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3 AI trends for Industrial to watch out for in 2023 and beyond

As the Industrial landscape becomes more complex & competitive, Industrial OEMs are under pressure to find new ways to optimize their operations and get ahead of the game. Artificial Intelligence (AI) has emerged as a powerful tool that can help Industrial OEMs address some of their most important challenges, these are a few AI trends for Industrial.

With the advent and rapid mainstream adoption of Chatgpt and similar technologies, AI has gone from a ‘we need it, but not sure how we’d use it’ concept to a practical, purpose-driven tool of choice for machinery manufacturers.

3 AI trends for Industrial:

In this blog, we will explore 3 AI trends for Industrial that will rapidly transform the industrial landscape in the years to come-

1. Predictive maintenance

Predictive maintenance is a foresighted approach to maintenance that uses data analysis and machine learning to identify potential equipment failures before they occur. Predictive maintenance using AI can detect equipment issues before they happen, allowing OEMs to schedule maintenance activities and prevent unplanned downtime.

AI algorithms can collect data from previously recorded service transactions, aftermarket parts & service sales, and other sources to create predictive models that can identify patterns and irregularities that are not easily detected by human operators. These models can predict when a piece of equipment is likely to fail, enabling OEMs to schedule maintenance activities in advance, reducing downtime, and avoiding costly repairs. 

A note on IIoT – While IIoT is still a promising technology, its implementation requires real-world upgrades to existing machines in the field. This is often cumbersome and complex as not every machine is upgradeable or the customer may refuse to upgrade at cost. Without a comprehensive roll-out of IIoT across the entire Installed Base, a narrow view of a few machines with IIoT hardly helps a machinery manufacturer pre-empt service requests and provide the required aftermarket parts & service resources.

2. Aftermarket Sales

Aftermarket sales are an important revenue stream for industrial OEMs. The aftermarket revenue of an asset can be as high as 5 times the original equipment price over years of operation. However, traditional aftermarket sales methods can be inefficient and may increase costs, as they mostly rely on manual processes and may involve unnecessary inspections or replacements. 

AI is transforming the way aftermarket sales used to work by enabling OEMs to provide personalized and more efficient services to their customers. Example: Artificial Intelligence-powered analytics can be used by Industrials to identify which parts are more likely to fail and when allowing OEMs to offer predictive maintenance services and sell parts that are more likely to fail, this will also help in inventory management by ensuring that the right part should be available at the right time.

3. Inventory Management

Effective Inventory Management is critical for the success of Industrial OEMs to enhance the effectiveness of their customer service. However, managing inventory is quite a hassle for the Industrials as it involves balancing the stock needed to be stored in addition to the cost of holding the inventory.

Artificial Intelligence is transforming inventory management by enabling Industrials to optimize their inventory. Artificial Intelligence-powered analytics can analyze historical data on sales and inventory, and also the other factors such as weather or season, political, and market conditions to forecast the demand and optimize the inventory required. This helps Industrials reduce inventory costs and ensures that they have the right part at the right time to cater to their customers.

In conclusion, AI trends for Industrial are revolutionizing the way Industrials used to operate. Artificial Intelligence is transforming the Industrial OEMs landscape by enabling predictive maintenance, optimization of aftermarket sales, and optimizing inventory management. By leveraging Artificial Intelligence, OEMs can increase efficiency, reduce costs, and improve customer satisfaction, giving them a competitive edge in a rapidly evolving market. As AI technology continues to advance, we can expect to see even more transformative applications in the Industrial sector. Read about AI in Aftermarket for Industrial OEMs in 2023.

About Entytle

Entytle, Inc. provides an Installed Base Automation (IBA) platform that assembles, cleanses, analyzes, and operationalizes Installed Base data so machinery manufacturers can make customer-facing workflows more efficient. Entytle’s IBA platform is deployed across thousands of Industrial OEM users. Other applications on the platform include IB HealthCheck, Customer Loyalty Manager, Data Quality Engine, and Entytle APIs, web and mobile interface amongst others that run on the versatile IBA platform. The cloud-based platform includes purpose-built AI that provides a complete 360 view of the Installed Base, intelligent hunting lists, and the ability to orchestrate automation between various tools, systems, or processes. This enables smarter, faster workflows leading to increases in productivity, capacity, and scalability. Industry leaders such as Johnson Controls, Baker Hughes, Peerless Pump, Dematic, Duravant, GEA, and many more trust Entytle to help drive efficiency and growth using their Installed Base. Learn more about how Entytle can help you win over your Installed Base and drive commercial productivity at www.entytle.com.

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