What can you do with industrial equipment that is out-of-date and wasn't built with the latest technologies? As Industry 4.0 continues to grow around us and we become more and more reliant upon connectivity, data, and analytics, this question is posing serious concerns for Asset Management professionals.
In our previous article, we discussed the alternatives to the rip-and-replace method: refurbishment and repair. Since both options have their drawbacks and advantages, that leaves organizations with tough decisions to make. Refurbish their existing assets or purchase new assets equipped with the latest technology? To answer this question, enterprises should consider a variety of criteria, including:
Taking into account these criteria, plant operators should decide on:
In general, refurbishment can lead to significant cost savings, when planned and carried out for the right equipment, at the right time and by the right people. Miss the mark on any one of these vital criteria and it may be a costly and fruitless exercise.
But there’s good news. In the Industry 4.0 era, making the best decisions about refurbishment should become easier than ever before. This is because Cyber-Physical Systems (CPS) and digitally enhanced machines will provide a wealth of data, that, if properly analyzed, could be used for:
Overall, the collection and processing of large amounts of data for the condition of the machinery can lead to a data-driven and factual decision making, rather than the simple rules and more hands-on approaches used today.
For example, many organizations schedule a refurbishment based on the time that a machine or other piece of equipment has been operating, for example, five years. This is by far less effective than employing machine learning in order to identify the structural issues of a machine in a timely manner and schedule its re-manufacturing at the best point in time.
Most importantly, the benefits of refurbishment are not only the cost savings of avoiding or postponing a purchasing decision. Refurbished assets increase their resale value and can, in several cases, be recapitalized with smaller depreciation periods that the ones associated with a brand-new machine. Under certain circumstances, this can lead to considerable tax benefits as well. Furthermore, in some situations, refurbishment removes the need to train operators on an entirely new machinery, which incurs a considerable learning curve. Likewise, if there are existing production operations, the impact will be minimized.
By and large, refurbishment can – under certain conditions – provide a compelling alternative to purchasing new equipment.
In particular, a carefully planned process that refurbishes the right parts, at the right time and with the engagement of the right people can lead to significant cost savings, while at the same time minimizing disruption on existing maintenance and asset management operations.
In the Industry 4.0 era, enterprises will be provided with rich datasets and advanced tools that will make the entire asset management and lifecycle assessment processes easier, most accurate and more effective than ever before.
With new technologies cropping up every day and the competitiveness of the global marketplace continuing to grow, it's no surprise that Asset Management professionals are evaluating their options when it comes to their legacy equipment. With so much on the line, it makes sense to review the alternatives and understand the pros and cons of refurbishments, upgrading, or replacing your industrial assets.
John Soldatos holds a Phd in Electrical & Computer Engineering. He is co-founder of the open source platform OpenIoT and has had a leading role in over 15 Internet-of-Things & BigData projects in manufacturing, logistics, smart energy, smart cities and healthcare. He has published more than 150 articles in international journals, books and conference proceedings, while he has authored numerous technical articles and blogs posts in the areas of IoT, cloud computing and BigData. He has recently edited and co-authored the book “Building Blocks for IoT Analytics”.