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How Artificial Intelligence Is Changing the Industry

What is Industry 4.0?

Industry 4.0

Graphic via Spectral Engines 

1) Increase of productivity through a higher level of automation that reduces production time, enables better asset utilization and inventory management.

2) Increase flexibility manufacturing through machines and robots that can execute the production steps for many products.

3) Increased quality of products via sensors and actuators that monitor the current production in real-time and quickly intervene in case of errors.

4) Increased speed from the first product or factory idea to the finished product through consistent data and AI opportunities.

What is smart maintenance?

Material sensing in Industry 4.0

Graphic via Spectral Engines 

Industry 4.0 uses Artificial Intelligence (AI) algorithms to notify manufacturing teams of emerging production faults that are likely to cause product quality issues. These faults can include deviations from recipes, abnormalities in machine behavior, changes in the raw materials, and the ability to recognize product defects. AI algorithms perform manufacturing, quality control checks, shorten design time and reduce material waste while improving production and performing predictive maintenance. By tending to production faults early, manufacturing teams can maintain high-quality levels.

Industry 4.0 also enables manufacturers to collect data about their products’ uses and performance in the field. The field data insights can provide product teams with compelling qualitative information while making strategic and tactical decisions.

Ever-changing market

AI is a core element of the Industry 4.0 revolution and is not limited to just the use-cases on the production floor. Manufacturers can use AI algorithms to anticipate needs, optimize supply chains, and predict market changes.

The new-to-market insights available through AI provide management teams a competitive advantage while positioning them to move from a reactive mindset to a strategic, planful business approach. The AI algorithms formulate market demand estimations by looking at patterns. Patterns of locations, weather, political status, consumer behavior, and more are all part of the algorithms.

Changing the fabrication of manufacturing

Within this decade, machine learning technology will change how companies manufacture products. Machine learnings coupled with cloud computing’s ability will become the most extensive form of AI in manufacturing. The possibilities are vast with the ability to collect, store and handle big data. AI applications perform real-time speech translation, robotics, and facial analysis, and these capabilities are fueling its growth in the manufacturing market.

AI constitutes various technologies that play a vital role in developing its ecosystem. Enormous market opportunities have opened as AI enables machines to perform activities like those performed by human beings.

According to the market reports, AI in manufacturing is expected to grow approximately 57.2% between 2020 and 2026. The AI in manufacturing by offering (hardware, software, and services), technology (Machine Learning, Computer Vision, Context-Aware Computing and NLP). With these changes, AI in the manufacturing market is expected to reach $16.7 billion by 2026.

Global AI in Manufacturing Market Trends


I hope this article provides you with actionable information. If you are ready to reimagine how artificial intelligence can support your team, we’d like the opportunity to help. Please reach out to our team at any time.

Tim Goebel is the Data & Artificial Intelligence Principal Consultant at SafeNet Consulting. Tim is an IT engineering leader with a track record of success bringing projects from conception through completion to enhance efficacy, control costs, and propel business growth. In early 2021 Tim achieved his Microsoft Certified: Azure AI Fundamentals certificate that verifies he has demonstrated foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.

Tim also has certifications and critical technical knowledge on Visual Studio C#, Scikit learn, Keras, Tensorflow, Python, NLTK, Tokenizing, Panda, Docker, MathWorks, labview, Open CV, RNN, CNN and more to meet business needs.