Artificial Intelligence does not need any introduction these days as we are in an era where it is going to take the centre stage. Machine Learning is going to be applied in calculative planning, sourcing & supply management of MRO items for large manufacturing organization. But first let’s figure out major challenges that, we as a procurement professional face in sourcing MRO items through conventional route –
• Substantial spend, spread across multiple plant/sites and categories
• Numerous unique SKUs, many of which are used only on certain equipment
• Unpredictable demand ― some 70% of MRO items turn less than once every two years
• A “just in case” mind frame, buying more than actually needed
• Large number of vendors, including local vendors at individual sites
• Spot buys ― unplanned purchases accounting for 50 percent of total MRO spend
All these factors lead companies to overstock, which when done again & again result in obsolescence. Technology in our era have contributed enormously & Machine Learning is one such solution which is ready to handle such issues meaningfully. It is prepared to address & eradicate major constraints for MRO category right from the source.
The ITES & eCommerce platform based companies are making strong associations with AI and machine learning. This AIML suites are looking to solve all existing problem with MRO category management with the help of data. Such IT enables take inputs from a wide variety of sensors, past maintenance data & schedules to accurately predict a breakdown and need of spares so that company can provide a preventive solution beforehand. Preventive maintenance will help organizations not to lose out due to down time of production. At the same time a greater safety stock need not be maintained as everything will fall in more or less planned schedule. It will save us from unnecessary inventory carrying cost & overstocking mind-set. Spot buying, in most of the time, will be enough to keep the plant in operational condition. This AIML looks to simplify the work of the procurement professionals in the future, with the smooth flow of operations and optimizing spends in MRO procurement. Together with, downtime improvement and gain in inclusive efficiency.
The future of MRO procurement lies not only in predictive maintenance but also in the ability to automate purchases & supply chain. Procurement teams will always be available with data on stocks and inventory, combining this data with predictive maintenance data, The IT suite can ascertain if a specific part’s stock needs to be replenished or not.
A syndicate between ML & AI would support in administering text search operation across gambit of unclassified data of the tail end voluminous MRO stocks to also predict near matches while the need arises for a specific item. This AIML combined search operations are generally more efficient as compared to predefined text base sear engines.
Once it signals for procurement of any item, The IT systems can handle the entire process, starting from need identification to supplier verification, getting quotations, analysing quotes to placing contract. The entire purchase cycle is in the realm of AIML automation enabled by a robust database where codification of item/parts are perfect for retrieving an outcome that is derived is a full proof solution.
Now, when it comes to automobile/engineering industry, a combination of integrated logistics & AIML driven procurement systems would eliminate the obvious possibility of generating obsolescence, when the safety stock can be reduced to a greater extend. AIML is likely to help the profit & variety trodden Automobile industry in reducing possible obsolescence & thus help on profitability.
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