How the unassuming AI can transform the manufacturing ecosystem 

It helps to boost production and saves on costs while utilizing resources constructively. It can analyze data accurately and point out the errors. It's not just time-saving but is also precise to the minutest detail. That's artificial intelligence for you. Companies are using it in manufacturing and R&D as they move away from the manual workforce. This technological marvel is ushering in a new era of automation.

Artificial Intelligence (AI) is not a new term in the field of production and manufacturing. In fact, the idea has been floating around since the mid-1950s. The large-scale production units like the cement companies used it on a notable scale back then as capital expenditure. At that time, there weren’t many updates coming out as they do now on a daily basis. The companies which used the technology forgot about or didn’t show much concern over the passing years towards the installation of the upgrades. This didn’t have much effect then but in the long run, these companies are now facing a severe issue – they are lagging in the advancements that could have been brought in decades ago.

In a technologically fast-paced world, they are having to adhere to the traditional methods of manual surveillance and operation while some of their competitors are racing ahead. This reduces the company’s profits while also limiting its potential for utilizing its resources in a more constructive way.  

Artificial intelligence has seeped into almost every aspect of our daily lives. From the navigation systems that we use to travel to our offices, to the workforce in our offices which is heavily reliant and dependent on AI. Even inside our homes, it gives us the power to operate our appliances from anywhere.  

Today’s industries still count on experience rather than counting on analytics, the high-speed processing of data, and the on-point decision-making skills of artificial intelligence. For example, the manufacturing powerhouses have cut short their manual workforce to a downsized team of control-room operators, but these operators are still the ones who hand out instructions to the machines, monitor the signals, and have to operate through hundreds of buttons to give commands for the machines to follow. This can be seen as switching to AI but limiting its potential to a mere 10%.  Moreover, the operators sometimes have tasks that exceed their expertise and knowledge, forcing them to prioritize simple tasks over the tasks that can add actual value.   

According to McKinsey, companies using AI have witnessed cost savings and revenue growth. As much as 16% of those surveyed noticed a 10-19% decrease in costs, whereas 18% saw a 6-10% increase in overall revenue. 

AI offers companies the chance to move to the next level in manufacturing and production. It offers them a way to transform their warehouses and factories from being manually operated to a completely digitally run and managed organization. It Improves their chain of production and delivery, thus, creating new opportunities for them in the landscape of the client-consumer relationship. The adoption of AI will create a ripple effect that helps every sector that depends on the big-scale companies with heavy assets.  

The need for an AI revolution  

There is an urgent need to adopt artificial intelligence for the purpose of research and development in the field of manufacturing. The factories need to be highly advanced for them to cope with the increasing demand to provide fast-paced services to their consumers. The current ecosystem of manufacturing, production, and sales needs to be changed from manual to automatic, and a more technologically advanced and dependent ecosystem needs to be created. There are many driving forces behind these required changes in the factories. Some of which are: 

  • Identify and detect defects: The assembly lines at the factories are still heavily reliant on manual labor. Although some of the factories have installed cameras to identify any kind of fault in their production, it’s still not enough. They lack accuracy and proficiency in detecting errors and faults in production which can be extremely costly for the companies. False-positive cases are common, and workers have to manually go and check and investigate the fault in the product, which costs more time and reduces efficiency.  
  • Quality assurance: This is an important aspect to focus on when it comes to a certain segment of companies, for example, electronic firms. Electronic companies deal in products and items like chipsets and microchips. Any fault or error in these small coin-sized pieces can cause a lot of problems for the companies if the fault is not identified and corrected before they make their way out of the factories. For these faults to be identified efficiently, image processing algorithms are required. These image processing algorithms can validate if the product is fit for usage. This Image processing technique can be utilized by installing cameras at key points along the production floor and assembly line.  

A McKinsey report suggests that AI can improve forecasting accuracy in manufacturing by 10-20%, which translates into a 5% reduction in inventory costs and a 2-3% increase in revenues. 

  • Assembly line integration and optimization: Manufacturing involves a lot of data that is uploaded to the cloud instantly. Artificial intelligence is good at analyzing and sorting loads of data, providing the experts with compact, concise, and categorized data. Integration of the assembly line with an in-house built app can provide the experts at the factories with categorized information that they can monitor and work on when any issue surfaces. Among other useful tasks, the app can also be optimized to perform tasks, such as, notify if any worker is ill and still working, when any non-working person intrudes in a space where they are not authorized, and provide alternatives if any component breaks down in the middle of work.  
  • Generative design: Generative design is another field that AI can help in. Basically, how it works is that the designer or engineer uploads the requirements of a design that they need in the generative design algorithm. The generative design algorithm then works on the goals of the design, checking it through a series of solutions until the desired result is obtained. The algorithm uses machine learning against the data it has collected over time to obtain the desired output. 

The potential that artificial intelligence holds is unlimited. It is up to us to creatively adapt and integrate it within our systems. Artificial intelligence is an investment every company should make as it will greatly benefit them in the coming years. It’s cost-effective with its parts and components not being that expensive. It is a priority for any small-scale organization which wants to compete at a bigger scale. It helps industries to continuously find cost-saving methods, increase their manufacturing capacities, and to meet their rising supply chain demands. It turns out to be more effective when producing a small batch of customizable items in a short span of time.

Furthermore, it can increase the regulation and inspection of products, while enabling the employees to learn and adapt to the new technological advances at the same time. This will make them more skilled at operating and managing the in-house systems. The world is moving towards automation at an unprecedented and exponential pace and now, is the right time to get your business to work along and cash in on the wonders of AI.  

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