Automated welding usually involves the production of large order volumes. The data generated from the welding process are also used as a basis for optimisation. But how does this work in manual welding? Can data also be recorded, collected and evaluated in manual production in order to optimise processes? The answer is: yes, even so-called big data.
Big data means very large amounts of data that can no longer be evaluated by humans within a short period of time and that computer programmes have to take over. But where does this data come from in manual welding? The answer is: from the welding process.
On average, a welder welds between 0.3 m and 0.6 m per minute. If you want to measure the electrical parameters and assume 1,000 measurements per second – this corresponds to one kilohertz – you will get up to 1 million data points for a 1 m weld seam. It is impossible to evaluate these without appropriate computer programmes.
How is big data determined during manual welding?
Welding equipment or power sources provide these large amounts of data. Or rather, the welding data management system, which is integrated in most modern power sources today. This is used to record measurement data such as the arc time, the current consumed or data on wire and shielding gas consumption. If you want to know how many welds were welded in one shift and how high the energy consumption was, you can use the corresponding measurement data from your welding data management system for the calculation.
Reveal optimisation potentials
Comparisons of the collected actual data with other welding workplaces or other shifts will irrevocably reveal differences. For example, if more welds are made at a manual workplace, this may be due to the skill of the welding operator. But it can also have other reasons.
The conditions around the workplace can be a trigger for more or less productivity. Maybe the welder has to cover a longer distance to the individual work materials? Are the workplaces differently equipped? Perhaps different welding torches are used for welding the same component? Even small differences in weight and handling can influence the active working time because the body tires or overloads more quickly. A comparison of the data can thus reveal valuable optimisation potential.
If the consumption data for energy, wire and gas are known, productivity data can also be derived from them. With newer welding machines for manual welding, even quality data can be determined.
This makes it clear that big data already plays an important role in manual welding. You are also welcome to watch the video on this topic:
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