Starting point: lots of data, little actionable value
When we refer to industrial digitization, we tend to think of smart factories, where all processes are interconnected and provide a huge amount of data that we must somehow be able to exploit to improve efficiency and productivity.
However, currently in the automotive sector we are still far from being able to take advantage of the full potential of new technologies. Most of the time quality control is done manually, which limits the amount of data we are able to collect, and it is “archived” locally so that it cannot be correlated with data from other machines, parts or measurements, nor with external variables that can affect the measurements, such as temperature, humidity, etc.
Quality walls and operational overloads
In short, we accumulate data, but we do not take full advantage of it. For example, if an OEM detects (a posteriori) that a process is starting to get out of control, it imposes a quality wall on its supplier, and the painful and costly tasks of continuous and intensive quality controls begin until, at some point, the process is back under control.
“We are convinced that another way of doing things is possible, and avoid inefficiencies and cost overruns by applying intelligent solutions for data management, transforming dimensional quality control into a comprehensive (and digital) service for the capture, analysis and management of quality control data generated in real time, to anticipate the occurrence of incidents, and apply preventive and even predictive criteria based on data analysis.”
From local to cloud: The same data for everyone
And that data does not have to be archived in a local computer, but can be in the cloud available to both the customer and the supplier, accessible at all times, so that they can share the results of the analysis and make joint decisions for the benefit of operations and their efficiency, in a process of continuous improvement and constant learning.
It should not be forgotten that Industry 4.0 is an industrial paradigm shift that also affects people, and where technological tools and process innovation are a means and not an end, so it is not only a matter of process automation, robotization of production, massive data analysis tools and interaction between machines.
And this cultural change also affects the relationships between suppliers and customers, which must be developed in a collaborative and open environment, sharing information for the benefit of both. Interconnecting capture, analysis and action – in a shared environment – shortens time, avoids rework and reduces the cost of non-quality. Deciding earlier is always cheaper than inspecting later.
“Let’s build bridges by sharing information to break down the walls of (non)quality and unnecessary costs.”
