Role of AI in Product Life Cycle Management
A product is an essential asset for any company. The value of a product varies throughout its life cycle. The usage of the product and internal and external factors affect its value. In short, the life cycle of the product is not a linear path.
Product life cycle management is a set of activities used to identify, measure, and improve the value of a product through its life cycle. So, how does Artificial Intelligence or Machine Learning fit into this process?
This blog analyzes how Artificial Intelligence can play a role in product life cycle management.
How do AI and ML Impact the Product Lifecycle?
Artificial Intelligence is the practice of creating machines that behave like humans. AI analyzes data and concludes to make better decisions. As technology evolves, AI is used in many areas. Some of the many uses of AI are in robotics, machine learning, pattern recognition, and planning.
These systems require models to train and make informed decisions. A machine learning model is a mathematical model used to perform a specific task. Machine learning models are trained using data and can be used to make predictions about new data.
As more companies adopt ML, they’ll need more data scientists and data engineers to help them build and scale systems that can handle the heavy lifting. Modelops is an approach to developing and deploying ML systems that takes advantage of the distributed processing model of ML.
Benefits of modelops include:
- Improved efficiency and scalability
- Reduced development time and cost
- More robust models
Additionally, AI helps to identify insights in all sorts of data, revealing trends and patterns that would otherwise have gone unnoticed.
Utilizing AI in PLM makes it easy to leverage rich products and services and deliver highly customized experiences.
- AI in Product Design
Source: FreePik
The initial product design phase is essential to the product lifecycle management process. During this phase, you will be working on building the foundation of your product and developing your business.
In this phase, AI can help you identify new opportunities in your products and services in real-time. You can also use it to make your current items better so that your products surpass competitors by offering better features at lower costs.
This way, data analysis combined with AI can give you a competitive advantage.
Integrating artificial intelligence with PLM offers an efficient and automated way for product design and development. Artificial intelligence helps the design and development team understand the product’s underlying factors and performance. You can do this by using AI tools. It saves not only time and money but also enhances the quality of the product.
- AI and ML Algorithms in Manufacturing
The application of artificial intelligence in manufacturing enables businesses to bring greater efficiency, transparency, and traceability to manufacturing operations. AI technology is a supporting tool for analyzing the data and information from R&D, Engineering, Logistics, and Marketing.
It can include changing how raw goods are processed, how products are created, and how goods are packaged. AI also provides data indicating where efficiency can be improved in the production process. Humans can then act on this intel to improve the process.
- AI in Testing Automation
Source: FreePik
Product lifecycle management addresses the entire lifecycle of a product, from conception through distribution. It requires that you test your products at every stage along the way. It starts before you create your product, during its production, and after its launch.
Unit testing is the most popular kind of testing. It means testing each feature or function individually. It can be helpful when you want to verify your software’s or hardware’s accuracy before releasing it on the market. It catches bugs before they get into production environments, where they can cause severe problems for customers or employees.
However, this kind of testing doesn’t necessarily mean that you’re going to see how these features interact with each other. For example, how the input interacts with the environment.
Machine learning algorithms can be programmed to automate the testing procedures and use that information to develop new features. The process will be much faster and more cost-effective.
- AI in Product Optimization
The role of AI in optimizing products through PLM has dramatically impacted how manufacturers can ensure that every product is optimized and meets customer needs. Why use AI?
Using AI, we can collect data and learn from it. It allows us to make improvements to our products continuously. By improving our products, we’re increasing their quality. When they’re of higher quality, our customers are more satisfied.
- AI in Distribution
With AI’s help, companies can now distribute products more efficiently. The first step is gathering all relevant information about the products you want to distribute. This includes price, availability, and size. Once you have gathered all this information, you can use it for your predictive analysis.
The second step involves performing your predictive analysis on historical data. It will help you make predictions about future events based on this data.
For example, if you want to predict which products will sell better during a particular month, you will need to look at past events when these products were distributed during that month. Then, you can predict which ones would sell more than the others.
Being able to do this means being able to do other things better. For example, reducing the production costs, increasing the quality of products, increasing the speed at which the product is produced, and increasing the efficiency of processes. This introduction of technology has been vital in the movement for modern supply chain management.
- AI in Performing Real-Time Checks
AI can perform real-time performance checks of products. AI algorithms can provide analyses of data collected from different sources. Algorithms will set certain parameters to check if the product is fulfilling the requirements or not.
It will help reduce the cost of testing and ensure that the product is tested before it goes out to market. It helps in reducing human error. Because machines don’t make mistakes; they are more accurate than humans when performing specific tasks.
Final Thoughts
The role of Artificial Intelligence (AI) in Product Lifecycle Management (PLM) is a growing trend in the industry. Take the Artificial Intelligence Course to learn more about AI. Companies are finding ways to use intelligent systems to streamline their processes. While AI is commonly associated with machines’ intelligence and processes’ automation, developers are increasingly using it to make their products more efficient.
