There is a widespread misunderstanding of what preventive maintenance (PM) does and does not do. PM does not put iron into an inadequate machine. PM does not work on junk. Initiating a PM program rarely effects your breakdown rate for a year or more unless you commit to this one thing. PM and predictive maintenance (PdM) inspection detect deterioration, damage and defects that will lead to failures, but does not stop them! You stop these incipient failures by doing the corrective tasks, which include correcting the damage, deterioration, or defect in a timely way before the failure.
Let’s face it, people make mistakes – and some mistakes can be quite expensive. Mistakes made in a gearbox rebuild, for example, can cost a plant hundreds of thousands of dollars due to unplanned downtime and even workplace injuries resulting from a bad rebuild. Have you ever taken the time to audit your in-plant or outsourced rebuild facility? Do you require acceptance testing of the components that have been rebuilt to verify they are service ready?
As a reliability engineer in an oil and gas facility, one of the main goals is to minimize reactive work, as well as increase reliability and availability of the physical assets. But another important task is to get the reliability growth noticed by all the people, including leaders and managers. A problem solved is a great chance for a “sales” presentation.
Worthington Industries, a global diversified metals manufacturer, recently finished a complete transformation of the maintenance department at its Columbus, Ohio, steel processing facility. In 2012, with maintenance accounting for the highest percentage of facility downtime at 7.2 percent and a growing open order backlog topping 280, the team decided it was time for change.
Industrial Internet of Things (IIoT) predictive maintenance is firmly on the radar of most executives. At the same time, there are serious concerns about the lack of internal resources to analyze, visualize and interpret the big data generated by industrial machines. This article proposes an alternative: Implementing a big data predictive analytics solution without hiring a big data scientist.
Using in-service oil analysis to improve machinery reliability has a long history. The first oil analysis was performed over half a century ago on a locomotive engine. Just as a human blood test provides important information about your health, the information provided by in-service oil analysis about machinery health, especially for a piece of complex machinery with many moving parts, such as a diesel engine, is unmatched by any other technologies on the market.
Predictive maintenance (PdM) is a very hot topic, and rightly so. Holding the promise of cutting down costly unplanned maintenance events, it’s one of those areas where the hopes of saving a lot of money are very real.
When Benjamin Franklin wrote, “An ounce of prevention is worth a pound of cure,” he was referring to fire safety. But, as you may know from experience, this saying holds true with regard to preventive maintenance (PM). Simply stated, preventive maintenance is an activity performed at a set interval to maintain an asset, regardless of its current condition. It’s a properly planned activity, where materials and parts are on hand and labor is scheduled ahead of time.The goal of any PM program is not only to extend the life of an asset or maintain it to its existing capabilities, but to also identify potential failures that could cause an unexpected event in the future. Properly planned corrective maintenance is typically several times less expensive than performing unplanned work. But, are the typical frequencies that PMs occur actually correct?
Earlier this year, there appeared to be a moment when Democrats and Republicans could agree on increased infrastructure funding. In his State of the Union address in early 2018, President Trump called on the United States Congress to produce a bill that generates at least $1.5 trillion in new infrastructure development.
Over the last few years, the continuous improvement of maintenance strategies is taking place at an incredible pace. The rapid influx of accessible data has the industrial world living in exciting times. As the industry just begins to scratch the surface of what the Industrial Internet of Things (IIoT) can deliver, there is a tremendous opportunity to displace antiquated ways of carrying out asset management.