AI as a Game-Changer in Parts Identification: Real-World Success Stories from the Field
Artificial Intelligence (AI) is often hailed as a transformative technology, but what does it truly mean for industries like manufacturing,...
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Partium : Nov 11, 2019 5:27:26 AM
Unexpected machine downtime is costly and nerve-wracking. Regular, prescient servicing, condition monitoring, and predictive maintenance can help avoid this.
But what are the things that can go wrong in machine maintenance? How can companies improve their maintenance management?
Read about the top 5 machine maintenance fails and how you can avoid them!
Service personnel often have to spend time looking for additional information. Necessary data about the machine or a particular part, for example, documentation, delivery papers, parts descriptions, pictures, and illustrations, are not kept at a central location and are often even stored in a place away from the machine that is to be serviced.
The service technician or maintenance person is thus not spared the endless march from the control center to various offices to dig up all requisite information. This costs valuable time.
Everybody talks about digitalization and digitization, IoT, Industry 4.0, and Smart Factory, but hardly anyone lives it!
Even now, most logbooks are in 95% of cases not digitized. We’re talking about a physical notebook placed next to the machine. These are even often not filled in correctly or in keeping with protocol, the entries are often sketchy, the handwriting hard to read – or the entire notebook might even get lost. As a result, all information about incidents, abnormal measurements, and similar is pretty much lost to posterity.
Parts have to be replaced from time to time. But what if something goes wrong in the identification of the required part?
80% of all components can be identified with ease via an online portal such as Docware or with the use of on-site context information such as barcodes, stickers, designation markers, or similar. If this fails things get rather more cumbersome.
Parts will have to be accessed or even completely removed from the machine, colleagues are consulted and kept from getting on with their jobs, the machine manufacturer is contacted, and/or extensive research has to be carried out combing through delivery papers and a variety of internet forums. In the meantime, the machine is inoperative and delivers no output.
Let’s suppose the correct part is finally identified after a lot of running around, but it is not in stock. This leads to further expenses in terms of manpower as well as financially. The part has to be ordered, and the machine has to be temporarily fixed and started up again in order to prevent further downtime with the associated costs. Once the replacement part has been delivered, we’re back to square one: the machine has to be turned off, the part removed and replaced.
Permanent condition monitoring offers more security, more profitability, more flexibility, and more transparency. You can keep an eye on your machines 24/7 and continually evaluate their condition. This forms the perfect basis for predictive maintenance assessments and approaches. In turn, you will benefit from maximum machine run-time and lowered costs for the life of the machine.
How can mistakes in maintenance and service be avoided?
Good planning is half the job! With the help of digital assistant systems, these mistakes can be avoided.
Mobile solutions, such as Partium, bundles all important information for machine maintenance into one single mobile device. Article information, pictures of parts, and documentation are all displayed directly on the smartphone and are thus available right where it is needed: by the machine.
Additionally, it is possible to add maintenance checklists and notes and share them with the team. This allows for a comprehensive, watertight line of documentation of any machine incidents. Already available condition monitoring systems can also be connected directly to the mobile assistant solution.
The Partium technology for easy identification of machine components via smartphone prevents long-winded identification attempts as described under point 4 above. This recognition technology can ideally be combined with other features of a mobile machine assistant, such as stock tracking systems (e.g. ERP), which is not just possible but sensible to keep an eye on the availability of spare parts.
Are you trying to imagine what such a solution might look like for your company?
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