Artificial intelligence (AI) has been a driving force behind increased productivity in manufacturing for over a decade. Various applications, ranging from predictive maintenance to defect detection, have proven the value of AI models coupled with data.

However, in recent months, we have witnessed a new phase of the AI revolution, where early adopters are already experiencing remarkable productivity gains. In this article, we will explore how these emerging technologies, like Open AI and large language models, are reshaping the manufacturing landscape.

AI Use Cases in Manufacturing

1. Extracting Valuable Insights with Natural Language Prompting

Within manufacturing operations, there is an abundance of written information, including processes, manuals, and documents related to various tasks.

Leveraging a Large Language Model (LLM) with a chatGPT interface, this textual data can be effectively crunched and valuable information extracted within seconds.

Workers, engineers, and operators can now access this wealth of knowledge effortlessly, revolutionizing the way they search for and retrieve necessary information. It's like having an intelligent assistant to guide them through complex procedures.

2. Streamlining Communication and Response Time

When a worker encounters an issue on the production floor, reporting it promptly and accurately is crucial. By utilizing generative AI technologies like ChatGPT workers can easily communicate the problem, and through automated classification and simple business logic, the system can initiate appropriate actions, such as triggering quality tests, maintenance responses, or seeking supervisory assistance.

This streamlined communication process significantly reduces response time, ensuring timely resolutions to operational challenges. (Download AI Messenger from Tulip library). Over time resolutions can be suggested directly to the operator by the AI using the approach demonstrated in paragraph #1.

As the issues are resolved, the resolution can be saved as a text description to create a natural language data set of successful solutions. This can then be made available to the AI to return similar issues and their successful resolution and even a recommended next best action.

3. Empowering Non-Technical Users with SQL Queries

Business Intelligence (BI) plays a pivotal role in obtaining real insights from manufacturing data. However, traditional BI tools often require specialized knowledge, limiting their accessibility to data experts. The advent of AI-powered solutions challenges this status quo.

With the assistance of AI, individuals without extensive BI experience can now create SQL queries and extract meaningful insights from data within seconds. As AI continues to advance, it will even suggest queries and provide comparative analyses, making data-driven decision-making more accessible and intuitive than ever before.

4. Reinventing Standard Operating Procedures (SOPs)

Standard operating procedures (SOPs) are vital in industries such as pharmaceuticals, where complex, routine operations must be executed with precision. Traditionally, creating SOPs has been a time-consuming process, requiring meticulous documentation. However, with the integration of Tulip's frontline operations platform and OpenAI APIs, a new era of SOP creation has arrived.

By harnessing the power of AI and applications, workers can now automatically generate SOPs, saving substantial time and resources. This transformation allows organizations to focus more on operational excellence and process improvement, ultimately enhancing overall efficiency.


The impact of AI on manufacturing productivity is rapidly evolving. From extracting insights from textual data and facilitating effective communication to empowering non-technical users with data analytics capabilities and automating SOP creation, AI is revolutionizing the industry.

Early adopters are already reaping the benefits of these innovative technologies, experiencing increased productivity, improved efficiency, and streamlined operations.

As AI continues to advance, we can expect even more creative and transformative applications that will shape the future of manufacturing, driving us toward unprecedented levels of productivity and competitiveness - Tulip is the easiest way to extract the value out of it, now and in the future.

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