June/July 2024 www.pwemag.co.uk Plant & Works Engineering | 39 Manufacturing Monitoring Systems Special Focus be produced. Production monitoring can show how long a work order is going to take. The data can then be shared with autoscheduling 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 AIpowered 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. 1. Inventory Management – Production monitoring plays an integral role in ensuring that enough raw materials are in inventory because it tracks machine cycle times, which can be used to predict when a manufacturer will run out of a specific material. Production monitoring can also capture when 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 autogenerates 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
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