Artificial intelligence in manufacturing is changing the world and AI will lead to the fourth revolution in manufacturing. In manufacturing, AI is opening the way for the “Industry 4.0” era. Manufacturers all over the world are using artificial intelligence to reduce critical errors, improve production times, and improve safety measures.

Soft Designers provide the manufacturing intelligence necessary for the modern digital factory, enabling an automated and connected ecosystem. Connected Intelligence combines processes, equipment, and IIoT devices seamlessly to deliver data for better control and better analytics, allowing organizations to reduce costs and improve operations by predicting the future.

Features of Artificial intelligence:

  1. Data management
  2. Predictive analysis 
  3. Data analysis
  4. Big data analytics
  5. Data visualization

Softdesigners’ digital platform allows manufacturers to gain real-time insights into every part of their manufacturing process and optimize operations. Collects information from multiple sources, analyzes it, creates a “digital twin” of a business’s infrastructure, and highlights areas that can be optimized.

Artificial Intelligence: Why It’s Important:

Artificial intelligence, when applied to system operations & maintenance, reduces downtime, increases safety, and improves reliability and performance of industry operations.

In manufacturing, artificial intelligence is used to combine data from multiple sources. This information is used to produce reports and analyses. By using a manufacturing intelligence system, manufacturers can gather data, manage data in a simple format, and use the data to improve operations.


Accurate reports in real-time:

Modern manufacturing intelligence systems gather data directly from the source of the machine or equipment. They then communicate that information in real-time to operators. These systems can also collect large amounts of data. These are data sets so massive that they can’t be manually recorded. This is known as big data.

A better customer relationship or satisfaction:

Real-time data analytics has been proven useful for machine operators and employees. Data analytics can also benefits respective customers. It basically eliminates the guesswork. Accurate real-time data gives you the ability to make accurate and timely predictions. It is an important part of becoming a data-driven business.

Actionable insights:

AI tools with massive visualization options and smart analytics capabilities are becoming increasingly available through the cloud, giving even small companies the edge to compete in a tight business environment. With these tools, it is easier to derive actionable insights that can help management make correct decisions


AI is used for:-

  1. Predictive Manitenance
  2. Augmented reality
  3. AI Surveillance

AI Predictive Maintenance in manufacturing

Real-time prediction is essential for smart manufacturing use cases such as inventory stocking for just-in-time production, quality monitoring, and so on. Using Soft Designer’s predictive maintenance workflow simplifies and automates the process of executing predictive models rapidly for operational experts.

The goal of predictive analytics is to predict future events using historical data. A mathematical model is built by using historical data to capture important trends. Predictive models are then applied to data to suggest what will happen next or to suggest the actions to take to maximize the chances of success. Due to advances in supporting technology, predictive analytics has gained a lot of attention in recent years, especially in the areas of big data and machine learning

Uptime improvement can be achieved by ensuring predictive maintenance in factories.

Predictive Maintenance can be used in various industries, such as:


Automotive industries:

In order to create driving assistance algorithms and driver assistance technologies, companies developed with sensor data from connected vehicles use predictive analytics to analyze sensor data.

Aerospace industries:

A manufacturer of engines created a real-time analytics application to predict subsystem performance for oil, fuel, liftoff, mechanical health, and controls in order to improve aircraft uptime and reduce maintenance costs.

Food and beverage industries:

Food and beverage manufacturers can take more control of their quality parameters is through data analytics. It provides a way to understand which element will have the greatest effect on a product during manufacturing and predict the impact of these factors on quality and taste.

Oil and gas industry:

Predictive maintenance is used in the oil and gas industry to enhance oil recovery (EOR) and improve oil recovery (IOR). It provides a screening tool and speeds up typically lengthy evaluations.

AI Surveillance:

Video surveillance has traditionally been seen as a reactionary technique incapable of detecting real-time threats. Previously, security teams had to rely on external security indications to develop further measures. This meant manually monitoring cameras after being alerted to a possible attack, which was usually ineffective.

Modern video surveillance uses artificial intelligence (AI) video analytics to discover and report problems in a fraction of a second. As a result, it is a very dependable proactive security system.

Because of the unique processes used to analyze video information, AI video analytics has exploded in popularity in recent years. This technology has gained widespread acceptance, as seen by its rapid growth.

Soft Designers AI surveillance detects:

  • Personal Protective Equipment (PPE) Detection:
  • Intruder Detection
  • Unwanted object detection

Personal Protective Equipment (PPE) Detection:

SoftDesigners AI surveillance can quickly and accurately detect the worker’s parts of a body where PPE is worn. If the worker does not wear the PPE immediately the notification will send to the management team.

Intruder Detection:

SoftDesigners Intruder detection system (IDS) is a software application that monitors a network for malicious activity or policy violations. Any malicious activity or violation is typically reported or collected centrally using a security information and event management system.

Unwanted object detection:

Object detection is used in tracking unwanted objects. This application helps to detect unwanted storekeeping, manufacturing defects when not visible to human eyes.

Augmented reality:

In augmented reality, a device camera captures live footage, which is then displayed on a screen with 3D elements overlayed. As a result, parts of the view are transformed into digital content and have the potential for interaction.

There is a natural bridge between AI and AR technologies, including advanced analytics and computer vision. Augmented reality and artificial intelligence (AI) are closely related technologies that application developers can combine to create different experiences. At its core, AR is an experience that combines both digital and physical environments.

Artificial intelligence involves the use of machines to simulate human intelligence, especially computer systems. Using AI software tools, machines can adapt to inputs, learn from experiences, and perform human-like tasks.

Key factors to be considered:


  • The use of predictive maintenance is highly effective in various fields, including risk assessment, equipment analysis, trend forecasting, and data mining.
  • By analyzing predictive information, organizations can develop better products, improve their response times, improve customer service, and stay ahead of the curve for better customer satisfaction.
  • Al helps to boost sales, enterprises can better serve their customers through better use of such tools.
  • This advanced digital technology can greatly benefit manufacturers by optimizing their operations and speeding up production.

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