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Radometech

AI in "Manufacturing"

In no other sector is artificial intelligence having more of an impact than on manufacturing, and the revolution is just beginning

Business Challenges

 

The manufacturing industry is expected to continue to grow in the next few years, despite all the challenges. Apart from the instability in both national and international economic conditions, there are also various internal challenges faced by manufacturers. Any manufacturer would want to increase their ROI, however Inventory Management and demand forecasting are still few of the main challenges in the manufacturing industry. Another challenge often faced by manufacturers is managing the machinery with highest operational efficiency and prioritizing sales leads. Up until now, manufacturers have been looking for effective ways to reduce costs and improve efficiency at their plants.

 

 

 

How can AI help?

For decades, manufacturing companies have been upgrading their plants with distributed and supervisory control systems and, in some cases, advanced process controls. With respect to operational improvement and dynamic adaptability, artificial intelligence can outperform conventional decision-support technologies. Real-time monitoring provides many benefits, including troubleshooting production bottlenecks, tracking scrap rates, meeting customer delivery dates, and more.  Also, AI enables companies to cost-effectively create and maintain their own algorithms and intellectual property in-house, which is cheaper, more versatile, and more adaptive to constantly changing equipment and market conditions. 

 

 

 

Use cases

Detects Faults: Manufacturers face challenges with machinery/product failures in many ways. A product might look perfect from outside, but it may damage once we use it. Yes, it happens to machinery, and leads huge loses to manufacturers. With the availability of vast data on how the products are tested and how they function, artificial intelligence-based tools and machines identifies the specific areas that need to be tested efficiently.

 

Machinery Predictive Maintenance: Predictive maintenance allows companies to predict when machines need maintenance with high accuracy, instead of guessing or performing preventive maintenance. Predictive maintenance prevents unplanned downtime and allows manufacturer to avoid device damage overheads. Machine Learning is one of the outmost technologies that can prevent unplanned downtime.

 

Quality Check & Control: Manufacturing requires acute attention to detail and some internal defects cannot be found easily with naked eyes. Thanks to artificial intelligence and machine learning technologies, they can detect smallest flaws in machinery. Using intelligent algorithms, smart machines can continuously monitor the productivity of machinery and spots failures, if any. 

 

Optimize Supply Chain: Use of Artificial Intelligence in the supply chain management is rapidly increasing. Machine learning, natural language processing, computer vision, robotics and speech recognition are making supply chain management tasks smarter. It establishes a strong communication channel among departments (internal & supplier communications), intelligent tools and apps can optimize the warehouse management and logistic operations. From product storing to delivery and receiving, everything can be analysed using AI. Artificial Intelligence is one of the most significant technologies that is used for managing supply, demand, and inventories.

 

Generative Design: In addition to facilitating the manufacturing process, AI can help organizations design products. These algorithms then explore all the possible permutations of a solution and generate design alternatives. Finally, it uses machine learning to test each iteration and improve upon it.

 

 

 

Why choose us?

Artificial Intelligence (AI) in manufacturing shows the greatest positive impact when compared to other industries. With documented success, why then are so many manufacturers slow to get onboard the AI train?

According to experts, 56% of manufacturers are planning to invest on AI by 2025 and expecting a revenue boost of around 40%.

 

We at RadomeTech believe AI is crucial for every business entity. Thus, we have a developed a tool which lets the user have the power of Artificial Intelligence and Machine Learning !

Get Started

Copyright Radome Techologies and Services Pvt Ltd 2020

Use Cases

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TELECOMMUNICATION

According to sources, 19% of Telecom companies are adopting AI by 2023 and 58% of Service providers see AI crucial for Network Management.

ANALYSE PERFORMANCE DATA
AUTOMATION OF NETWORK MANAGEMENT
SPOT ANOMALIES IN NETWORK TRAFFIC
IMPROVE NETWORK CAPACITY PLANNING

OIL & GAS

Oil  & gas is one of the most lucrative industries, it is also one of the most dangerous. According to experts, 50% of Oil & gas industries say they have already begun AI to help solve challenges at their organisations.

OPTIMIZE PRODUCTION AND MAINTENANCE COST
ENHANCE QUALITY ASSURANCE
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DEFECT DETECTION
ABILITY TO MAKE BETTER DECISIONS

REAL ESTATE

Experts believe that 16% of the Real Estate companies are adopting AI in their businesses by 2023 and are expected to see a marginal profit of around 50%

IMAGE RECOGNITION & ANALYSIS
ANALYSE PATTERNS
RISK FORECASTING
OPTIMIZE SCHEDULES
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What we do.

We craft unisex leather bags and accessories for those, who appreciate premium handmade products, durable quality and urbane style.

AI for Healthcare

In the complex world of Healthcare, AI tools can support healthcare providers to provide faster service, diagonse issues and analyse data to identify trends or genetic information that would predispose someone to a particular disease.

AI ASSISTED MEDICAL DIAGNOSIS
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MEDICAL RISK PREDECTION
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AUTOMATED WORKFLOW ASSISTANCE
MEDICAL IMAGE ANALYSIS
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Use Case

Aircrafts require a vast spectrum of parts to operate ranging from high cost repairable parts to low cost fast moving consumables Apart from the fact that certain parts are highly expensive, failure to have the necessary part readily available can also translate into expensive AOG (aircraft on ground) incidents.

Manufacturing

Experts believe that about 40% revenue boot will be there upon adopting to AI in Manufacturing. Around 50% of the manufacturers are planning to Invest on AI for their processes.

DETECTS FAULTS
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REDUCE UNPLANNED DOWNTIME
PREDICTIVE MAINTENANCE
Quality control

Retail

According to sources, 85% of customer interaction in retail will be managed by AI by 2023 and a revenue growth of 10% on adopting AI in the business process.

DEMAND FORECASTING
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SUPPLIER PERFORMANCE PREDECTION
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OPTIMIZE INVENTORY
ROUTE OPTIMIZATION