Production monitoring of machine cycles can help manufacturers get raw materials to the correct machine when they ’ re needed and avoid downtime .
more scrap than projected is being produced , signaling not just a potential production problem but also the need to re-order a raw material sooner . An MES storing real-time production and process monitoring data can feed this information into the purchasing model of an ERP system , which then auto-generates purchase orders for materials , ensuring the availability of materials to support production runs while also improving utilization .
2 . Warehouse Management – Production monitoring of machine cycles can help manufacturers get raw materials to the correct machine when they ’ re needed and avoid downtime . Here , real-time data in the integrated MES system is fed into warehouse management software , which uses this information to automatically direct forklift operators or other workers on where to deliver raw materials for use at a specific machine .
3 . Quality Control and Compliance – Manufacturers can use both monitoring approaches to ensure quality . For example ,
production monitoring together with a vision system can trigger a programmable logic controller ( PLC ) to detect bad parts . Similarly , process monitoring can capture factors , such as machine temperatures falling below acceptable parameters . In either case , the data can be used to automatically trigger automatic rejections of the affected parts . Additionally , process monitoring data fed into ERP and quality management systems can simplify compliance and certification by automatically verifying and documenting that parts were made in accordance with specified parameters .
4 . Preventative Maintenance – The two types of monitoring can be used to indicate when to perform machine maintenance . For example , production monitoring can capture that a particular machine has just produced 300,000 parts over several work orders and trigger a maintenance work order for that machine . On the other hand , when process monitoring captures a machine ’ s cycle counts , the number of cycles or length of cycles can indicate wear or a problem with the machine , again triggering an alert to schedule maintenance at a time that minimally impacts production .
5 . Auto-Scheduling – In those cases when a machine goes down , the part still needs to be produced . Production monitoring can show how long a work order is going to take . The data can then be shared with auto-scheduling functionality in the MES system . If the downtime is minimal , auto-scheduling may simply update production timing on the current machine . However , if the downtime will impact delivery to the customer , autoscheduling can re-assign the part production to another machine .
Looking Ahead – Adding the Power of AI
The applications of production and process monitoring will continue to grow as manufacturing monitoring systems take advantage of advances in generative artificial intelligence ( AI ). Both forms of monitoring have made it possible to build huge historian stockpiles of data from machines on the shop floor , which can be used to build predictive models . Then , when mapped against real-time data in ERP , MES , and other manufacturing applications , these models will make it possible to forecast what is or will happen on the shop floor with much greater accuracy .
The resulting AI-driven insights will provide a strategic resource for training engineers and operators on how effectively their product “ recipe ” is working . Moreover , these AI-powered analytics and forecasts will become a critical factor in empowering manufacturers to make timely , highly informed decisions across their business . And that ’ s a recipe for success .
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