AI-supported solutions for fast and precise spare parts searches in maintenance

As digitalization progresses and Industry 4.0 concepts are implemented, the field of industrial maintenance has changed significantly. Innovative technologies, in particular artificial intelligence (AI), play a decisive role in optimizing operational processes. It enables an increase in efficiency and productivity and can be used in many situations. In this paper, we would like to focus on a specific use case: revolutionizing spare parts search and management with AI.

AI-based spare parts search - an overview

The AI spare parts search uses advanced algorithms and machine learning to simplify and speed up the identification and procurement of spare parts. When a technician captures a desired part of a system, whether by photo or text input, the innovative AI software springs into action. It analyzes the image, performs a visual and semantic comparison with the stored spare part information from the database and precisely locates the required spare part. The results are displayed directly in the app, where the technician can request additional support from the spare parts service or warehouse team if required. This integration makes it possible to confirm the result of the search for more complex spare parts or to initiate a more in-depth search. In addition, the app can be easily integrated into existing systems such as Enterprise Asset Manamagent (EAM), enabling efficient management and procurement of spare parts within the company infrastructure.

Types of AI-based spare parts search

The integration of various search modalities, including image and text search functions, into the EAM system allows users to effectively identify spare parts using photos, graphical representations or detailed descriptions. These functions add a visual component to the EAM system’s capabilities, which significantly speeds up and simplifies the identification of spare parts. Furthermore, advanced filter options by category, location or specific parts lists support the search by refining the results and facilitating access to the required parts. In addition, the interpretation and understanding of the context of queries is enabled by the integration of semantic search technologies into the EAM system. Thanks to this technology, concepts within the parts databases can be matched even if there are no direct matches.

Collaborative spare parts search in teams

Another advantage is the promotion of collaborative spare parts searches in teams through the introduction of an agent portal in the EAM system. This portal facilitates direct communication and collaboration between technicians, spare parts services and warehouse staff. Requests can be seamlessly routed to experts who can assist with additional information or confirmations, while a dashboard with notification functions keeps everyone involved informed about the status of requests. This approach not only improves the speed and efficiency of spare parts ordering, but also increases overall productivity.

Spare part analysis

The integration of advanced analysis tools into the EAM system makes it possible to precisely analyze the search behavior of users. By taking a close look at the most frequently searched parts and machines as well as the overall efficiency of the parts search, companies can optimize their spare parts portfolio in a targeted manner. This not only leads to increased purchasing efficiency, but also makes a significant contribution to improving maintenance processes.

Advantages of the AI-based spare parts search

  1. Increased process efficiency: AI technology
    significantly accelerates parts identification and therefore contributes to
    higher overall productivity in maintenance management.

  2.     . Minimized incorrect orders: Our AI-based search significantly reduces incorrect orders by identifying even spare parts that are stored in the database without a picture.

  3.           Cost-optimized warehousing: By using spare parts analytics, we optimize your warehousing, resulting in significant cost savings.

AI-based spare parts search and EAM

The integration of AI into EAM systems to optimize the search for spare parts is a revolutionary advance in maintenance logistics. Our product, Insight Mobile, plays a central role in this process by serving as a mobile platform that seamlessly connects with Partium technology and EAM systems. It enables technicians to access the necessary information directly on site, significantly speeding up the identification and procurement of spare parts. Insight Mobile takes efficiency, accuracy and collaboration in maintenance processes to a new level and helps companies maximize their operational performance.