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Industry 4.0 in Artificial Intelligence – AI Objectives

What is industry 4.0 in Artificial Intelligence?

Beginning from first industrial revolution by utilization of water and steam power to second industrial revolution of mass production through electricity. Third industrial transformation promoted the involvement of computers in industry and upcoming fourth industrial revolution regarded as Industry 4.0 in Artificial Intelligence. It can also summarized as

“the tendency of industry to move towards automated and connected production system that have ability to analyse its performance and to improve itself”

Industry 4.0 in Artificial Intelligence is the optimization of industry 3.0

In actual, smart technologies not referred as industry but industry 4.0 encompasses these areas as substantial components of industry. Industry 4.0 is the optimization of industry 3.0 i.e. computerization of manufacturing industry. During industry 3.0, computer as complete new technology introduced which digitized many manual tasks. When connections and communication between computers made and computers elevated to do tasks with least human intervention, this begin another era, Industry 4.0. Therefore, Industry 4.0 involves the processes and manufacturing technologies of cloud computing, internet of things (IOT), cognitive computing, cyber-physical systems and artificial intelligence (AI).  The main idea of industry 4.0 comprise of following domains

  • Smart Factory
  • Smart Manufacturing
  • Dark Factory
  • Industrial Internet of Things 

Smart factories and manufacturing drive the production of any industry faster through automation. A number of people still deny the capability of industry 4.0 to bolster the business. However, examples of the businesses who has marked success through employing smart manufacturing are still there such as Adidas and Amazon [1]. Dark factory or lights-out manufacturing considered when a raw material enters the system and a finished product produced without any human resource interference. A Japanese robot manufacturing company FANUC [2] has been using lights-out manufacturing from more than a decade. Industrial Internet of Things (IIOT) directly corresponds to the communication between computerized devices and decision-making based on inter correlations. IIOT enabled by using technologies that cloud computing, edge computing, cyber-physical systems, big data and artificial intelligence.

What is AI in Industry?

Artificial Intelligence, the domain of computer science in which machines prepared to behave like human that machine intelligence made analogous to human intelligence. Artificial Intelligence is broader term, which includes many sub-domains such as machine learning, speech processing, natural language processing etc. There are profuse applications of AI in industrial functions. AI as frontier research discipline focuses on the preparing algorithms that are makes correct predictions for given task while AI in industry propounds the usage of these algorithms in the industrial technologies that benefits the production, customer retails and revenue of company. Apparently, it seems that intelligent production systems fueled by AI techniques cause alienation of human beings from jobs which itself cause societal problems and unethical. However, business personals see it as next challenge to enhance the production process and expect huge opportunities in their way.

In order to accelerate AI in industry and explore more opportunities, a number of advances made such as the availability of data acquisition sensors in low prices, automatic data acquisition techniques, more powerful computing devices to perform complex operations expeditiously, high bandwidth connections and large cloud servers for data management and storage to petabytes of data.  To make best out of these technologies, business environment must be studied thoroughly which will lead to efficient usage for business innovation, insight discovery and improvement.

Industry 4.0 in Artificial Intelligence manufacture?

Industry 4.0 gets a huge buttress with the involvement of Big Data and AI. Data generated in factories can analysed by intelligent software solutions. Data analyzation includes the recognition of patterns and trends in experiences, which can make manufacturing process coherent and can save a lot of energy squandering. Those manufacturing plants, who are adapting the intelligent solutions save themselves from manual operator input for many of their operations.  To execute AI software solutions, sufficient computation power needed. Edge computing devices and cloud computing devices also employed to form a system. These computing devices interconnected through some network connection when there decision making independency. Hence, operating as an artificially intelligent internet of things system.

An IOT based operating system MindSphere by Siemens is one of the formidable manufacturing industry which is enabling the usage if Industrial AI in Industry 4.0 manufacture.

Benefits of AI and Industry 4.0?

Industry 4.0 in Artificial Intelligence benefits in a lot of aspects but more prominent of these are following aspects:

Undeviating Automation :

AI based solutions when deployed on peculiar robots, they tend to boost the mass-production mechanism. Robots have the capability of doing any task recurrently, developing production models, eliminating human errors, building automation solutions and automatically assuring the quality of products. All of this accomplished without human interference. Big data analysis helps in optimizing the productivity of robots, hence formulating an entire automated procedure of production.

24×7 Manufacturing

Unlike human labors, which require breaks in order to function efficiently, robots and intelligent machines inclined to work on production lines 24×7. They don’t get hungry or tired or require no holidays. It noticed that during the national holidays, a number of industries have to lessen their productions because of unavailability or less availability of labors. Robots also overcome this problem. Moreover, robots are faster as compared to human in tasks such as picking, placing, packing and assembly line departments. So that the turn around delay minimized and maximum products manufactured in relatively  less time.

Safe operational sites

At manufacturing sites, there are chances of manufacture errors such as electricity failure, short circuits etc. Human resources that are working in precarious environment has to compromise with safety issues. These scenarios are sometimes very dangerous that they can lead to loss of precious human lives. Usage of robots on the other hand in similar operational sites reduce the loss of human lives.

Unprecedented jobs for human

When AI takes the role of unskilled labour, it increases the opportunities for human being to do innovative tasks. Hence, the invincible human intelligence can be utilized to bring novelty and to find the solutions of complex problems.

Example of AI in Industry 4.0?

Industry 4.0 in Artificial Intelligence can boost the manufacturing industry in such a way that has not yet been anticipated. According to the statistics, presented in [4] AI will uplift the production by 40% or more by 2035. The effect of AI on global industry is shown in following chart.

  • Computer vision techniques are readily being employed for the detection of defected products in production lines. Such algorithms can identify the minor defects that  can be neglected by a human eye.  A simple case is depicted in following figure.
  • Machine learning algorithms that operates on visual data helps in carrying out counting, classifying and recognition.
  • Stock transaction can be created by using the camera input just from the raw material placed in shelf.
  • Other than computer vision, data analysis that is carried out on structured or non structured data is helpful in order to predict the future trends of product sales, customer requirements and ongoing trends.
  • In addition to above mentioned examples, service robots can replace the role of safety guards by comprehending the visual and audio input. For example, sometimes sound of particular manufacturing component changes when it is undergoing some fault. By understanding the sound possible error can be recognized and can be made correct by automatic means.

[3] Schatsky, David; Muraskin, Craig;
Gurumurthy, Ragu. “Cognitive technologies: The real opportunities for
business”. Deloitte Review.

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