Published: August 27, 2024

Lynn Loughmiller, Software Engineering Manager at DELMIAWorks, takes a closer look at how production and process manufacturing monitoring systems improve performance in manufacturing

Manufacturers are under more pressure than ever to deliver high-quality products quickly, yet a multitude of variables can disrupt the best-laid production plan – from machine and human errors to unexpected downtime and material shortages. Real-time production monitoring and process monitoring work together to provide instant insights that enable manufacturers to quickly identify and resolve potential issues before they impact the ability to meet customer commitments.

Production monitoring vs. process monitoring

Both production monitoring and process monitoring rely on real-time data from smart machines and sensors on equipment, but they are actually two different parts of a recipe for gaining insight into what is happening in manufacturing at any given moment.

Production tracking is similar to the top of a recipe that lists the ingredients, with parts and materials at the center. It tracks the production of parts, starting with the raw material used, such as a plastic pellet or a sheet of metal, counting the parts as they are made, tracking their movement into inventory, and recording the associated scrap.

Process monitoring is like the part of a recipe that shows how things are done. It focuses on conditions that affect processes, such as whether machine cycle times, temperatures, currents, and lubricant levels are within specified parameters.

Five ways production and process monitoring can improve your operations

When real-time data from manufacturing monitoring systems is shared with a manufacturer’s enterprise resource planning (ERP), manufacturing execution system (MES), and other related software, the information can automatically trigger actions and support decision-making across the enterprise. Here are five examples of how production monitoring and process monitoring can be used—either individually or in combination—to improve operations.

1. Inventory management – ​​Production monitoring plays an essential role in ensuring there are enough raw materials in stock, as it tracks machine cycle times, which can be used to predict when a manufacturer will run out of a particular material. Production monitoring can also capture when more scrap is being produced than planned, indicating not only a potential production problem, but also that a raw material needs to be reordered sooner. An MES that stores real-time production and process monitoring data can feed this information into an ERP system’s purchasing model, which then automatically generates material orders, ensuring material availability to support production while improving utilization.

2. Warehouse management – ​​Production monitoring of machine cycles can help manufacturers deliver raw materials to the right machine when needed and avoid downtime. Real-time data from the integrated MES system is fed into warehouse management software, which uses this information to automatically instruct forklift drivers or other workers where to deliver raw materials for use on a specific machine.

3. Quality control and compliance – Manufacturers can use both monitoring approaches to ensure quality. For example, production monitoring in conjunction with a vision system can trigger a programmable logic controller (PLC) to detect defective parts. Likewise, process monitoring can detect factors such as machine temperatures falling below acceptable parameters. In both cases, the data can be used to automatically trigger automatic rejection of affected parts. In addition, process monitoring data fed into ERP and quality management systems can simplify compliance and certification by automatically verifying and documenting that parts were manufactured according to specified parameters.

4. Preventive Maintenance – The two types of monitoring can be used to indicate when machine maintenance needs to be performed. For example, production monitoring may detect that a particular machine has just produced 300,000 parts across multiple work orders and trigger a maintenance order for that machine. On the other hand, if process monitoring captures the cycle counts of a machine, the number of cycles or the length of the cycles may indicate wear or a problem with the machine, which in turn triggers an alert to schedule maintenance at a time that will minimally impact production.

5. Automatic Scheduling – In cases where a machine is down, the part still needs to be produced. Production monitoring can show how long a work order will take. The data can then be shared with the automatic scheduling feature in the MES system. If downtime is minimal, automatic scheduling can simply update the current machine’s production timing. However, if downtime impacts delivery to the customer, automatic scheduling can reassign part production to another machine.

Looking to the future – harnessing the power of AI

The uses of production and process monitoring will continue to grow as manufacturing monitoring systems leverage advances in generative artificial intelligence (AI). Both forms of monitoring have made it possible to build vast historical data sets of machines on the shop floor that can be used to create predictive models. When these models are then matched with real-time data in ERP, MES, and other manufacturing applications, much more accurate predictions can be made about what is happening or will happen on the shop floor.

The resulting AI-powered insights will provide a strategic resource for training engineers and operators to learn how effectively their product recipe is performing. In addition, these AI-powered analytics and forecasts will become a critical factor in enabling manufacturers to make timely and informed decisions across their entire business. And that’s a recipe for success.

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