Impact of AI and ML in Manufacturing
Govciooutlook

Impact of AI and ML in Manufacturing

By Gov CIO Outlook | Thursday, March 14, 2019

Artificial intelligence and machine learning have created hype across industries, but there has been limited adoption when it comes to the manufacturing industry. As machine learning becomes more prominent, the numbers of tools and frameworks available to developers and data scientists have increased.

The ongoing maintenance of machinery and equipment in the production line represents a major cost, with a crucial impact on the bottom of any asset-reliant production operation. Predictive maintenance has become a necessary solution in recent days for manufacturers who have a great deal to gain from predicting a failure of a part, machine or system.

Due to today’s very short deadlines and an increase in product complexity, manufacturing companies find it increasingly difficult to maintain high standards of quality and to comply with quality regulations and standards.

Quality 4.0 uses of AI algorithms to report emerging production failures to manufacturing teams are likely to cause product quality problems. The defects can include deviations from recipes, subtle machine behavior abnormalities, and changes in raw materials. In addition, Quality 4.0 allows manufacturers to collect data on their products use and performance in the field. This information may be useful for product development teams in strategic and tactical engineering decisions.

Alongside improving current production processes and operational efficiency, ML can be leveraged to capture implicit and explicit process know-how, enabling manufacturers to use the system to bridge their talent gap and increase quality and productivity.

Artificial intelligence is a key element of the industry 4.0 revolution and is not limited to the use of floor boxes. AI algorithms are used to optimize production supply chains to help businesses anticipate market changes. AI algorithms formulate market demand estimates by seeking patterns that link location, socio-economic, and macroeconomic factors, weather patterns, political status, and consumer behavior. This gives the management an enormous advantage, from a response to a strategic approach.

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