Applications of Artificial Intelligence in Production and Industrial Engineering ! Examine the Impacts and Insights on Value Additions !

Prof.(Dr.) D G Mahto, Founder & CEO -
Abstract:

  1. Predictive Maintenance: AI can analyze data from sensors and equipment to predict when machinery is likely to fail, enabling proactive maintenance to prevent costly downtime.

  2. Quality Control: AI algorithms can inspect products on the production line for defects more efficiently and accurately than human inspectors, ensuring higher quality standards.

  3. Process Optimization: AI can optimize manufacturing processes by analyzing data to identify inefficiencies and suggest improvements, such as reducing waste or minimizing energy consumption.

  4. Supply Chain Management: AI can optimize inventory management, demand forecasting, and logistics to streamline the supply chain and reduce costs.

  5. Robotics and Automation: AI-powered robots can perform repetitive tasks on the production line with precision and consistency, improving efficiency and productivity.

  6. Digital Twins: AI can create digital replicas of physical systems or processes, allowing engineers to simulate and optimize production scenarios without disrupting operations.

  7. Workflow Optimization: AI algorithms can analyze workflow data to identify bottlenecks and optimize resource allocation, leading to smoother operations and faster production cycles.

  8. Human-Machine Collaboration: AI can facilitate collaboration between humans and machines, augmenting human capabilities and improving overall productivity and safety in industrial settings.

Keywords:
Artificial Intelligence, Production and Industrial Engineering, Human-Machine Collaboration, Workflow Optimization, Increased Efficiency and Productivity

Learning Outcomes
After undergoing this article you will be able to understand the following:
1. How AI Is Already Impacting Production & Industrial Engineering ?
2. Importance of AI in Production and Industrial  Engineering 
3. How Artificial Intelligence can be used to improve efficiency in various industries?
4. Automation of Repetitive Tasks
5. Optimization of Processes
6. Reduced Human Error
7. Increased Efficiency and Productivity
8. Improved Quality Control
9. What's the Future of AI in Production and Industrial Engineering?
10. What subjects of Artificial Intelligence be included in an existing B.Tech syllabus?
11. Conclusions 
12. FAQs
References 


1. How AI Is Already Impacting Production & Industrial Engineering ?
Artificial intelligence is the talk of the town and indeed for good reasons. Artificial intelligence can be said to be a transformative force that can shape the future. And to be honest, engineering is no exception. AI with its capability to process large amounts of data, ability to learn from patterns, and making intelligent decisions can have a very profound impact on the world of engineering.

AI is an umbrella term that encompasses a broad range of techniques and approaches, which has emerged as a major field in computer science. Almost all AI programs are meant for solving a single task for which it was specifically developed, so, it would be apt to use the term artificial narrow intelligence (ANI) as opposed to AI. In earlier years, AI programs were mostly the so-called “expert systems.” These were computer programs that mimicked expert human decisions for a given task. The expert knowledge was hard-coded into a computer program as a set of rules, based on which the program performed logical inference to provide an output that closely mirrors a human expert. Then came approaches based on heuristics, such as evolutionary algorithms, which discover solutions on their own while maximizing a performance metric. In recent years, AI systems based on ML, and specifically deep learning have gained popularity. These AI/ML systems need not be monolithic and may be comprised of several different techniques.

The top impacts of artificial intelligence on the production and industrial engineering are as follows.

Better Design Optimization

 AI tools are helping engineering push the boundaries of their creativity. Some AI tools help engineers optimize their designing process through highly optimized and effective designing tools. This not only saves time and resources but also helps engineers optimize their innovation and designing.

Automation and Robotics

 AI has made so many unimaginable things possible. For instance, AI is now working alongside humans in manufacturing units like robots. This streamline the manufacturing process making it more effective. This not only saves on resources but also enhances work safety.

Competent Data Analysis

 AI has made data analysis easier for engineers. AI’s ability to process and analyze large amounts of complex data helps engineers gain deeper insights and make more efficient data driven decisions. AI driven data analysis is changing how engineers understand complex systems.

AI Based Simulation and Prototype Testing

 AI has enabled engineers to accelerate their innovative processes. Through AI based simulation tools, engineers can effectively test their designs virtually before virtual testing. This reduces production costs as well as enhances the innovation speed.

Predictive Maintenance and Reliability

This one is a total game changer for industries like manufacturing, aerospace etc. AI based predictive tools help predict any equipment failures and disturbance using real time data from sensors.  This helps not only cut down on maintenance needs but also enhances the overall productivity.


2. Importance of AI in Production and Industrial  Engineering 

  1. Predictive Maintenance: AI can analyze data from sensors and equipment to predict when machinery is likely to fail, enabling proactive maintenance to prevent costly downtime.

  2. Quality Control: AI algorithms can inspect products on the production line for defects more efficiently and accurately than human inspectors, ensuring higher quality standards.

  3. Process Optimization: AI can optimize manufacturing processes by analyzing data to identify inefficiencies and suggest improvements, such as reducing waste or minimizing energy consumption.

  4. Supply Chain Management: AI can optimize inventory management, demand forecasting, and logistics to streamline the supply chain and reduce costs.

  5. Robotics and Automation: AI-powered robots can perform repetitive tasks on the production line with precision and consistency, improving efficiency and productivity.

  6. Digital Twins: AI can create digital replicas of physical systems or processes, allowing engineers to simulate and optimize production scenarios without disrupting operations.

  7. Workflow Optimization: AI algorithms can analyze workflow data to identify bottlenecks and optimize resource allocation, leading to smoother operations and faster production cycles.

  8. Human-Machine Collaboration: AI can facilitate collaboration between humans and machines, augmenting human capabilities and improving overall productivity and safety in industrial settings.

3. How Artificial Intelligence can be used to improve efficiency in various industries?

AI benefits various industries in their efforts to innovate: increase efficiency, enhance safety, and improve reliability.

1. Increase Efficiency

"Getting more done with less." This statement has long been the mantra of one of AI's most powerful skills: automating tasks to cut down on manual effort. Here, we outline a few ways companies have benefitted from the unparalleled efficiency of AI, which include supporting customer service, text comprehension, and image creation.

2. Supporting Customer Service 

One lingering disadvantage of human-assisted customer service is the long wait times required to contact a service representative. This unpleasant situation could be remedied if AI automated the assessment of customer data to improve quality assurance. Rapid identification of product issues results in faster product improvement, which would in turn lead to fewer frustrated customers waiting in long queues.

Companies experiencing high call volumes are using similar technology to completely automate certain elements of the process.

3. Text Comprehension 

AI’s ability to unearth valuable information among layers of data demonstrates the efficiency it provides. As the internet becomes saturated with data, even simple Google searches have become less precise amid the widespread digital noise. One practical use for AI is to improve the online search experience.

4. Image Creation 

Another efficient use case of AI is digital media creation. Models are trained with vast numbers of images to predict and generate new images accurately. This allows for the creation of a large number of images from the same prompt, saving creators substantial time developing new images. 

5. Enhance Safety

AI is not only a tool to make our lives easier and more productive, but it also has the potential to create a safer environment for us all. AI sets up safety guardrails to reduce human errors by automating or aiding complex tasks. We examine a few ways that AI supports humans by enhancing safety, tracking employee fatigue, automating hazardous tasks, and detecting anomalous health symptoms.

6. Accident Prevention 

People are likely to make mistakes, and this is especially impactful in a workplace where the consequences may be serious. For example, in the manufacturing space (which often involves large, heavy machinery), human errors pose one of the biggest risks to the well-being of employees.

These technologies have been adopted by industries such as mining, which require the operation of heavy machinery and involve working long hours filled with monotonous tasks.

Similar technology is used to address another major safety hazard: driver fatigue. 

4. Automation of Repetitive Tasks applying AI
AI automates repetitive tasks by leveraging technologies like robotics, machine learning, natural language processing, and computer vision. This automation liberates human talent for more strategic, creative, and complex responsibilities, enhancing productivity and fostering innovation across various industries.

AI will help people improve their work experience by automating rote, repetitive tasks. The technology will maximize the "goods" of work while minimizing the "bads." This may contribute to a surge in AI jobs and increased demand for AI skills. AI needs a lot of human feedback.

5. Optimization of Processes using AI
AI process optimization refers to using AI and machine learning technologies to improve business process management, support organizational strategies, and meet goals—from analyzing data to automating repetitive tasks to helping team members make better decisions.
AI can also be used to examine previous performance, behavior and other metrics that can then be used to improve and optimize your business processes and results. For example, this is very important when looking at customer buying behavior, predicting trends or detecting fraud.

6. Reduced Human Error using AI
AI algorithms empower organizations to make data-driven decisions, minimizing the impact of subjective biases. By relying on data-driven insights, businesses can enhance decision-making processes, mitigating the risk of errors stemming from human judgment.

7. Increased Efficiency and Productivity using AI
The three ways to increase productivity are technology, division of labor, and motivating employees.

One of the most significant contributions of technology to productivity is the automation of repetitive and time-consuming tasks. Software applications and systems can take over manual processes, allowing employees to focus on more value-added activities. This can be enhanced through effective applications of AI tools.

8. How AI support and improve Quality Control?
AI can help manufacturers detect defects in products faster and more reliably than manual inspection or conventional machine vision systems. AI can use deep learning algorithms to analyze images, videos, or sensor data from production lines, and identify anomalies, flaws, or deviations from specifications.

The Role of AI in Quality Management

  1. Automation of Quality Control Processes: One of the key contributions of AI in quality management is the automation of quality control processes. By utilizing AI-powered systems for data collection and analysis, organizations can streamline inspections and testing procedures. AI algorithms can quickly analyze vast amounts of data, enabling real-time decision-making and reducing the need for manual effort.
  2. Predictive Analytics for Quality Assurance: Artificial Intelligence brings predictive analytics to the forefront of quality assurance. By leveraging historical data and machine learning algorithms, organizations can identify potential defects and deviations in the quality process. This proactive approach enables preventive measures to be implemented, preventing quality issues before they occur. Real-time monitoring and continuous improvement become achievable through AI-driven insights.
  3. AI-Based Sensors and Monitoring Systems: AI-based sensors and monitoring systems play a vital role in quality control. These systems can collect real-time data, monitor quality parameters, and identify anomalies. By employing adaptive algorithms, AI can identify patterns, trends, and deviations that might be difficult for human operators to detect, ensuring that quality issues are addressed promptly, and allowing for improved product consistency and customer satisfaction.

9. What's the Future of AI in Production and Industrial Engineering?

While the spread of AI-related buzzwords in recent news may seem overwhelming and even outright confusing, we hope this article sheds some light on how AI has the potential to create value in whatever industry it lives in. The evidence shows that with proper safeguards established and privacy concerns addressed, AI can provide tangible, substantial gains, benefitting companies and individuals alike to be more productive, safe, and reliable.

Many more benefits of AI are being developed as we speak by great minds in academia and industry with even more positive changes to come soon.

10. What subjects of Artificial Intelligence be included in an existing core B.Tech syllabus?

The Essential Subjects which should be suitably adjusted or taught as optional subjects in any of the core B.Tech program are the following: 

  • Artificial Intelligence

  • Machine Learning Techniques

  • Neural Networks

  • Deep Learning

  • Reinforcement Learning

  • Data Visualization and Presentation

  • Information Retrieval and Text Analytics

  • Social Network Analysis

  • Real Time Data Streaming

  • Data and Information Security

  • Intelligent Systems

  • Deep Learning

  • Reinforcement Learning

  • Natural Language Processing

  • Text Technologies for Data Science

  • Data Analytics and Mining

  • Big Data Management

  • Bayesian Data Analysis

  • Probabilistic Modeling and Reasoning

  • Cloud Technologies

  • Internet of Things

  • Statistical Learning.

11. Conclusions 
Despite many challenges, we can expect to see continued growth in the use of AI in Production and Industrial Engineering. This growth will be driven by the increasing availability of powerful AI tools and the decreasing cost of computing power.

The rapid evolution of AI/ML technologies offers an unprecedented opportunity to transform the manufacturing industry. The broad range of manufacturing applications, detailing the potential of AI/ML to improve the safety, efficiency, productivity, and sustainability of manufacturing are of enormous importance in production and industrial engineering.

12. FAQs 

Q: What is the future of AI in Production and Industrial Engineering ?

The future of AI in Production and Industrial Engineering is bright. We can expect to see more widespread use of AI for tasks such as process automation, quality control, and productivity enhancement. 

References


Prof. (Dr.) D. G. Mahto is a multifaceted professional, serving as a Director, Professor, Philanthropist, HEI Builder, prolific writer, international consultant, reviewer, and expert career advisor at "Career Education for Success—Discover, Apply, Succeed!" He has guided countless individuals, products, and brands in discovering their true potential through insightful content, purposeful concepts, and motivational writing. With a deep sense of leadership and a commitment to community upliftment, he inspires others with his success stories and takes on the challenge of driving technological transformation, redefining social impact, and fostering interpersonal relationships for a more meaningful, balanced life. Prof. Mahto is dedicated to bridging the gap between dreams and reality for young people, striving for qualitative change in their lives. To explore his articles, books, and international journal contributions, visit his blogs at Career Education Success Now, Career Edus, and Discover Knowledge Wisely. You can also reach out to him via email.

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