{"id":2912,"date":"2019-12-11T09:00:41","date_gmt":"2019-12-11T09:00:41","guid":{"rendered":"https:\/\/tecnologiaparalaindustria.com\/?p=2912"},"modified":"2025-07-22T11:58:17","modified_gmt":"2025-07-22T11:58:17","slug":"tendencias-en-la-recoleccion-de-datos-para-un-programa-de-mantenimiento-predictivo","status":"publish","type":"post","link":"https:\/\/tecnologiaparalaindustria.com\/en\/tendencias-en-la-recoleccion-de-datos-para-un-programa-de-mantenimiento-predictivo\/","title":{"rendered":"Trends in data collection for a predictive maintenance programme"},"content":{"rendered":"

Implementing a proper predictive maintenance strategy is a great idea, but you will never succeed if you are not using the information to take the right steps. It's true that maintenance, operations and reliability engineers are reading and interpreting the information, but you still need to translate this data into action.<\/span><\/p>\n

Yet some reliability engineers have never used the information provided by the su <\/span>condition monitoring equipment<\/b><\/a>This wastes a substantial portion of data that could be used to develop and refine maintenance and reliability plans and strategies.<\/span><\/p>\n

The <\/span>predictive maintenance solutions<\/b> should not necessarily be on their own. In order to create a greater understanding of the plant and its overall maintenance, the <\/span>predictive maintenance systems<\/b> can be integrated into higher-level systems. CMMS\/EAM software and historians are the preferred systems for many maintenance managers to achieve this.<\/span><\/p>\n

\n

A common problem is the purchase of <\/span>predictive maintenance equipment<\/b> without the required support procedures. For example, if you are using the <\/span>predictive maintenance tools<\/b> to identify defects but you have no work control and planning of the production process, then the defect to be identified will be targeted as a high cost and unplanned repair.<\/span><\/p>\n<\/div>\n

The greatest value that predictive maintenance tools can provide is the element of time. Time allows planning, scheduling, and ensuring the execution of the repair at minimum total cost and minimum total downtime.<\/span><\/p>\n

Allocation of time and resources can be difficult in a busy plant.<\/div>\n

 <\/p>\n

Why does the predictive maintenance programme sometimes get lost in the shuffle?<\/b><\/h3>\n

Often what happens is that some of the best and brightest maintenance technicians are given responsibility for predictive maintenance. They perform brilliantly but in obscurity because they are not aware of their achievements.<\/span><\/p>\n

Then they are changed, replaced by other technicians or assigned other tasks. Technology is put on the shelf and sometimes not used for several months, if at all. The consequence is that assets slowly deteriorate and decision-makers do not notice the lack of attention from predictive maintenance specialists until things are really bad.<\/span><\/p>\n

Therefore, their recovery is an uphill battle. Many organisations do not have succession planning and retention initiatives and are surprised when they lose predictive maintenance specialists.<\/span><\/p>\n

Prevention is the answer to a high percentage of machinery problems. Catching conditions that could cause problems early and solving them promptly is the secret to reliability.<\/div>\n

We see an increase in the use of online wireless data collection and the cloud for technologies such as mobile phones and tablets. <\/span>vibration analysis<\/b><\/a>. Communication links for smartphones, tablets, personal computers will be commonplace within two to three years.<\/span><\/p>\n

These technologies are being used by very few yet, they are underestimated and hardly used today, sensors capable of detecting and transmitting machine condition data will be increasingly used, no longer requiring an operator making rounds or a predictive maintenance technician in the field carrying tools measuring from point to point.<\/span><\/p>\n

We will now see technicians who are more specialised in information analysis and decision-making. They will invest their time in actions of greater value to the company. There is now a closer relationship between supervisory control and data acquisition. This will accelerate as cloud and advanced analytics gain acceptance.<\/span><\/p>\n

If you are interested in learning more about the <\/span>vibration monitoring and sustained analysis of rotating machinery<\/b><\/a>we invite you to <\/span>subscribe to our Newsletter<\/b><\/a>.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Implementar una adecuada estrategia de mantenimiento predictivo es una idea grandiosa, pero nunca lograr\u00e1s el \u00e9xito si no est\u00e1s usando la informaci\u00f3n para dar los pasos correctos. Es cierto que …<\/p>","protected":false},"author":2,"featured_media":2913,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[472],"tags":[],"class_list":["type-post","category-automatizacion-y-control","CTA-newsletter","entry"],"yoast_head":"\nRecolecci\u00f3n de datos para un programa de mantenimiento predictivo<\/title>\n<meta name=\"description\" content=\"Recolecci\u00f3n de datos para los programas de mantenimiento predictivo. 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