Advanced MES & Analytics: From Machinery to the brain of the Enterprise

The advanced versions of these systems make factories that manufacture sheet metal parts, tubes, and metal profiles into smart factories by gathering data and analysing them. The program has not lost its core value, but has rather been enriched, making it into the timing belt, working as the transmitter and executor of the orders coming from the brain of the plant, powered by data analytics.

Thus, combined with data analytics, MES has become Advanced MES and is the basis of a digital factory and smart production, because it compiles all the data coming from machines and processes automatically, in real time. These data are stored on the Cloud, where current data are combined with historical data. They are all analysed with artificial intelligence in general and machine learning in particular. With algorithms, optimized work schedules can be provided for each line as well as responses to different scenarios, facilitating and streamlining decision-making.

In addition to planning production resources for the medium term, it will show a big picture view – within a single plant or several – which will allow the operator to properly balance the workload. Data is also obtained on the status of machines, orders, stock capacity, and delivery times. These are data that when looked at fully offer the best solutions to any eventuality. Along this line, for example, Advanced MES provides warnings about different incidents such as problems with stock, workload readjustments, alerts of new orders, and its forecasting capabilities even anticipate purchasing demand.

There are two key aspects of the Advanced MES: visibility and scheduling.

-  It provides visibility with machine and order status, material needs, and the maintenance calendar. Process analytics will allow bottlenecks to be located at any time and reacted to so as to streamline the flow of production.

-  Scheduling through Gantt charts with automated production proposals. Simulation scenarios to assess the impact new orders will have on production are also possible. The data will allow for more flexible scheduling, and workloads can be balanced in real time simply by dragging production orders from one workplace to another.

Advanced analytics

Every day decisions are made; regardless of whether they are operational or strategic, the important thing about them is the data involved, because the quality of said data will ensure that the actions approved are the most appropriate. Gathering this data is no easy task if it is done manually. As mentioned above, this was and continues to be the way said data are obtained, which not only causes enormous delays, but also increases the chances that the data quality is suboptimal.

Data quality is measured by accuracy and timeliness. If it does not reflect the situation on the ground, we run the risk of making bad decisions. That’s why the right technological tools must be available to be able to automatically gather data in real time, offering the speed required by the digital era. These are tools that in addition to gathering data, cleanse and process them. The basic objective is to reduce the number of machines and warehouses and get more out of people, achieving greater capacity and, as a result, a better flow of production, while eliminating inefficiencies and optimizing manufacturing processes.

In short, advanced manufacturing allows processes to be streamlined, time and costs to be saved, and plant productivity to be increased. This is unavoidable in Industry 4.0, a new stage that is already here, not something yet to come. The sooner we become part of the change, the better our position will be to compete in the digital era. Let’s adapt our factories and make them into smart factories.