Transforming a business or enterprise digitally is not child’s play. It takes a lot of effort to achieve a high level of intelligence. AI is extensively used in the manufacturing sector, facilitating industrial automation.
AI-driven machines are laying an easier path to the future by offering advanced digital transformation solutions, enhancing production efficiencies, and bringing machine interaction closer to human interaction.
Artificial intelligence is a combination of data fetched from machines, sensors, and workers and then the same gets applied to the algorithms that are designed to optimize operations. Standard AI contains images, speech, video recognition, autonomous objects, natural language processing, predictive maintenance, and forecasts.
Artificial Intelligence plays a game-changer role With different components of digital transformation, AI integration may be overwhelming. Manufacturers are concerned about the effective utilization and management of numerous data points generated by intuitive computing power and connected machines. In addition to this, many of them are uncertain about getting started with AI, its cost, and IT requirements.
Use Cases of AI In Manufacturing
AI facilitates manufacturers to cope with internal challenges that are prevalent across the industrial landscape. Such challenges can be decision making, integration issues, and information overload. Apart from this, integrating artificial intelligence in manufacturing enables plant owners to rapidly transform their proceedings.
As per a source, AI technologies will boost industrial production to approximately 40% or more by 2035. Moreover, AI is predicted to boost economic growth at an average of around 1.7% across 16 industries till 2035. In brief, AI is going to bring a rapid transformation in the manufacturing industry in the future and evolve further.
Let us take a look at how AI is helping the manufacturing sector to accomplish:
A majority of manufacturers try to keep their critical production and facility operational. AI contributes significantly to modernizing the management of maintenance, moving it from a regular or responsive posture towards a predictive one.
However, by combining machine data and sensors with artificial intelligence, plant managers can identify imminent failures and offer accurate predictions for the same. Furthermore, some manufacturers can take maintenance management even further by using prescriptive maintenance.
In addition to this, AI is used to detect the time for maintenance and recommend, prioritizing equipment maintenance, recommending spare part levels, and how long the equipment will operate without failure. Moreover, AI makes it possible to reduce maintenance costs, increase uptime, and modify equipment costs within your accounting documents.
Industrial robotics, also referred to as manufacturing robotics, is a technology to automate repetitive tasks, reduce or prevent human errors, avoid industrial accidents, and shift the focus of workers to more productive operational areas.
However, the implementation of artificial intelligence includes inspection of products, welding, painting, picking, placing, drilling, grinding, and glass drilling.
With the assistance of Artificial Intelligence, manufacturing robots can track their own performance and accuracy and train themselves to deliver better performance. Moreover, a few industrial robots are equipped with machine vision that facilitates them to achieve accurate mobility in random and complex work environments.
Workplace safety is one of the most popular use cases of artificial intelligence in manufacturing units. This trend has been primarily driven by the pandemic. With AI-enabled solutions, it becomes possible to conduct thermal screenings, conduct training, monitor employee interactions, track human contacts, and facility sanitization.
Other than this, AI tools have led to long-term solutions that are associated with workplace safety events before their occurrence. Moreover, speeding up post-incident root cause analysis. Overall, AI and digital transformation solutions lead to a safer workplace, healthier employees, and consistency in operations.
Machine vision is another segment where artificial intelligence can be useful. The manufacturing segment has witnessed rapid adoption of various prominent use cases like a warehouse, logistics optimization, quality inspection, production, and fleet management. In addition to this, such solutions have become affordable which has further led them to uptake.
Manufacturers use machine vision in logistics and warehouses to reduce transactions and increase overall capacity. Also, it alters the way pallets are prepped, makes sure that customer orders are packed accurately, and reduces employee transactions by eliminating the need for scanning. What’s more, AI-empowered solutions can improve logistics throughput, reduce return rates and increase the accuracy of customer orders.
Manufacturing enterprise owners are leveraging the potential of artificial intelligence to tackle cybersecurity issues and sensitive data concerns within the increasing number of devices. Other than that, operational technology environments produce enormous amounts of security data and logs along with their respective networks, applications, and security appliances.
Adding to this, Artificial Intelligence can assist the plant managers to sift through the noise and help by automatically detecting viruses, malware, frauds, worker behaviors deviating from normal baselines and increasing the level of threat combating intelligence. Furthermore, AI is quickly being adopted into commercial manufacturing solutions across the entire value chain of the industry.
In addition to this, when AI is combined with other technologies like machines, sensors, and human inputs will significantly improve equipment operations and open doors to the latest forms of productivity and innovation within the industry.
AI-enabled tools can assist plant managers in optimizing processes to achieve sustainable levels of production. Furthermore, they can prefer AI-powered process mining tools to eliminate bottlenecks within the organizational process. However, if a manufacturer has multiple factories across different regions then building a consistent delivery structure is quite challenging.
With AI-enabled solutions, plant managers can compare the performance of various regions by breaking it down into multiple steps that include cost, duration, and the person responsible for that step. Such insights can enable manufacturers to streamline manufacturing processes more effectively.
Manufacturing involves more information than ever integrated, and AI technologies can rationalize a way to apprehend such data. Thanks to AI, a factory worker should acquire raw materials and have an automated stock transaction. Overall this technology eliminates the need for scanning or inputting data into the system.
Combining Artificial Intelligence with manufacturing by using machines, sensors, and human inputs will drastically improve operations. It will likely open a way towards different forms of productivity and innovation within the manufacturing unit.
While your enterprise may not possess the skill sets necessary, it does not mean that you can not invest in commercial software to integrate AI into your operations. You can hire a reliable digital transformation solutions provider to kickstart your AI journey.
Robert Jackson is a content cum digital marketer at Solution Analyst, a leading DevOps development company. He is an avid reader and likes to remain updated for technological advancements in the domains of web, mobility, IoT, and emerging technologies. His articles are informative and interesting at the same time as he expresses insightful thoughts clearly.