Faster and better: AI use cases for ETO/MTO companies

Faster and Better - Intellico

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A recent analysis by the Observatory on Artificial Intelligence highlighted how the ageing of population will result in an unbalance between working and retired population in ten years. These figures suggest that an increase in productivity is not just a matter of competition, but also of survival for many companies. This is more relevant for companies delivering very specialized components, leveraging on high vertical skills of their technical teams built with years of experience on designs.

In the dynamic world of engineering, the concept of design-by-reuse stands as a beacon of efficiency and innovation.

Utilizing existing designs and components, this approach not only streamlines the engineering process but also reduces development time and costs – key factors in Make-to-Order (MTO) and Engineer-to-Order (ETO) sectors.

How can AI leverage on past experience to boost companies’ flexibility and productivity in the context of MTO/ETO?

Let’s see some examples of use-cases Intellico Solutions lead with MTO/ETO companies in the machinery and machinery components field.

Better design, faster

In our previous article (link) we described how design-by-reuse can improve time-to-market efficiency. By analyzing past designs, AI systems can compare designs and suggest similar past designs.

ETO/MTO companies in manufacturing can process hundreds of CAD projects per week. The challenge of enhancing process efficiency is to find out which products or components already exist and can be reused or adapted in the initial phase of a new generation or product variant. It is a common challenge for many manufacturing companies that have a large database of CAD product models containing years of engineering experience. However, it is often difficult to perform targeted database queries to find specific design information, and this can slow down the design process, making it difficult to re-use existing components.

Portfolio rationalization

Similarity analysis on designs can also support the correct classification of design into specific families based on similar characteristics, improving the existing archiving system, and facilitating the efficient management and retrieval of designs. Furthermore, AI plays a critical role in identifying the most relevant design variants to be selected as a “platform”. This selection process is crucial for reducing variability in the portfolio offering, ensuring a more focused and efficient product strategy. Leveraging AI in this way allows ETO companies to improve product management and ultimately better organize operations and delivery to the client.

Smart configuration

For companies operating ETO/MTO sectors, the ability to efficiently customize products according to specific customer requirements, manufacturing processes, and existing equipment in their plants is crucial. AI recommendation engines excel at configuring tailored offerings by intelligently suggesting the optimal combination of components. They achieve this by analyzing information from past successful quotes and leveraging insights into customer preferences and requirements. This not only streamlines the customization process but also enhances the accuracy and relevance of the offerings, ensuring that each customer receives a solution that is precisely aligned with their needs.

Adaptive scheduling

The inherent variability in the production processes of MTO/ETO companies often challenges the effectiveness of traditional deterministic scheduling software. These systems can struggle to accommodate the fluidity and customization required in MTO/ETO environments. In contrast, AI offers a dynamic solution by leveraging historical manufacturing data to inform scheduling decisions. AI algorithms can analyze past production cycles and, by recognizing patterns and similarities in product design, accurately predict the duration of manufacturing phases or determine the most efficient sequence of operations. Its real power, however, lies in its ability to swiftly adapt to unexpected changes in priorities, seamlessly reorganizing schedules to maintain operational efficiency and meet customer deadlines, even in the face of unforeseen challenges.

And what about generative AI?

So far, we have presented some predictive AI use cases. However, generative AI further boosts knowledge sharing inside companies. It significantly enhances the utility and accessibility of maintenance manuals and other internal sources, offering a transformative tool for industries reliant on complex machinery and systems. Through natural language processing and machine learning, generative AI can elaborate the content of extensive maintenance manuals, making it easier for technicians to find specific information quickly.

For instance, when a technician encounters an unfamiliar problem, they can describe the issue in natural language, and the generative AI system can instantly pinpoint the relevant sections of the manual, suggest possible solutions, and even offer step-by-step guidance, all tailored to the technician’s current task. Furthermore, generative AI can continuously update and enrich technical manuals with feedback from technicians and evolving best practices. This ensures that the manuals remain a cutting-edge resource, dynamically adapting to the latest technologies and procedures.

In the face of rapidly advancing technology, the integration of artificial intelligence into ETO and MTO operations is paramount for those looking to lead continuous innovation and efficiency.

Embrace AI to enhance design precision, streamline production and operations, leveraging on all the company’s know how built all over time. Intellico Solutions has partnered with highly specialized manufacturing companies, and supported them in defining and implementing the “AI journey” also with advanced research programs (check: https://intellico.ai/blog/explainable-ai-for-manufacturing-and-rd-ai-regio-project/).

AI has transformed the workspace for designers and technical teams, empowering them to focus on complex tasks and innovate more sophisticated designs through human-machine collaboration. This synergy enhances creativity and precision, driving innovation and enabling the exploration of new frontiers in design and development.

Are you ready to take the first step towards transforming your business?

Do you want to learn more about the difference in predictive and generative AI? Check our article: https://intellico.ai/blog/embracing-the-future-an-introduction-to-ai-for-todays-business/

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