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17 May 2018

The Downtime Your EAM Data Can Prevent

May 17, 2018Blog

Downtime is inevitable in the manufacturing industry and most certainly in the auto industry. Most of the causes can be preventable but downtime occurs for a few reasons that make the whole manufacturing process come to a halt. Material issues, shortage of operators or unscheduled maintenance from a system failure are all unplanned for. There are also the causes that you have no control over such as viruses and malware, despite having scheduled production. Most manufacturers largest source of lost production time is, in fact, unplanned downtime on the job, costing companies more than they originally estimated. The effects of the increased costs and reduction of productivity can be hugely damaging for manufactures.

 “The automotive industry is a stellar example of the cost of downtime. In 2006, automotive manufacturing executives in the United States estimated production line downtime costs at about $22,000 per minute, or $1.3 million per hour. Some estimates ran as high as $50,000 per minute”. (Industry Insights)

Besides the productivity rate decreasing as time goes on, there are also the other costs associated with the downtime such as the cost of employees and service workers. Each of them is unable to carry on their tasks causing the company to produce a smaller amount of goods while still using the same amount of labor and costs. Salaries, rent, and third-party fees will all still need to be paid even though no work is being completed.

When your business is unexpectedly down for a few hours in the midst of peak season, you not only risk losing money but the risk of injuring your company’s reputation for delivering value to your customers. If downtime becomes a regular occurrence and manufacturers begin to struggle to meet demands, it is likely your customers will begin to lose trust and patience with you. An injured relationship could result in customers taking their business elsewhere.

With such high costs at stake, keeping production machinery operating smoothly is critical to a high-volume factory. To ensure that downtime costs are at a minimum, it is important that manufacturers have clean, accurate and complete EAM master data. Without accurate data, you may have a decrease in production output and quality, an inability to properly plan maintenance and most importantly have an increase in downtime resulting in production loss. There are many more EAM data challenges for your operation that you may not even be aware of.

 

How We Can Help Reduce Your Downtime

 

NRX AssetHub helps identify data quality issues using strong reporting capabilities to highlight gaps, and measure the completeness of the asset and maintenance data residing in EAM systems. Intelligent filtering allows our customers to focus on areas of concern such as knowing when to service a part prior to it becoming a problem. By making it easy to find issues relating to data quality, NRX AssetHub helps you increase maintenance efficiency and reduce downtime. Allowing you to optimize or change maintenance strategies for existing assets. When customers have started identifying gaps in their data they can use the multiple features of NRX AssetHub to accelerate the data repair process, such as smart search and filtering to locate records along with additional features.

 

About NRX AssetHub

 

NRX AssetHub provides maintenance and reliability professionals at asset-intensive businesses with world-class software solutions for analyzing, visualizing, building, editing, organizing, approving, and sustaining high-quality Asset and Maintenance Data for the Enterprise Asset Management (EAM) and Computerized Maintenance Management (CMMS) systems. We help our customers get their EAM data right.

To find out more about how NRX AssetHub can help your organization cleanse and eliminate EAM data challenges, book a meeting with us today!

 

Sources

Industry Insights. https://www.simutechmultimedia.com/the-true-cost-of-downtime-what-you-dont-know-about-how-downtime-affects-your-productivity/ 2017.

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