29 Mar
2019

Make Better Decisions with Machine Monitoring

Manufacturers can make better decisions in their smart factory with real-time machine monitoring, allowing them to quickly react to downtime, performance gaps and fluctuating customer demand

Smart Factory
IIoT
Types de déchets dans la production allégée : Défauts Déchets

A paper-base data collection system or lack of a data collection system is a serious handicap for manufacturers who want to reduce costs, maximize profitability and remain competitive.


Not knowing what really happens in your factory can seriously hinder your productivity and your waste. With the capabilities of sensor data collection systems as well as their ease of access to, there are fewer barriers to implementing an automated data collection system and a factory dashboard where the data is displayed in real time. 

Reducing downtime with machine monitoring

Providing basic real time information, such as downtime on your factory dashboard or smart phone, can have a significant impact on uptime. Employees will react promptly as red signals appear on the screens and redouble efforts to solve the problem and return to the desired state. The greater the amount of data that is collected, the more patterns will be able to identified and downtimes will be able to be prevented.

 

 

Improving quality with machine learning

By tracking work cells and production lines all while establishing which ones are consistently above or below an acceptable level of quality, it is possible to quickly identify and correct unproductive activities. Continuous monitoring all along the production process contributes to an early detection of quality issues, increasing efficiency and reducing the costs of solutions that go beyond manual quality controls.

Powered by a sufficient amount of data and supported by the appropriate analytical tools, machine learning can indeed predict problems pertaining to quality. For example, given a recurring situation, machine learning will able to identify this type of situation before it occurs, allowing employees to act accordingly. Detecting a problem before it even happens is a revolutionary approach to quality control. Trend recognition is potentially one of the greatest benefits of an IoT solution and a way to get most out of your data.

 

Plan with greater precision

Gathering real production data, using machine monitoring gives you more accurate data when you plan and schedule. Sensor-based data is more consistent as it is free from variations caused by data collection from multiple operators each using their own personal interpretation in their work. If an abnormal change in the time required to produce an article is detected, the analysis tools can isolate this anomaly and associate it with the relevant data so that the cause of this underperformance is analyzed and corrected.

 

 

Improve stock accuracy

It comes as no surprise that automatic metering systems for finished products are much less likely to be inaccurate than manual counting systems. In addition, thanks to real-time information, no one is waiting for the end of a manual count. Actual stock levels can be known at any time and at any stage of the production cycle. With accurate inventories, a company can confidently determine its capabilities and thus consider an increase in the order fulfillment rate.

Planning machine maintenance with machine monitoring

If a machine isn’t working adequately, do you stop the entire production line to solve the issue, or do you try to tinker a repair without stopping the line so that production continues at all costs? Here’s a strategic decision that does not necessarily have to be made by the machine operator. With the information displayed in real time on the dashboard of the factory, this maintenance problem can be communicated to the manager best able to decide when it is advisable to make such a repair.

 

Real-time data display has multiple benefits yielding quick results.

 

Discover other advantages of factory dashboards.

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