A manufacturing execution system (MES) is the foundation for operations in a modern factory or manufacturing plant — scheduling, managing and tracking each step of the production process for a particular job or work order.

With equipment and machines all connected, the system collects real-time production data as raw materials combine to form finished products. Operations staff can then use this information as it’s tracked by the system to increase uptime, reduce costs, and improve productivity, as well as create documentation to support regulatory compliance.

But why stop there? Today’s digital and cloud technologies can take the concept of an MES much further, connecting beyond the factory floor to create a system that positively impacts the entire business.

MES beyond the factory floor

Imagine how much more useful a MES can be if it also integrates with engineering, quality management, ERP and other corporate-wide systems, analyzing operational data in the context of a broader set of real-time and historical datasets to support business and financial decisions. The key to predictive and proactive decision-making lies in the quality and quantity of the data collected — and more important, how that data is correlated and analyzed. Integrating MES with ERP and other corporate systems such as HR and finance, as well as connecting out to customers and suppliers, makes it possible to collect data across the corporate infrastructure and the supply chain. This yields joined-up data analytics that has far more value to the business.

For example, by integrating with inventory and quality management systems, it becomes possible to ensure that inventory deemed suspect during production of a specific job isn’t used in the next operation. A traditional job-specific MES doesn’t have this intelligence. There are many other persuasive examples. Let’s say a machine on the factory floor goes down. Integration with finance and sales identifies which orders are affected by downtime, correlates that with customer data and assesses the financial implications. Customers are notified in advance and orders prioritized — minimizing the impact to the business.

Another use case is the ability to analyze historical performance data to look at how the same machine is performing over time. Is it slowing down at a particular time during a specific shift? By looking at machine performance in the context of other sensor data including temperature, humidity, vibration, and time of day, operators can determine, for example, if a machine runs slower at a given humidity level or time of day, and then take steps to improve output.

Businesses with multiple manufacturing sites can compare the performance of multiple plants, analyzing data that is used to improve the performance of a poorly-performing operation. The data collected can also be leveraged for long-term bench-marking, proactive maintenance, and to evaluate shop floor and employee performance.

Extending connections out to partners and suppliers as part of that ecosystem makes it easy to communicate shortages in raw materials at the supplier to the manufacturer, enabling the use of alternate suppliers to meet customer demand.

MES in the cloud?

Most traditional MES’s are on-premise solutions, but cloud-based systems are becoming more common — and with good reason.  A SaaS (software-as-a-service) solution may reduce the initial investment while also minimizing maintenance and support costs over time. Back-up is automated and no on-site training is required.  Cloud implementations also provide seamless on-demand scalability as business needs grow predictably — or unpredictably. Finally, a cloud-native system is inherently designed to be connected, and so integrates much more simply with other systems.

Being designed as a cloud-based MES system from the outset is important for a couple reasons. First, a cloud-native MES hasn’t been retrofitted from an on-premise solution to create a cloud product with less functionality or different features. Secondly, many of the potential issues of security, scalability and so on that might arise with a solution that’s new to the cloud have already been resolved in a secure multi-tenant system that’s proven itself at numerous customer sites worldwide.

Operating MES as a SaaS application allows manufacturing companies to focus on their core business — leaving IT in the hands of IT experts.

The big picture

At Plex, we’ve put both of these principles together, in a cloud-native MES that extends the scope of a traditional system, offering benefits that go beyond an individual job on the factory floor. The cloud-based implementation extends the scalability of the system, offering limitless growth with a ‘pay-as-you-grow’ SaaS-based pricing model. A tightly integrated closed-loop system with enterprise-wide visibility provides a wealth of data that enables our customers to drive innovation, improve quality and performance, and provide better service to their own customers.