AI in Manufacturing Industry, quality assurance, manufacturing process optimization, supply chain optimization, smart assitance, failure mode predict
ARTIFICIAL INTELLIGENCE IN THE MANUFACTURING INDUSTRY
Artificial intelligence refers to a system's ability to simulate or mimic human mental power and AI is gaining its popularity. AI started in computer science. But it's broadening its reach into other disciplines and into industries including manufacturing these days. So then machine learning is a subset of AI.
Machine learning is a self-learning and self-enhancing algorithm to make
machine learning possible data and data modeling. Because machine learning
algorithms learn through data.
Manufacturing industries have gone through many phases starting with
mechanization at the stage of Industry 1.0 and Industry 2.0. It was driven by
mass production and electricity automation was the hallmark of
Industry 3.0. The latest word in manufacturing is industry 4.0 also known as
the fourth Industrial Revolution which features
ubiquitous smart systems. These working together through the internet with
minimal human intervention.
So industry portfolio takes industry 3.0 to the next level by incorporating new technologies. Such as the Internet of Things, AI, and self-monitoring is another important characteristic of industry 4.0. To identify and define a manufacturing problem to solve which is time-consuming, expensive, and also very error-prone. So an ideal solution is automation. Artificial intelligence in the manufacturing industry is being used across a variety of different application cases.
Quality Assurance
Quality assurance is a manual job that requires skilled engineers to ensure that electronics and microprocessors are being manufactured correctly to prevent mistakes or defects in products. All its circuits have the proper configuration. Automated optical inspection (AOI) is an automated visual inspection technique where a camera automatically scans the device using a machine scanner under test for both failure and quality defects. Automatic optical inspection uses computer vision technology.
Manufacturing Process Optimization
Once AI is implemented in this process through autonomous machines or
robots. They replicate monotonous tasks in the manufacturing process. Thus
saving costs before proposed to production. The autonomous machines/robots
perform the same task repeatedly. Learning every time until they provide enough accuracy.
Order picking
Retrieving products from the storage area for shipping them in different unit sizes. It should be a more accurate and direct influence on the delivery time.
Safety and Security Standards
Artificial intelligence is used as a way to support is enhancing the individual operator experiences through augmented reality technologies. This will assist field workers to perform their duties or otherwise in supporting various health and safety aspects of that fieldworker supporting them to make sure that they're wearing the correct personal protective gear. Also supporting them throughout the entire operational process making sure that if they fall in that. Artificial intelligence can pick them up making sure that their entire operation is safe.
Supply Chain Optimization
AI tool implementations are major improvements to industrial supply chains
and inventory management applications. Predictive inventory management uses
predictive analytics for various inventory-related tasks including reducing
inventory planning time. Minimize inventory, Cost optimize repairment’s and
find optimal reorder points. For these tasks techniques such as time series
analysis, probabilistic modeling, as well as simulations, are most commonly
used.
Assembly Line Optimization
By layering artificial intelligence into the assembly line various
automation can be created. Like when equipment operators are showing signs of
fatigue supervisors get notifications when a piece of equipment breaks down. Then the system can automatically trigger the following plans or other
alternative activities.
Cyber Security and Privacy
AI-driven cybersecurity and privacy are related to aspects such as cyber threat
detection. It observes the network infrastructure and detecting threats in
real-time. It often includes such network activities as network traffic
analysis, endpoint detection, and response, malware sandboxes, etc.
AI-powered cyber threat detection is often part of a larger cybersecurity
solution. That also uses many prevention measures.
Automated Data Management
Data is stored in many systems. So it is hard to access and analyze the
data quickly and holistically. So, some industrial companies start to
engage the service of data management solutions. They perform tasks such as
data acquisition, data preparation, data filtering, data cleaning, and
integration, etc. in real-time.
Smart Assistant
An intelligent voice assistant is a significant example of a smart
assistant. In manufacturing settings, integrating voice assistant
technology into its real-time industrial monitoring systems that notify,
suggest, predict, prevent and focus on operations. It allows workers to
gain data-driven insights and perform tasks without coding the explicit
commands or printing status reports.
Failure Mode Prediction
A product may look perfect but it breaks down soon for the first use
similarly a product that looks defective may do its job perfectly. It
identifies the occurrence of possible failure and predicts the severity by
using a large amount of data on how products are tested and how they
perform. Artificial intelligence can identify the areas that need to give
more attention to tests and improve performance.
Predictive maintenance
Predictive maintenance allows organizations to predict when machines need
maintenance instead of guessing or performing maintenance. It prevents
unexpected downtime and breakdown by using machine learning techniques.
Technologies such as sensors and advanced technologies are embedded in
production equipment. This enables predictive maintenance by using alert
systems and resolving machine issues/failures.
AI-Driven Research and Development
Automated component design is the most significant use case in AI-driven
R&D. The goal letting software independently develop different designs
in a short time, given a set of pre-defined constraints. Digital twins and
simulations often enhance AI techniques.
Generative Design
Artificial Intelligence can help manufacturing companies or organizations
design products. Exploring all the possible permutations of a solution and
quick generation of alternative design solutions. Finally, it uses machine
learning to check each iteration to improve the process.
Defect Detection
AI is used as a way to enhance defect detection through sophisticated image processing algorithms. That can automatically categorize defects across any industrial object that it sees. It is being used to analyze sensor technologies in the Internet of Things. These technologies are looking into the industrial manufacturing process to collect data to understand and how to improve those efficiencies related to the production output and how often things fail.
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