Manufacture-Automation and AI’s Role in Manufacturing Industry- B-AIM Pick Selects

October 30, 2020

AI and Automation, the terms that bring excitement and fear simultaneously on the face of any manufacturer today, post a pertinent question to the manufacturing Industry, Is the future exciting or scary, the answer to which will be discovered in coming years but will it be adventurous? For sure. From history, we have learnt that change is inevitable and it should be accepted ecstatically. Now to understand the ongoing changes we need to look at the basics behind AI and automation.

 

Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In computer science, AI research is defined as the study of "intelligent agents"; any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term AI is applied when a machine mimics cognitive functions that humans associate with other human minds, such as learning and problem-solving.

 

Automation fundamentally means the technology by which a process or procedure is performed without human assistance. Automation or automatic control is the use of various control systems for operating equipment, such as machinery, processes in factories, boilers and heat treating ovens, switching on telephone networks, steering and stabilization of ships, aircraft, and other applications and vehicles with minimal or reduced human intervention.

 

Role of AI and Automation in Manufacturing:

 

“Artificial intelligence isn’t a scary future it’s the amazing present”, said well-known Yale University professor, David Gelernter. Imaging an AI-powered machine with an IQ of 5000, as compared to average human IQ of 100. We do not have the vaguest idea what it would mean and how powerful it can be.

Artificial intelligence in manufacturing is no more the thing of the future, it is the thing of today. We are accustomed to using AI in our everyday life with Apple’s Siri and Amazon’s Echo. AI has made tremendous progress with the help of improved processing, algorithms, and a lot of data. With advanced Machine learning all this data can be analysed and critical insights can be gained, helping future projects keeping user behaviour in mind.

Next-gen AI-powered industries will work on lean inventories, reduced product glitches, cheap labour cost, shortened unplanned downtimes, and increased production speed. With AI in manufacturing, we are fundamentally talking about network connected factories, where design team, production line, and quality control are highly integrated into an intelligent machine, producing useful insights.

 

Automation and artificial intelligence help in doing the repetitive task with a high level of accuracy which was unimagined with human ability. It will help us in working in dangerous environments which were previously not imaginable due to higher chances of loss of human life. Future machines will have voice and image recognition that will be used to perform complex tasks which were earlier not possible without human intervention.

 

Use Case for AI and Automation in Manufacturing:

Manufacturing automation involves a complicated and detailed oriented approach to produce a material, hence following are the use cases for the industry.

AI and Automation are hot topics of manufacturing companies of future. With AI and automation powered technologies, the manufacturer can improve efficiency, fasten processes, and even optimize operations. It can reduce the production cost by 20% of which 70 % comes from improved resource productivity.

Transportation and logistics companies are in forefront of AI and Automation adoption. Companies in emerging nations are more enthusiastic about these benefits, while industrialized nations have a different view.

AI and automation will transform the value chain from end-to-end. Operations of the organization will be most heavily affected by this change. These factors augment existing levers that help in improving productivity.

 

Adoption of AI and manufacturing automation will significantly alter the composition of the workforce, e.g., all the quality control task that requires intensive human support will be heavily supported.

Currently, factories automate processes and machinery through a fixed approach. In future, AI and automation in manufacturing industry will together formulate an approach to make intelligent decisions in unexpected situations. In the current scenario, robots cannot select an item from a bin of unsorted parts, but in future AI supported robots will be able to do the same.

Conclusion:

Industrial companies should use the following approach to implement AI and automation in the present day scenario:

  1. Analyse the current scenario – Once the company identifies the pain points, it should evaluate itself against its competitors. Repository of topics and benchmarks will be required for the same.

  2. Identify the enablers – Once use cases are built, stakeholders should discuss in depth to prioritize the implementation, keeping financial and non-financial benefits in mind. Then the company should develop the final approach of implementing AI and automation in the industry

  3. Test and scale – The organization should test the MVP and then quickly deploy the solution over multiple iterations

AI and automation will become the most important lever in increasing productivity of next-generation manufacturing plants. An organisation needs to put infrastructure in place quickly raise their game to remain relevant in the coming years.

 

B-AIM

 

 

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