Smart Factories and Artifical Intelligence

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Smart Factories and Artificial Intelligence


A smart factory is a highly digitized and connected production facility that depends on smart manufacturing. Thought to be the so-called factory of the future and still in its infancy, the concept of the smart factory is considered an important outcome of Industry 4.0. 


The term describes a highly digitalized and connected environment where machinery and equipment are able to improve processes through automation and self-optimization. Therefore the smart factory is a concept for expressing the end goal of digitizing in manufacturing.


The three most important topics about smart factories are autonomous, visibility, and connectivity.



Essential Four Layers for the Smart Factory

These layers can help you understand where you are on the progress of becoming a smart factory and which steps you need to take to make progression to the next step.


The first layer is data availability. We are sure that most factories already have data for each process even if it is poor quality and inconsistent. If a factory does not have data, it is impossible to analyze and improve processes.


The second layer can be accessible data. The availability of data does not mean that we are able to quickly analyze and find inferences using the collected data. It is very important to keep the data in a structured and workable format. 


Generally, it is the quality of the data, the consistency of the data and the rate of missing data that determines the success of the artificial intelligence (AI) project. Also the preprocessing phase can often cover up to 70% of projects! For instance, a lot of effort is required to make sense of unstructured data (free text, image etc.).


Third layer is active data. Active data is different from available and accessible data. Active data means data that can perform proactive analysis using machine learning and AI to generate insights without much human supervision. The system can pin key issues and anomalies predict failures with high accuracy and inform relevant people with valuable insights at the right time.


The fourth layer is action-oriented data. We can think of this layer at the highest level that can be reached. At this stage, machine learning can generate actionable solutions to the issues that are identified in the early stages. The manufacturing machines and devices that are connected to this module or system can then execute some changes with no human contribution. Collecting data, defining issues, and creating solutions happen in sequence with little to no human input. 


Your state in the process of becoming a smart factory is directly proportional to the data-oriented approaches you follow.


The Relationship Between AI and Smart Factories


Term of AI is not new, but it is now finding applications in smart factories. In the last five years, there has been a tremendous increase in interest and investment about AI in manufacturing. There are dozens of reasons behind this, but we know that only AI can exist where the data is. With the development of devices such as sensors, the cost of data storage, the development of data analysis tools and concepts such as the internet of things, it was inevitable for factories to become smarter. So, these have collectively made it unavoidable for AI to be implemented in manufacturing.


The growing usage of big data technology, industrial IoT in manufacturing, extensive usage of robotics and computer vision technology in manufacturing, cross-industry partnerships and collaborations, and significant increase in venture capital investments will propel the growth of AI in the manufacturing market.