances in intelligent automation, which can leverage the power of the cloud to solve business problems and increase efficiency.

Intelligent Automation (IA) is the umbrella under which artificial intelligence (including machine learning and deep learning technologies) and robotic process automation (including workflows) fall. Machine learning and deep learning can be used to solve operational business problems, such as predictive analytics and predictive maintenance. Manufacturers already incorporate workflow design into their business operations, with many having workflows that are partially automated and save time for end-users. Robotic process automation’s workflow optimization and cost savings can be augmented by leveraging AI’s ability to expand the scope of what data can be interpreted and evaluated as part of an automated process, such as free-form text.

By using data they are already recording, manufacturers can use predictive analytics to solve new problems and facilitate product engineering. Machine learning models are being used to predict how to fabricate specific physical materials and minimize anomalies in complex chemical reactions. Manufacturers are saving time that would otherwise be spent doing calculations, and are noticing anomalies before a product enters Quality Assurance.

Predictive maintenance solutions allow machines to report back when they will require servicing, thus reducing unplanned downtime and kicking off workflows to plan service.

Workflow automation has been a growing aspect of intelligent automation, with the incorporation of deep learning. Natural language processing makes it possible to turn free-form text into business logic, such as with sales order instructions that must be routed to specific departments. By handing over more tasks that require interpretation to artificial intelligence, employees’ time is freed up to focus on higher value tasks and more complex challenges.

Another area where intelligent automation is improving the experience for employees and customers alike is through chat bots and custom smart assistants. By connecting them to existing workflows and knowledge bases, they can help process orders, onboard employees and function as a specialized resource both in the operations room and on the factory floor.

The explosive growth of the cloud has made on-demand processing more accessible, more efficient and relatively lower-cost. All of these things make adoption of intelligent automation a no-brainer for manufacturers.

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