AI Trends Impacts Manufacturing

Artificial Intelligence is deemed to be the greatest technological innovation in the manufacturing industry. AI has provided machines the intelligence to "think and act" in a way that only humans could. It is mostly used by manufacturers for AI-powered analytics to increase productivity, product quality, cost-effectiveness, and employee safety by reducing unexpected downtime and designing better products.

When the pandemic first hit in 2020, lockdowns and remote working has been implemented. However, essential industries in healthcare, food production, logistics, and manufacturing are expected to respond with unprecedented speed and agility to cope with the COVID-19 pandemic. All of these elements have contributed to the sector's rapid digital transition.

The pressure of effective, precise, and fast data acquisition and interpretation have led manufacturers and other industrial sectors to jump on board with AI investment and adoption. Consequently, we're hearing from companies all around the world that their digital strategy plans revolve around advanced AI adoption for the past years. The following are some important trends and projections for how AI will affect and evolve the manufacturing industry this year.

An increasing skill gap addressed by AI

An acceleration of AI use assists in recruiting new talents for the industry. This is in response to the current battle of skill gap and an aging workforce. Industrial markets and applications will be responsible for some of the most significant AI advances and beyond as innovation accelerates. This will bring fresh tech talents to the sector, which wants to be at the forefront of this new wave of technological advancements.

On the manufacturing floor, AI is also altering the roles of workers. The creation of technology that frees employees from repetitive activities and allows them to focus on more analytical, high-value work is one way to help people feel more purposeful in their careers. The ability to re-skill individuals to operate in a high-tech workplace with AI is a benefit for investing more in technology.

As general AI disappears, full-stack, problem-specific AI thrives

AI was just a nice-to-have before the pandemic. An option that most manufacturers think or plan of. However, it was frequently trapped in the pilot phase because of uncertainty about the aim of adoption. Now, manufacturers are turning towards AI to solve real-world problems that can't be solved using traditional methods as a result of the pandemic. The focus will be on full-stack AI solutions that can quickly solve specific problems, including the hardware needed to collect data as well as the machine learning models that utilize the data. Customers will be able to use this instead of more generic AI technologies that need to be educated and customized before they can be useful.

Sensor-independent adaptive AI

Sensors to collect vibration data and AI models that learn and forecast from gathered data are usually part of full-stack AI systems. This is why the combination of AI and IoT-enabled sensors is a game-changer.

Manufacturers, on the other hand, are prone to accumulating a variety of sensor technologies over time in order to find the most effective solutions. It's exceedingly difficult for an AI model to produce accurate predictions based on real-time data from two different vibration sensors if it's been trained with data from one.

To solve this problem and make use of existing infrastructure, AI providers that rely on sensors are quickly attempting to become sensor-agnostic. A new approach for determining the difference in frequency response between different vibration sensors allows applying a machine health model to any type of sensor, including those made by other firms. This type of sensor-agnostic AI method is extremely rare, but it’s expected to become a key trend in the coming year.

Moving towards insurable AI

AI systems in reality, like people, make mistakes. This usually leads to huge losses. Clients are finding it even more difficult to assess which vendors can provide significant value as well as how to manage the risks as more startups and enterprises enter the AI sector. Good thing, some AI technologies are already being vetted and guaranteed by insurers, and offering insurance policies that cover the risks offers businesses the confidence they need to move forward with AI adoption.

As the AI they use becomes more capable of handling high-stakes tasks, it's a development that manufacturers should be aware of. Because they will be responsible for building the future manufacturing plant, manufacturers must be able to keep up with the AI trends that are evolving. Some of these trends will take longer to develop than others but expect them to all come to fruition at some point in the near future.

Other Applications

There are a number of other factors to consider while integrating AI. AI will improve both machine vision and robotic use patterns as robotics become more fully integrated into production automation. As a co-robotic partner, AI can also assist in moving the production robot out of the cage and into a co-robotic relationship with the living worker. Without AI and machine learning, such a move is inconceivable.

Finally, AI will help to achieve sustainability goals by optimizing the use of energy and natural resources. This will become an important component of AI's application in manufacturing as consumers grow keener on supporting sustainable products.

Final thoughts

The manufacturing industry is still in the early stages of this transition. So it's critical to stay current on the latest technology breakthroughs in a continuously evolving market. Even businesses that are doing well now are at risk of being left behind as the world around them evolves.

Combining AI and machine learning with other technologies, such as sensors, robots, and human inputs, would improve operations considerably and will most likely lead to new kinds of industry innovation and productivity. Don't let the fact that companies don't have the requisite expertise keep them from investing in commercial AI/ML solutions that can help them get started.

Performix is committed to industrial transformation and will work with businesses to develop a solution portfolio to fit every company's needs. Performix believes that today's manufacturing difficulties can be solved with a variety of artificial intelligence and machine learning solutions.