Know How Industrial AI Is Revolutionizing Manufacturing

In no other sector does Artificial Intelligence have more of an impact than manufacturing, and the revolution is just beginning.

 

Undoubtedly that the manufacturing industry is leading the way in the application of artificial intelligence technology. From significant cuts in unplanned downtime to better-designed products, manufacturers are applying AI-powered analytics to data to improve efficiency, product quality, and employees' safety.

 

Manufacturing Industry And AI

Constant servicing of production line machines and facilities is a considerable manufacturing cost, with a critical influence on the bottom line of any asset-reliant production process. Besides, surveys indicate that unplanned downtime costs producers an estimated $50 billion annually and that the cause of 42 percent of this unplanned downtime is asset loss.

For this cause, predictive maintenance has become a must-have solution for producers who have a great deal to benefit by anticipating the next malfunction of a part, machine, or device. 

 

To devise predictions about asset malfunction, predictive maintenance uses sophisticated AI algorithms in machine learning and artificial neural networks.

This allows for a massive reduction in expensive unplanned downtime, as well as an expansion of the Residual Usable Life (RUL) of manufacturing machinery and facilities. 

 

In situations where maintenance is unavoidable, technicians can be briefed in advance on which parts need inspection and which equipment and procedures to be used, resulting in very focused fixes that are scheduled in advance.

 

What are the AI Trends you should look out for if your business is in the manufacturing sector?

 

The Rise Of AI - Quality 4.0

Owing to today's extremely short time-to-market deadlines and the growing complexity of goods, production firms find it increasingly difficult to retain high-quality levels and comply with quality legislation and standards.

Quality 4.0 includes the use of AI algorithms to alert manufacturing teams of evolving output defects that are likely to cause product quality problems. Faults can include differences from formulas, minor anomalies in system behavior, shifts in raw materials, and more. A high degree of consistency can be preserved by tending to these problems early on. 

 

Consequently, Quality 4.0 helps businesses gather information about their products' use and performance in the field. This knowledge can be powerful for product development teams to make both technical and tactical innovation choices.

 

Human-robot Collaboration

The International Federation of Robotics estimates that more than 1.3 million manufacturing robots will be active in factories worldwide by the end of 2018. In principle, workers will be qualified for more specialized roles in construction, repair, and programming as more and more jobs are taken over by robotics.

 

Human-robot cooperation will have to be successful and secure in this transitional period as more manufacturing robots join the factory floor alongside human staff. Advances in AI would be central to this development, allowing robotics to carry out more cognitive tasks and make autonomous decisions based on real-time environmental data, and further optimize processes.

 

Making Better Products With Generative Design

Artificial intelligence also affects the way we design things. One approach is to enter a comprehensive brief specified by designers and engineers as input to an AI algorithm (in this case, referred to as "generative design software"). The brief can contain data detailing limits and different criteria, such as content types, available manufacturing processes, budget limitations, and time constraints.

 

The suggested approaches will then be evaluated using machine learning to gain further insight into which designs perform well. The method can be repeated until an optimum design solution is achieved.

 

One of the key benefits of this method is that the AI algorithm is fully impartial – it doesn't default to what a human designer would assume to be a "logical" starting point. No conclusions are taken at face value and everything is tested according to real performance against a wide variety of development scenarios and conditions.

 

Adapting To An Ever-changing Market

Artificial intelligence is a key element of the Industry 4.0 transition that is not limited to using cases on the factory floor. AI algorithms may also be used to improve supply chain manufacturing, helping businesses predict industry shifts. This offers management a big benefit, going from a reactionary/response approach to a strategic one.

 

AI algorithms devise market demand forecasts by searching for trends connecting location, socio- conomic and macroeconomic influences, weather patterns, political status, consumer behavior, and more. 

This knowledge is invaluable to suppliers as it helps them to optimize staffing, quality management, energy usage, and the procurement of raw materials.

 

AI Will Continue To Transform The Manufacturing Industry

The automotive field is a perfect match for artificial intelligence applications. Even though the Revolution of Industry 4.0 is only in its early stages, we are still seeing major benefits from AI. From the design process and the manufacturing floor through the supply chain and management, AI is destined to transform forever the way we produce goods and process materials.

 

NDIM offers a programme on MDP on artificial intelligence in the manufacturing sector that will help you understand how new technologies are being extensively used in manufacturing to perform quality control, shorten design time, reduce materials waste, improve production reuse, perform predictive maintenance, and more. Businesses agree, the Internet of Things, when combined with AI, provides an increasingly sophisticated system of managing machines, gathering data, scheduling maintenance, and performing hitherto routine tasks, so that they can perform at par with their counterparts across the world.

 

This programme will help participants understand new technologies such as Artificial Intelligence, Augmented & Virtual Reality, the Internet of Things (IoT), and Big Data. It also showcases how various Manufacturing and Production companies are using AI, AR, VR, and IoT to their advantage. Apart from this, the programme guides participants on the benefits and limitations of these technologies to understand where best to use and avoid these.