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The shift to artificial intelligence in manufacturing

Manufacturing has seen many new innovations over the years, but few of those have had as much impact as artificial intelligence. Nearly every process is going to change as AI, machine learning, and the Internet of Things (IoT) are fully implemented. But is the manufacturing ready for these changes? Read on to learn more about the shift to artificial intelligence in manufacturing.The shift to artificial intelligence in manufacturing_IQS

Artificial intelligence

Robots and other automated machinery are commonplace manufacturing components around the world. Automation has increased productivity; created safer work environments; and made products better, cheaper, and more profitable. But all of those improvements could pale in comparison to what artificial intelligence and IoT will bring to the manufacturing world.

The current iteration of automated cognitive processing involves data collection. For example, IoT sensors monitor the temperature or the pressure of a particular function and then report the data to a worker who evaluates it and then determines the appropriate course of action.

However, that relatively simple process is poised to change dramatically. Machine learning and artificial intelligence will soon be applied to the raw data produced by IoT sensors, and automated algorithms will be in charge of determining what the appropriate course of action is.

With sensors sending signals to computers and cloud-based servers running specialized artificial intelligence software backed by machine learning algorithms, a robot designed to make a precision motion could alert personnel when something goes wrong. In fact, if properly designed and programmed, the system could make the necessary adjustments on its own. In effect, it would be a self-sustaining, self-correcting, automated manufacturing robot.

While that may sound like science fiction to some, these systems are rapidly becoming reality. Manufacturers must prepare for the inclusion of IoT and AI systems into their operations or risk losing ground to the competition. Now more than ever, process documentation, quality management, personnel training, and compliance testing are vital to the success of every manufacturer on the planet.

To prepare for this shift toward data driven manufacturing, companies will have to employ sophisticated enterprise quality management systems (EQMS) that increase data visibility, ensure compliance with standards, and reduce systematic risks.

Data is the new currency

The data generated by sensors in an IoT environment is enough to overwhelm conventional systems, but with cloud computing and AI, the data can quickly be analyzed, processed, and transformed into actionable information useful to decision makers. The key to making a system like this work is cognitive technology.

As machine learning algorithms collect and process more data, the resulting information becomes more accurate and useful. Manufacturers will have to allocate resources on not only IoT sensors, but on cognitive processing systems, cloud-based computational power, and decision-making personnel.

When all is said and done, manufacturers operating in an AI-enhanced environment may find themselves spending more resources on data management than on the actual manufacturing process. Essentially changing the focus of operations from producing goods to monitoring the automated machines and artificial cognitive processes that produce the goods.

In such a brave new world, artificial intelligence will handle how products are manufactured. Cognitive machines will be tasked with maintaining quality and compliance standards. Personnel will adopt new roles revolving around system maintenance.

The disruption to manufacturing caused by widespread implementation of these cognitive manufacturing machines will likely be difficult and painful, but the benefits are too great to ignore. Manufacturers need to prepare and be ready for artificial intelligence. It is on its way, ready or not.IoT and the Connected Value Chain_IQS

 

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