Automatic data collection in the shop floor

For decades, we have seen unchanged the obstacle course of those who, stopwatch in hand, pen, paper or Excel spreadsheets, try to collect production data. If collecting data is already very complex and time-consuming, the analysis is even more. Can we really aim for efficiency in the means of production without optimizing the collection and processing of shop floor data? Tricky…

First of all, why collecting data ?

By collecting data from your shop floor, you will benefit from a flow of information that will allow you, after analysis, to access an ever higher level of understanding and knowledge. The nature and history of all this data will reveal productivity trends, and highlight the causes of non-OEE (losses).

This data allows you to accurately assess the various reasons for low OEE levels and will naturally help identify solutions to rectify them. With good data quality followed by good analysis, you will have the tools for quick and optimal decision making. Very often, managers realize that they have in front of them the equivalent of a “second factory” hidden by non-productivity, whether it comes from material, human, or organizational errors. The elimination (or reduction) of these errors allows to considerably increase the real production capacity of the shop floor.

By collecting data from the operators, we often observe an increase in their commitment. Having a clear vision of his productivity, the operator will be more involved in the realization of his missions, and will gain in performance.

The collection of this data also makes it possible to establish, a posteriori, a complete history of the downtime reasons which will be used as a basis for optimizing the production process by working on preventive maintenance for example. Better still, by comparing the data collected in real time with a known situation, it is possible to detect all types of symptoms revealing an imminent breakdown.

Finally, analyzing the data of your floor shop means above all being able to correct the errors that are detrimental to productivity, and thus respond more efficiently and more quickly to your customers’ expectations. Shorter lead times, better quality, higher confidence, these are the factors that guarantee you a remarkable satisfaction rate.

No more manual data collection

While the industry has become much more digital in the last few years, the collection of shop floor data has not kept pace. Old methods, manual declarations, unreliable data, waste of time, lack of regularity and punctuality, all of these are non-exhaustive reasons that could push all companies to go digital. But this is not the case. Too many factories want to implement digital data management, but find that existing solutions are often too expensive.

Astn’go is positioned as the LEAST EXPENSIVE solution, even though it is published by the leader in the MES market, Astrée Software.

Manual data collection is still widely used in industries. Not because they want to, but because of the simplicity and affordability of existing solutions. But there are many disadvantages when using this type of data collection. Manual data collection is still widely used in industries. Not because they want to, but because of the simplicity and affordability of existing solutions. But there are many disadvantages when using this kind of data collection.

• First, the “accuracy” of manually collected data is largely questionable. More often by habit than by negligence, an operator will at best know how to declare the stops he has observed, the scraps he has counted, and the reasons of these. However, there will be many undetected and yet very disabling micro-stops, unperceived undercuts, and a host of other causes of non-performance.
• Second, manual collection makes it impossible to update the data in real time. In other words, the period between when the data is collected and when the time it is available and studied is far too long to anticipate problems on the line. Often it is D+1, and it is too late. The manager can only observe without being able to act.
• Thirdly, these data are most of the time rendered on illegible and indigestible cards, making “accessibility” almost impossible. In fact, the data are present but cannot be processed and interpreted in a correct way and are often accumulated without ever being really studied.
• Finally, the “objectivity” of data reporting is not only complicated to verify, but also complicated to implement. Caught up in the momentum, if there is no incentive for the operator to fill in a data item (for example, a scrap reason), experience shows that he will not fill it in as he goes along. He will probably do so at the end of the shift, but with values that are often approximate.

In short, by manual collection, production information is often approximate and lacks objectivity. This work is an additional burden for the operator, who will not pay enough attention to their statements. Unfortunately, they are usually wrong and have to be checked and consolidated by the managers, which makes it an additional waste of time.

How to simplify collection by automating it ?

In order to increase data accuracy, veracity and availability, the use of Astn’go is essential. Indeed, by connecting your machines to Astn’go, you will have an omniscient view of your machines, thanks to accurate and objective data available in real time without effort.

By easily connecting the machine to Astn’go with the IIoT, all essential data will be accessible :

• Production downtime, breakdowns and even micro-downtime, where an operator will not take the time to note them all, quantify them and qualify them.
• The actual performance of your production lines or equipment.
• The OEE with its components and especially the reasons of losses.

In addition to the data collected in total autonomy, Astn’Go greatly simplifies the operator declarations required to provide additional information. With a few clicks, operators can declare scrap quantities and their cause on their terminal. When Astn’go detects a downtime, the operator can qualify the reason.

Plus, the use of Astn’go allows you to set up continuous improvement actions, useful to better communicate with your operators. Among these actions, the SIM (short interval management) will provide you with a niche of usable information in order to improve your production process.

You will use all your data acquisition sources, your environment (machines, IIoT, automats…) and your human capital (operators, managers, maintenance managers, team leaders…).