Top 10 Use Cases of AI in Manufacturing

Top 10 Cases of AI in Manufacturing

Top 10 Use Cases of AI in Manufacturing

As per profound research published in Annual Manufacturing Report 2018, 92% of senior executives in manufacturing acknowledge the calibre of “AI in Manufacturing”. It would not only enhance their productivity but turn their workforce smarter.

The significant gap between amounts of researches made in regards to AI innovations in manufacturing to minuscule implementation. This very fact reflects the lack of awareness and opportunity AI has to offer.

How AI in Manufacturing can be beneficial?

  1. Predictive Maintenance
  2. Predicting Possible failure modes
  3. Quality Checks
  4. Environmental Impact
  5. Digital Replica
  6. Generative Design
  7. Customer Service
  8. Robotics
  9. Price Forecasts
  10. Leveraging Data

Prominent Cases for AI in Manufacturin

AI has been game-changer on multiple fronts. The very calibre to transform manufacturing processes through AI-backed tools has been very part of growth. Let’s dwell deeper into some prominent aspects where Artificial Intelligence has been driving success to manufacturers.

1) Predictive Maintenance

Predictive Maintenance

Every mechanical instrument or one that is operating consistently requires maintenance at a certain point of time. Predicting or performing preventive maintenance can be tiring as well as costly.

Manufacturing companies can prevent unplanned machine downtime, through predictive maintenance. A perfectly webbed ecosystem of advanced sensors with manufacturing machinery optimises the overall manufacturing process.

2) Predicting Possible Failure Modes

Predicting Possible Failure Modes

At times, our predicaments around a certain object might overshadow possible failures. Failures can be in multiple forms and far from the visual imaginations. At times, an imperfect object might perform perfectly, whereas a perfect object can fail disastrously.

This ensures that perception to a certain set of objects and their performance won’t lead to operational failures. Artificial Intelligence backed eminent data can analyse possible failures. Companies can seamlessly figure out, areas that need to focus upon.

3) Quality Checks

Quality Checks

Quality Control has been one of the most crucial aspects which can drive or drop companies growth. At times flaws are so minute to be detected by the expert human eye. Machine learning backed camera vision can “Segregate” products with certain imperfections. Further, the inspection could be undertaken by a human expert.

At times, the complete process can be fully automated, mitigating even the slightest human interferences. Adopting AI-backed manufacturing process would ascertain top quality commitments

4) Environmental Impact

Environmental Impact

Anything we manufacture, assemble or produce leaves a certain set of environmental footprint. All the natural resources that are ravaged to produce the final product, at the cost of harming the environment. Cutting on plastic consumptions and e-waste has just turned more of a necessity than just an option.

AI can significantly reduce waste while manufacturing of certain products. To a certain extent adopting AI in manufacturing can even reverse the environmental damages done over the years. Developing and optimising more eco-friendly material with higher sustainable services.

5) Digital Replica

Digital Replica

A digital replica can be also termed as a virtual representation associated with a product, service or factory. Through sensors and data collection devices, one can create a digital replica to the model. Integrating and connecting data from all sensors and manufacturing instrument.

Real-time analysis based on physical items. The complete framework of components is connected with a cloud-based platform. The technology could help brands expand over multiple aspects.

6) Generative Design

Generative Design

Designing your objects is no longer a hassle. Adopting a generative design will offer multiple outputs adhering to certain criteria’s and parameters. Infusing your requirements such material, cost constraints & manufacturing process will fetch you with the liberty to choose from multiple alternatives.

The outputs generated through machines are based on analytics of Machine Learning. The design that would most efficiently comply with parameters or the one that fails. The algorithm finds multiple ways in which a product could be designed and produced. It also opens prospects for multi-functionary design alternatives.

7) Customer Service

Customer Service

Customer Service is one such aspect, often left-out in the manufacturing sector. however, it’s of the grave mistake business leaders commit and lose significant business. AI-backed solutions on the other hand imperative in predicting consumer expectations.

These solutions can right-away prompt critical issues leading to a better-personalised experience for consumers. Incorporating AI in manufacturing would strengthen your consumer engagement leading to better growth opportunities.

8) Robotics

Robotics

We shouldn’t be surprised by the fact, soon manpower in industries would be overtaken by robots. However conventional robots need to be programmed for the functions they need to perform. They are unified with the path of action they need to follow.

On the other hand, AI-powered robots no longer need to be programmed for tasks performance. These robots can seamlessly interpret CAD models, removing all sort of human interaction.

9) Price Forecasts

Price Forecasts

Manufacturing requires subsequent raw materials and supplies. Price fluctuations over this resources can often disrupt your balance sheets and leave a dent upon profits. Such an extensive instability in resources prices could leave your end product price commitments shaky.

To mitigate this issue, a better data-oriented AI algorithm would turn to be greatly helpful. Business leaders would be notified of the very accurate time to stock-up on their resources. Dynamic algorithms with multifaceted data could help in predicting prices with subsequent profit margins.

10) Leveraging Data

Leveraging Data

Although data usability at initials could be quite general. Manufacturers usually collect an immense amount of data while processing, operations and manufacturing. This Big data, when incorporated into advanced analytics based algorithm, would fortify eminent insights for business growth.

Including AI in manufacturing significantly impact parameters such as Risk Management, Supply Chain Management Product Quality, Predictions in Sales volume & Minimising on recall issues. This AI-based application can open up newer and better prospects for business growth.

Final Words: The Future of Manufacturing

Artificial Intelligence is particularly a revolutionising technology irrespective to any industry. Consistent development and drop in the cost of operation have made it more accessible to a wide range of companies. On the other hand, the manufacturing sector has always been looking for a system upgrade which is efficient and cheaper.

AI in Manufacturing would fortify industry success with efficient and data-driven decisions. Business leaders can minimise their operational costs by optimising manufacturing processes leading to better service to their customers.

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