Generative AI has gained significant prominence worldwide in 2023, transforming the way researchers, enthusiasts, and software developers tackle machine learning and artificial intelligence challenges. Generative AI is an artificial intelligence subfield that can create content in the form of text, images, music, and code. A massive amount of text data is used to train these models. Let us examine some use cases of these models in the manufacturing industry.
- Text Generation and Summarization: Large language models can generate text in a conversational and human-friendly manner. These models support several languages and aid in use cases such as producing content for marketing and sales departments, supporting developers with code documentation, and assisting developers in understanding the code written. Long-format papers can be summarized using Generative AI models to deliver precise, context-relevant information. Summarization can be tailored to the user’s preferences.
- Semantic Search Systems: These models can be used to build search and knowledge-based systems that can recognize the context in user queries and return relevant information, enhancing user acceptability and search experience over traditional keyword-based search systems.
- Question and Answering Systems: The generative models may also answer user queries by recognizing the context of the query and generating answers utilizing knowledge learned from massive amounts of data relevant to the user inquiry.
- Synthetic Data Generation: Generative models, with their vast knowledge base comprising massive amounts of data, may generate synthetic data for experiments and training machine learning models in situations where real-world data is unavailable.
- Image Generation: Generative models can create images with various artistic styles, settings, and colors. These are useful in generating synthetic images to aid users in machine learning modeling.
Applications in Manufacturing – Warranty and After Sales
- Claim Process Optimization: Warranty dealers and claim processors can use Generative AI models to revolutionize question-answering systems by answering queries with interpretable and appropriate reasoning by understanding the context and semantics of queries using a large number of documents. The systems shorten the procedure and optimize it.
- Customer service and support: Using generative language models such as GPT3.5 and GPT4, personal assistants and chatbots can be constructed to aid customer support teams in addressing client inquiries and issues relating to warranty, claim procedures, and troubleshooting steps. These models can also help with faster claim processing and provide a better client experience.
- Warranty Claim Validation: Claims processors can use Generative models to analyze and validate dealer claims. These models use warranty information, product specifications, and claim information to identify patterns of fraudulent claims and make decisions to automate the validation process, prevent fraud, and speed up claim settlement.
- Recommendations: Using usage patterns and historical data, large language models can provide individualized recommendations to clients and dealers regarding warranty coverage and upgrades.
- Text Sentiment Analytics: Customer evaluations and feedback can assist warranty providers and dealers in improving their service, identifying and resolving reoccurring issues, and enhancing the overall customer experience. Without the need for training, generative models can assist in determining the sentiment of the text. These models extract textual patterns and provide reasoning for sentiment prediction.
- Intelligent Search System: Generative AI models can aid in the creation of a centralized knowledge base that dealers, technicians, claim processors, and warranty providers can use to find and obtain relevant information on claims, warranties, troubleshooting common issues, service manuals, and FAQs. It lets you quickly discover root causes, potential part replacements, SLAs, and applicable resolution actions. It can return relevant search results and citations, as well as supporting content related to the context of the query.
- Quality Control and Defect Detection: Generative AI algorithms can analyze a large amount of manufacturing data, including sensor readings and images, and process this information to detect defects and patterns identified in the data.
Tavant is actively exploring and integrating these cutting-edge features into the highly advanced Tavant Manufacturing Analytics Platform (TMAP). This strategic initiative aims to empower customers with a distinct competitive edge by utilizing advanced Generative AI models. In our initial forays into this dynamic field, we have successfully developed compelling POCs in the domains of chatbots, personalized assistants, and smart-search systems. Leveraging warranty after-sales data, these pioneering POCs deliver unparalleled value to dealers and claim processors.
Some of the modules in TMAP where we are exploring Generative AI models are:
- Warranty – Automate claims processing, identify suspicious information, improve dealer performance, reduce warranty spend, enhance the quality of the claim, and identify anomalies in the image.
- Price – Recommend optimal parts price, completive pricing analysis, evaluate the performance of pricing strategies, monitor and alert price changes, and segment customers based on their price sensitivity.
- Quality – Identify product quality issues, failure rates, and areas for improvement by analyzing claims, returns, and repairs.
- Field – Optimize services using AI Smart search, service & parts demand to forecast, and real-time insights enabling you to improve service quality and enhance customer satisfaction.
- Contract – Enhance contract performance, improve profitability, mitigate risks, and strengthen customer relationships through personalized contract offerings and optimized prices.
Final Thoughts
By utilizing the various text content available, such as installation and warranty manuals, service guides, and safety guidelines, Generative AI can transform the manufacturing industry by enabling technicians, dealers, and manufacturers with personalized assistants, chatbots, intelligent search systems, and recommendations. This can assist dealers in providing excellent customer care, as well as business users in identifying potential issues and improving the product and after-sales services.