Preventive and predictive maintenance with a PLC Arduino

June 3, 2020 by
Preventive and predictive maintenance with a PLC Arduino
Andrei Postolache

Preventive maintenance

In an industrial automation environment, the aim of preventive maintenance is to avoid breakdowns by acting before they happen. This is usually done by replacing worn parts before the end of their useful life. It can also be a cleaning or lubrication action. The clearest example is vehicle maintenance, in which oil, belts, filters and other elements are replaced on a scheduled basis before their wear causes breakdowns.

This system allows planning the intervention since the machine or installation works correctly. By knowing the necessary resources in advance, you can plan a preventive stop that affects production as little as possible.

Predictive maintenance

Predictive maintenance is a variant within preventive maintenance, which consists of analyzing and measuring the wear and tear of the elements in order to replace them as soon as they show symptoms that predict the failure before the failure materializes. Analytical techniques such as thermography, diagnosis by vibrations, electrical measurements (such as increased engine consumption) are usually used.
This system is the best in terms of reliability because it allows you to know with certainty that an element must be replaced.


          Advantages

          The main reasons why the industrial sector depends on preventive maintenance are:

          • It significantly reduces the cost of repair which includes: materials personnel, outsourced services... costs
          • Avoid damage to machines or installations, in the event of a chain reaction caused by the fault.
          • Minimize production losses, which are not only limited to the quantity of product that has been interrupted, but also to the disruption of planning due to delayed deliveries and, especially, poor service if the situation affects customers.
          • Eliminate risks for people because some breakdowns can cause very serious accidents.

          Creating a preventive maintenance system

          To create a system capable of controlling the preventive maintenance system, three very important aspects must be defined:

          • Define assets. Number each machine or installation, give it a name so that all personnel calls it the same way ... In this step, it would be convenient to define the criticality of the asset, that is, how important it is, and what happens if it is out of service. For this, it is important to take into account the consequences of a shutdown.

          • Define procedures. Ideally, you should start with the manufacturer's documentation. Most of the actions are included in the machine manual. It will almost always be necessary to add new actions because the environment and use are not exactly as the manufacturer intended. Another very useful tool is the fault log for each machine. With it, you can analyze what has failed in the past, and how you can prevent the incident from reappearing unexpectedly.

          • Define cadence. Manufacturers often give guidance on how often actions should be repeated. The easiest way is to apply these guidelines, and modify them over time, depending on the results. In certain environments, the machines may be subject to greater or lesser wear than the manufacturer intended, so you need to adapt the periods to optimize the cost/benefit ratio.

          Implementation

          To create the automated system you could use the latest technology from Industrial Shields in terms of data acquisition and communication, for we recommend you an M-Duino 21+ with GPRS. The idea is simple, you have to install sensors on each machine at the critical points where preventive maintenance is needed.

          Take for example a factory with several machines running at the same time, where we can find electrical engines, compressors, robots, conveyor belts and hydraulic presses.
          Your programmable logic controller based in industrial Arduino PLC will be in charge of collecting the information from the sensors that will analyze the following parameters:

          • In the case of engines, a very common fault is overload, which can cause the engine to malfunction or burn out. To do this, you should install an electric consumption meter that, if its limits are exceeded, will trigger an alarm and disconnect the engine so that it is not damaged.
          • In many factories, compressed air is usually used to supply various machines. You could be interested in installing a pressure sensor at the outlet of the compressor to control the correct pressure at all times, as otherwise, it could cause the other machines to malfunction.
          • Regarding robots, for example in the case of welding, it is necessary to change, apart from other elements, the welding nozzle and its calibration. To do this, all you need to do is consult the manufacturer's guide to see how many cycles need to be done. By means of a program, a planner can be created, which with the data collected in relation to the change intervals, we can anticipate before the badly welded parts come out.
          • The speed of the conveyor belts is a very important factor in terms of production and for this reason, we can install a presence sensor at a certain point that tells us the parts that are passing in a certain time interval and in case of not complying with it It will indicate that the belt is not working properly and needs to be checked, for example, greased.
          • In the case of hydraulic presses, it is very important that the oil pressure is correct because if it is not, it can deform the parts or the die and have control of this parameter you can install an oil pressure sensor.

          This system is just one example of the versatility that a preventive maintenance system combined with IoT can have since it can be applied to all types of machines or processes, adding measurement parameters such as temperature in engines, the thickness of different parts, etc.

          As we have said, the PLC controller Arduino will collect the data from all the sensors and when critical levels are registered, it will activate the alarms. At the same time, it will create a record for each machine with the failure intervals so that it can also do predictive maintenance. These records can be stored in the cloud or on a server that the company can access from anywhere.

          Below you will see a connection diagram to better understand the process.




          For further information, contact us via  WhatsApp or send us an e-mail. We can assist you to automate your company.


           
           

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          Preventive and predictive maintenance with a PLC Arduino
          Andrei Postolache June 3, 2020
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