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AI in Production: a Game Changer in the Manufacturing Market

 “AI will perform manufacturing, quality control, shorten design time, reduce materials waste, improve production reuse, perform predictive maintenance and more,” quotes Andrew Ng, the creator of the deep-learning Google Brain project. Artificial intelligence is a technology creating a path into machine learning technologies, evolving manufacturing processes and pattern recognition software primarily, and holds the potential to transform industries over the future period.

Known for the advancement of Industrial 4.0 over the years and in future, AI is set to obliterate human jobs by aiding larger machine interactions nearer to the labour interactions. Adoption of AI in manufacturing has led to greater progress in the areas of automation, production capacity, the safety of the environment, low operating costs and many more.

Companies Making Smart Adoption of AI in Manufacturing Areas

Quality assurance – AI majorly focuses on minute details and errors much precisely than the human workforce. The defects and faults in the production are immediately flagged and coordinated when integrated with a cloud-based data processing framework. Hence, AI plays is of utmost importance for factories’ manufacturing products like circuit boards & microchips, utilizing ‘machine vision’ and high-resolution cameras.

Maintenance- Machine learning is a vital component of AI and Azure Machine Learning empowers AI to build, test and attain predictive analytics solutions on your data. For instance, smart factories operated by LG are adopting Azure Machine Learning to identify and anticipate defects in the machinery to prevent any faulty incidents. This leads to predictive maintenance, which can lessen the unexpected delays.

Efficient and more reliable design- Artificial intelligence is also altering the method of designing products. Wherein one technique is called ‘generative design software’ which incorporates data describing restrictions and different parameters, namely, suitable production methods, material types, budget limitations and time constraints. ‘Airbus’ is one of the companies using this tool to obtain thousands of component designs in a short time. AI giant Autodesk shrinks the time taken for manufacturers to examine new ideas.

Reduced environmental impact – Adoption of AI reduces the environmental impact in production and ensures safety in the risky zones of manufacturing units. Siemens outfits its gas turbines with hundreds of sensors, enabled with an AI-based data processing system, which adjusts the fuel valves to reduce the emissions as much as possible.

Integration – Azure’s Cognitive Service is a cloud-based machine learning system which streamlines communications for manufacturers between their branches. Data received in one production line can be coordinated or shared with other branches, in order to automate material provision, maintenance and other manual undertakings. 

Harnessing useful data – Hitachi plays close attention towards the productivity and output of its units implementing AI methods. The previously unused data is collected and processed by AI, by opening insights which usually consumed time to analyze in the past years.

Post-production support –  Kone, an elevator and escalator manufacturer company is utilizing AI-enabled ‘24/7 Connected Services’ to monitor the usage of its products as well as update clients about the use. This aids them in detecting defects in the process but also shows clients in what ways their products are being used in practice.

Automation is influencing manufacturing industries to achieve great efficacy and productivity with much speed as compared to the human workforce. Adoption of robotics has minimized the risk to be borne by the human workforce in the production areas. In the coming years, robotics will be projected to have features like voice and image recognition to simplify complex human tasks. The IoT functionality is anticipated to empower production process in greater lengths due to its abilities to analyze the production, tracking and aggregating control rooms projecting lucrative steps in the coming years. Virtual Reality encourages adopting the latest tools to support augmented and virtual reality. It aids connectivity among remotely located people to function on tasks jointly where troubleshooting is necessary. Features like Simulation and product-creation hold high potential to lessen the manufacturing time drastically.

AI will impact manufacturing industries in numerous ways, which are yet not imaginable. Moreover, we can focus on a few noteworthy names which are adopting AI in the most optimum way in their businesses, yielding larger profits and efficacy in production. Some of the key names are Amazon Web Services, Siemens, IBM, Google AI and Microsoft.

IBM Cloud, Amazon Machine Learning, TensorFlow and DeepMind by Google, Google AutoML Vision, Cortana voice apps, Skype, bot payments, Azure Bot Service, Bing customized search by Microsoft are some of the AI tool examples implementing advanced algorithms to strengthen the interactions between machines and humans and innovating production. 

To conclude, from a future perspective, AI is projected to have a profound impact on the manufacturing industry as it leverages automation and adoption of advanced robotics. AI offers customers, manufacturers and the supply chain, a host of advanced benefits which were difficult to achieve before. Industries will be in the position to provide greater benefits to consumers and fulfil their demands in real-time; also, the supply chain will be incredibly efficient. Thus, artificial intelligence (AI) by its definition, seems to be an effective solution and promises to redefine the manufacturing industry.

Inkwood Research

Author: Inkwood Research

We at Inkwood research provide you with not just consulting services but also with syndicated and customized research reports which help advance your business further.
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