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The Factory-X consortium ’ s use cases are diverse . They range from boosting transparency and consistency of production equipment-related information to traceability of machine components to simplifying production setup and control . Let ’ s take a closer look at one of those use cases : Under the banner of ‘ collaborative information logistics ,’ it focuses on tackling the inefficiencies that emerge because of the lack of standards in how companies exchange data about manufacturing assets .
Making life easier for shop-floor personnel
Consider the plight of the maintenance manager on a modern production line . The line involves an array of material-handling equipment , fabrication and processing machines , assembly equipment , and quality-control machines from different vendors . Each machine has different sets and formats of documentation , maintenance instructions , and spare-part information , all on different websites . In addition , there ’ s the matter of managing and scheduling the updates for all the different software releases for many machines . Keeping track of it all via vendor websites takes a lot of the maintenance manager ’ s time and effort .
Two dynamics further complicate the challenge . First , shop-floor equipment is becoming increasingly complex and , often , more integrated with other equipment on the line . That integration is a good thing . But that complexity does make it harder to reprogram , reconfigure , and maintain , and repair production assets , and integration boosts the odds of a problem with one machine cascading to others . Second , an aging manufacturing workforce has seasoned talent retiring in larger numbers , putting complicated and consequential maintenance and repair in less-experienced hands .
Sharing data boosts production efficiency
The idea behind Factory-X ’ s collaborative information logistics and several other use cases is to enable the exchange of information about production assets using common data standards to enable communication between component / material producers , package-unit makers , those running the package units in production , and outside service providers repairing and maintaining the units – across any platform . It boils down to improving production fundamentals to minimize downtime and keep factories running more efficiently .
Doing so will let users such as our maintenance manager access specific , updated data on assets at the serial-number level in one place . That means they ’ ll be able to avoid the time and effort of searching for , confirming , tagging , and otherwise dealing with scattered , potentially dated information about all the different machines on the production floor . The maintenance manager , operators , and others will have current , accurate information on the documentation , digital nameplate , precise components , technical components , and spare parts of a machine , as well as specific maintenance or integration needs that each production asset needs to run effectively on its own and in harmony with other machines up and down the line .
Further , AI can improve the efficiency and effectiveness of the maintenance manager ’ s routine tasks . For example , the system can learn which maintenance activities have been conducted in response to identified issues and can suggest maintenance activities , parts , and special tools required as the maintenance manager creates a new maintenance order .
Production-asset-chain integration is happening
Many individual business supply network platforms already share production-asset-
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