Three use cases for generative artificial intelligence in production

Artificial intelligence (AI) has the potential to turn the way we work today completely on its head. For years, companies across various industries have been working to implement machine learning, deep learning, and other AI-based algorithms to analyse large datasets with self-learning systems and solve specific tasks through pattern recognition built on that foundation. Since the end of 2022, the hype surrounding generative AI, or GenAI for short, has acted as an additional catalyst for this trend. Increasingly, manufacturing companies are also allocating budgets to create the resources needed for the implementation of practical AI solutions.

A recent study by IT service provider adesso on the use of GenAI in German industry sheds light on why: 70 % of respondents stated that they save at least three hours a week by using GenAI. But AI doesn’t just promise efficiency gains. The introduction of technology also provides the ideal opportunity to re-evaluate processes and transform them.

“To fully harness the potential of GenAI in development and production, decision-makers should not only identify opportunities but also design projects and refine processes – from procurement to service,” says Dr. Olaf Neugebauer, Senior Manager and Head of the Competence Center IoT at adesso. “The insights and freedom that market stakeholders gain through the use of AI allows them to raise the quality of their services and products, and therefore customer satisfaction, to a whole new level.”

Dr. Olaf Neugebauer is Senior Manager and Head of the IoT Competence Centre at adesso. (Source: private)

Creating frameworks

Industrial companies are currently focused on implementing their IT and data strategies to future-proof their IT landscapes. By doing so, they are aiming to reduce costs, add more flexibility and boost efficiency, as well as get started on real-time analysis, automate processes and implement AI.

The following three areas offer significant potential for the use of AI and GenAI in the manufacturing industry.

1. The talking machine

The scenario: All condition monitoring data and machine notifications are efficiently collected through an IoT platform. A GenAI system then uses this data to generate audience-specific information in clear and understandable language via interfaces. This results in concise linguistic summaries of complex machine dashboards and analyses. In a subsequent stage, this technology could be linked to a “digital maintenance assistant” that revolutionises maintenance processes.

2. Digital maintenance assistant

Do detailed manuals and machine documentation, often spanning several shelf meters and lacking centralised accessibility, create unnecessary work? Instead of laboriously searching for the right information, employees should be able to directly interact with manuals and maintenance reports through a chat interface, quickly finding appropriate solutions in case of errors. The next stage of this digital maintenance assistant could be a connection to the “talking machine”, which offers proactive support and revolutionises maintenance processes. This efficiently links machine condition data with the knowledge base from manuals and maintenance documents.

3. Similarity analysis in engineering

A GenAI system like this is specially designed to support the processing of quote and project enquiries. It helps specifically with the question: “Has something similar already been manufactured or designed?” If the answer is yes, the system provides valuable information about previous projects and offers recommendations on how existing parts could potentially be modified. This saves companies time and resources, while at the same time allowing them to fall back on tried and tested solutions.

Neugebauer concludes: “We are on the cusp of an era when market opportunities will be reshuffled. The rise of the internet and mobile business have transformed the economic landscape, creating new market leaders. Now GenAI is set to bring about equally far-reaching changes. GenAI technologies are going to be as commonplace in the future as e-mail or smartphone apps are today. The manufacturing industry should already be preparing for this now – because the time has come to turn enthusiasm for GenAI into actual business success.”

Do you have any questions?

There is no website or brochure which can replace a personal meeting to talk about your goals and topics. We are looking forward to an appointment on site.