The data acquisition has become a central element to boost the quality and efficiency of production. And an area where this collection can occur is with robots. However, all too often, factory managers can not see the potential of robots to obtain useful information and help automate operations.
Why focus on robots?
Robots are seeing greater use as the benefits of automation increase. Decreasing costs, improved performance and simpler programming make robots more attractive. When manufacturing equipment implements these machines, it is quite easy to improve data acquisition and add test and inspection stations. The most basic data acquisition comes from the robot itself. You can control the production of parts and the consumption of inventory, indicating to the systems how many elements were used in a given period of time. This information also comes with timestamps, so it is easy to store information about when each component was handled. Such capacity is particularly important in regulated environments, where easy access to historical data in transfers can be an important factor when products must be withdrawn from the market.
Auxiliary equipment used with robots can also bring a large amount of data. Visual sensors, clamps and other gears have the potential to provide some additional data.
A structure for the success of data acquisition
It is often quite simple to add inspection stations to the robotic work cells. The cameras used to guide robotic movement can also be used to examine components. The presence of characteristics of key components, as well as measurements, are some of the most common types of controls. These visual inspections can often be performed while moving or manipulating the parts to maintain high speeds of operation.
In addition, the sensors can be easily added to verify other parameters. When these inspection stations are installed in work cells, quality controls can be increased with minimal impact on performance. The additional monitoring can bring important improvements. It is easier to detect trends when more parts are checked, so changes can be made before the defective parts are made.
These quality controls can also help solve problems with customers. For example, a company that has proof that the parts meet the requirements when they left the facility can easily resolve a dispute in which the shipper may have damaged the goods.
These improvements come from the analysis of data points in real time. But great benefits are obtained when large amounts of data acquisition are extracted. Data mining allows operators and maintenance technicians to observe many different parameters over long periods.
When recurring problems arise with the production team, the file data can be examined so that analysts can understand what happened before a failure occurred. This information can be used to prevent future failures. When the parameters that precede the faults are detected, maintenance can be performed before a failure causes an unplanned shutdown, improving the overall efficiency of the plant.
Trends in the management of this data
At present, much of this analysis will be based on the knowledge of engineers, technicians and even equipment suppliers. But in the near future, deep learning systems are likely to analyze the huge volumes of data collected. Some form of artificial intelligence may be needed when companies want to analyze equipment used in plants at many different global facilities. Transforming data from many high-performance machines into useful data may be beyond the analytical reach of most humans. However, it may be a while before conservative manufacturing companies rely on machine learning systems.
While that is a long-term problem, the question of where to store all this data is an important decision today. Often, a storage hierarchy can be an effective solution. The basic data can be stored in the robot controller. When this limited capacity is exceeded, the oldest data can be transferred to the company’s manufacturing execution system (MES). There, you can store large volumes of data for your corporate review. When local storage capacities are exceeded, companies usually turn to the cloud. These data centers will store the amount of data that the company wants to pay. Cloud services are especially important for companies that want to store data from multiple facilities.
big investment
While it might seem that adding robots and inspection stations is a big investment, many observers explain that the benefits of installing more quality inspections often outweigh the costs. If a supplier sends defective parts to a major customer, then that customer can demand a 100% inspection of those products until the quality levels return to normal. The cost of some cameras and sensors is well below the expenses associated with a withdrawal effort and quickly adds inspection practices in response to a customer’s problem.
Companies that have robots installed may be surprised to discover how effective it can be to add sensors and perform more inspections. Those who have not yet implemented these automata are often glad to know that there can be substantial benefits with robotic systems beyond the speed and precision of automation that are the main attractions for many facilities. When robots are integrated into the manufacturing processes together with the applicable sensors, users have the opportunity to collect much more information, which provides significant improvements in their manufacturing operations.