{"id":7887,"date":"2022-05-04T06:46:39","date_gmt":"2022-05-04T12:46:39","guid":{"rendered":"https:\/\/limblecmms.com\/?p=7887"},"modified":"2025-05-30T13:05:14","modified_gmt":"2025-05-30T19:05:14","slug":"downtime-tracking","status":"publish","type":"post","link":"https:\/\/limblecmms.com\/blog\/downtime-tracking\/","title":{"rendered":"Downtime tracking: how to collect and use machine data"},"content":{"rendered":"

[vc_row kd_background_image_position=”vc_row-bg-position-top”][vc_column][vc_column_text]Businesses that rely on machinery to create revenue lose money when the machinery is idle. Yet, many operations do not have insight into the efficiency of their equipment and lack understanding of the causes for unplanned stoppages.\u00a0<\/span><\/p>\n

Downtime<\/span><\/a> tracking is an important tool for businesses seeking to maximize <\/span>production efficiency<\/span><\/a>. Yet, collecting data to show the machine has stopped is simply one step in the process. The next steps include allocating cause, aggregating the data, and applying remedial tactics to prevent or reduce future occurrences.\u00a0<\/span><\/p>\n

In this article, we’ll present how to collect, analyze, and use machine data to improve equipment uptime and gain competitive edge.<\/span><\/p>\n

Benefits and purpose of tracking machine downtime<\/span><\/h2>\n

We’ve mentioned the financial cost of machinery being <\/span>idle<\/span><\/a>. Reducing downtime increases your production and revenue while labor costs remain the same, <\/span>decreasing your labor cost per unit produced<\/b>. That flows through to a greater profit margin or a lower price to your client.<\/span><\/p>\n

A <\/span>self-reported survey<\/span><\/a> carried out by Aberdeen Research found that unplanned downtime can cost up to $8,600 per hour. If these figures are representative, <\/span>losing one hour of production per week equals over $400,000 lost in annual revenue<\/b>.<\/span><\/p><\/blockquote>\n

Finances aside, there are other, less obvious impacts. You may lose customer trust if production deadlines are missed or if product quality fluctuates due to intermittent production.<\/span><\/p>\n

A common theme from operations that implemented downtime tracking is the disparity between what they thought their productivity was<\/strong> and what the tracking revealed<\/strong>. You can’t fix it until you can identify and measure it.<\/span><\/p>\n

Once the data is aggregated and categorized, you can test tactical mitigations against further stoppages for their effectiveness and impact on <\/span>overall equipment efficiency<\/span><\/a> (OEE).<\/span><\/p>\n

Examples of such interventions include:<\/span>
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