The industrial internet of things (IIoT) has been lauded as a possible solution to the looming threat of unexpected downtime. The rationale behind this is that smart equipment will be able to provide status updates and alerts to engineers before a breakage occurs. However, this is not an alternative to an effective maintenance strategy, especially in regards to lubrication. Here, Mark Burnett, VP of the Lubricants and Fuel Additives Innovation Platform of NCH Europe, explains.
Adoption of the IIoT has undoubtedly been one of the most eagerly anticipated prospects in manufacturing for some time. Now that it is no longer an abstract concept, it is understandable that many manufacturers consider it the miracle cure for many industrial ills.
One such ill is unexpected downtime. This is currently a large problem for manufacturing businesses, where even one machine halting production for one minute can result in substantial financial losses. Therefore, any potential solution is highly valued and sought after.
That is why there has been such interest in intelligent systems capable of generating masses of data on critical variables such as temperature, pressure and cleanliness. By keeping maintenance engineers updated on the status of equipment and predicting upcoming failures, intelligent machinery looks to make life simpler for businesses and engineers alike.
However, there is no substitute for an effective maintenance strategy. While systems may be able to forecast repairs, an effective strategy gives maintenance engineers more time between repairs. This is particularly important for processes such as lubrication.
For example, a steelworks plant will have a lot of machinery with high operating temperatures. If these machines do not have a lubricant with sufficient heat resistance and thermal properties, this can lead to decomposition of base oils and a higher rate of corrosion.
Likewise, pelleting machinery often processes materials such as wood that is prone to producing a substantial amount of dust. These abrasive particles often find their way into the lubricant and accelerate wear.
While intelligent systems will certainly be able to alert engineers of the need to perform maintenance or change lubricant imminently, they will not be able to accurately diagnose the reason why. The only way to do this is to develop and practice an effective approach to lubrication.
The first step to an effective lubrication strategy is to determine the requirements of the lubricant. In order to do this, engineers and plant managers should assess the operating conditions of the machinery in question.
These operations do not necessarily relate to the plant conditions or even the temperature of the machinery itself. However, the operating environment should also be accounted for. A food processing or pelleting plant will be prone to contamination, so it is important that lubricating greases have a composition that nullifies the impact of particulates.
For machine conditions, the most important variables are operating temperature and load dimensions. For example, if a machine processes heavy materials, plant engineers must ensure that it is lubricated sufficiently to perform under the high pressure. This involves selecting a lubricant that has a high load-bearing capacity.
A number of things can happen without correct specification. In some instances, an unspecified lubricant will simply deteriorate quickly and need replacing frequently, which in turn increases the cost of operation. Yet in other cases, the lubricant will be unable to handle the load and will deteriorate during the first use. This not only leads to machinery damage but also risks breakage and downtime.
Of course, even an intelligent system in an IIoT network will only be able to highlight the unusually high operating temperature or breakage after the wrong lubricant has already been applied. Maintenance engineers can pre-empt the problem by understanding what kind of lubricant they need.
In the case of heavy load-bearing machinery, plant engineers would need a high viscosity lubricant with a calcium-sulphonate formulation, such as NCH Europe’s K Nate HV.
Even a perfectly specified lubricant is only as effective as its application. Applying too much lubricant is just as bad as applying too little, as both cause the equipment to fail sooner.
The implications of under-lubrication are clear. Without enough lubricant on a surface area, friction will occur and accelerate wear. Over the course of a production cycle, it is not uncommon for high amounts of friction to lead to a complete machine breakage and downtime. Industrial sensors may be able to alert engineers to an impending failure, but cannot tell them that they are under-lubricating the equipment.
Conversely, many plant engineers take a ‘more is better than less’ approach to lubrication in the hopes that it will reduce the frequency of maintenance. Unfortunately, this is not the case.
For example, when equipment is over-lubricated with a grease, the excess volume of lubricant raises the overall operating temperature of the equipment. This heightened temperature increases the rate of oxidation, which can cause the build-up of hardened grease deposits on surfaces.
These deposits impair the effectiveness of lubrication and can prevent the flow of future products unless properly removed. They also increase the pressure on seals, which results in failure and leakage of lubricant.
Plant managers and maintenance engineers can avoid these problems by ensuring all engineers know how much lubricant to use. This is information that a lubrication specialist, such as the supplier of the product, can help with.
The final step to an effective lubrication strategy is to ensure that machinery is regularly lubricated and that any possible issues, such as grease deposits, are addressed before they cause problems.
This is where the IIoT can help by notifying when equipment is running low on lubricant. While this ensures that maintenance is conducted regularly, engineers must then inspect the application fully to assess whether any further action needs to be taken.
Undoubtedly, the rise of IIoT is bringing a wealth of benefits to manufacturing businesses, but the elimination of downtime is not strictly one of them. What it does offer is an opportunity for engineers to manage and prevent downtime more effectively, which can only be realised with proper planning, the right products and a comprehensive strategy.