Artificial Intelligence: The Future of Searching for Spare Parts in the Maintenance of Large Industrial Enterprises
Artificial Intelligence: The Future of Searching for Spare Parts in the Maintenance of Large Industrial Enterprises
Patrick Schneider, VP Enterprise Solutions at Partium
Posted 3/21/2024
In large industrial enterprises, maintenance plays a critical role in guaranteeing continuous, efficient operations. A key aspect of this area is the search for spare parts.
This process is traditionally associated with challenges including time intensity, high error rates, and inventory management. Introducing artificial intelligence (AI) into this environment brings with it a transformative wave that has the potential to revolutionize the search for spare parts.
Not only are the processes for identifying spare parts accelerated by implementing AI technologies such as machine learning and image recognition, they are also made much more precise. This development greatly increases the efficiency of the search for spare parts while reducing inventory costs at the same time. Find out exactly how it works in this article.
Challenges in the Traditional Search for Spare Parts
Time-consuming manual search and identification processes
One of the biggest bottlenecks in the search for spare parts in industrial enterprises is the high amount of time required for manual search and identification processes. This section highlights the various aspects and implications of this challenge:
Manual data entry and query: In many cases, the search for spare parts is based on manual systems that require data to be entered and queried in databases. Not only is this process time-consuming, it’s also susceptible to human error.
Complexity of identifying parts: Correctly identifying spare parts is difficult, especially with specific, uncommon, or obsolete components. Manually going through catalogs and databases to find the right part is often a lengthy and laborious process.
Reliance on expert knowledge: In many cases, quickly identifying spare parts depends on employees with special knowledge or experience. This leads to relying on individuals, which can then lead to delays if they are absent.
Loss of time due to physical inventory verification: If inventory data is not up-to-date or accurate, employees may need to physically search the warehouse to find the part they need. This is an especially time-consuming process that makes other optimizations practically impossible.
Storage costs, especially for rarely used or obsolete parts
An essential aspect that influences the cost-effectiveness of maintenance in large industrial enterprises is storage costs, especially for rarely used or obsolete spare parts. These costs not only include the physical storage space, but the associated administration and maintenance costs too. So far, though, there has been no way around it!
AI in the Search for Spare Parts: Examples of Use, Advantages, and Solutions
Using artificial intelligence (AI) now (2023/2024) offers an array of possibilities to improve the search for spare parts in industrial enterprises:
Improved day-to-day searching for spare parts
Use of image recognition: Employees can take photos of the spare parts required and upload these images to the search system directly. AI-supported image recognition identifies the part more quickly, significantly reducing time spent searching.
Integration with text search: Large language models (LLM), image searches, and descriptions are combined in one search, resulting in faster, more accurate identification.
Re-digitization of unlabeled spare parts inventories:
Recording and cataloging: AI systems can help to record and catalog unlabeled or poorly documented spare parts inventories. These inventories can be efficiently digitized and systematically arranged by analyzing images and text data.
Reading PDFs and other document formats:
Data extraction: LLMs (large language models) are able to browse complex documents, such as PDFs, and extract relevant information about spare parts. This includes technical specifications, manufacturer information, and instructions for use, which are important for maintenance.
Experts need to check the results but no longer need to search for them themselves.
Optimizing warehouses:
Efficient warehouse organization: Warehouses can be optimized by identifying spare parts using image recognition. Difficult-to-describe spare parts can be completely packed, stacked, and organized to “wait” until they are needed. They can even be outsourced, making room for fast-moving products.
Implementing AI in the search for spare parts offers significant advantages for large industrial enterprises. The search process for spare parts is significantly accelerated and simplified by using technologies such as image recognition and large language models, while reducing errors and complexity at the same time. This increase in efficiency not only leads to faster, more precise identification of spare parts, but also contributes to reducing overall costs (operation and storage).
Conclusion
But what specific AI solutions are currently available for searching for spare parts?
One established AI solution to searching for spare parts already exists: Partium. The web-based application can be used on smartphones, tablets, or a desktop.
Partium is used in lots of industrial enterprises around the world and helps users accelerate and optimize processes involved in searching for and sourcing spare parts. Some of the best-known clients in the maintenance sector include Deutsche Bahn (German Railways), ÖBB, and Vienna Energy.
Patrick Schneider
Patrick Schneider is VP Enterprise Solutions at Partium. Patrick has managed many projects related to spare parts identification and spare parts search in the maintenance, after-sales, and service field.
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There are three significant trends that are causes of concern for the real estate industry and large enterprises globally in 2023. While most of these are common problems real estate owners and operators encounter, they threaten the very existence of such businesses during economic downturns. How do they keep themselves afloat and profitable? Real estate owners and operators are turning to technology solutions to find ways to curb spend and improve bottomline in 2023 and beyond.Â
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So, let’s start with my hypothesis that TPM drives all three elements of OEE, namely: machine availability, speed and quality.  Traditionally as a Maintenance Leader and then Operational Excellence (OpEx) leader in paper mills and packaging manufacturing plants, my focus was all about machine availability. If the machine was running, it belonged to operations and I could focus on writing PMs, improving RCM and building Gantt charts for my next planned outage. However, experience has taught me that just focusing on availability is missing 2/3 of the opportunity to improve business by not embracing the entire OEE metric through maintenance action.Â
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Never has there been a greater responsibility for every business to maximise its efforts to drive to net zero. Correct machine maintenance coupled with Lean processes (once just the domain of operations) is now proving to be a force multiplier across maintenance and engineering in the drive to net zero.Â
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Aging Facilities in the US are entering the Renovation Phase. The average facility age is 50 years old. For many facility managers, the risks and costs associated with mid to old-age facilities is new territory. Aging facilities that are reaching 40 to 60 years old are facing a new stage of capital investment that many are not prepared for.
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ISO 15243:2017 is a standard that classifies different modes of failure occurring in service for rolling bearings made of standard bearing steels. For each failure mode, it defines and describes the characteristics, appearance, and possible root causes of failure. The standard aims to assist in the identification of failure modes based on features that are visible on the rolling elements, raceways, and other functional surfaces.Â
This is the 2nd installment of an 8-step process to enable you on your journey to Operational Excellence. Once you have identified areas for improvement you must develop and implement your improvement plan.
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Making the decision to shift maintenance operations from manual methods to software is a huge step. The process can also be overwhelming and confusing for many professionals especially if you have had little to no experience with maintenance and asset management software in the past.
Making the decision to shift maintenance operations from manual methods to software is a huge step. The process can also be overwhelming and confusing for many professionals especially if you have had little to no experience with maintenance and asset management software in the past.
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In the manufacturing industry, having the right spare parts in the right place when you need them is key to making sure your facility is operating efficiently. Developing technology such as vision picking, predictive analytics, and more are rapidly transforming the way spare parts management programs function across industries. Storeroom and spare parts organization is typically an area where we see opportunities for improvement in many organizations. What does a good storeroom look like? What are best practices in spare parts management? How can we use new technology and trends to organize and optimize the storeroom?
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The way your asset management system is set up and used, particularly the asset register, will play a major role in determining the ability of your maintenance organization to effectively operate. Data must be gathered at the appropriate level to allow it to be used, then summarized and reported on if necessary.
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Do we really have to talk about this? Maximo has had Inventory Management functionality for many, many years. Not only is the function present, but it interconnects to many of the other Maximo modules such as Purchasing and Work Management.
Do we really have to talk about this? Maximo has had Inventory Management functionality for many, many years. Not only is the function present, but it interconnects to many of the other Maximo modules such as Purchasing and Work Management.
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In a race to differentiate, FMs are turning to technology to optimize asset management, workflow automation, auditing and reporting, energy management, and many other O&M functions. However, there are several roadblocks that hinder the optimal use of technology and the smooth expansion of FM operations across client portfolios. Let's closely examine these common tech roadblocks and explore effective strategies to navigate them.
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In the fast-paced world of manufacturing, the integration of production automation has become a transformative force, reshaping industries, and redefining the way businesses operate. One of the key areas where automation demonstrates its prowess is in enhancing reliability and maintenance processes. By leveraging advanced technologies, artificial intelligence, and smart systems, production automation is ushering in a new era of efficiency, cost-effectiveness, and minimized downtime.
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