Every manufacturing managers’ worst nightmare is unexpected machine downtime. In the hopes of reducing the amount of time that their organization must face without a critical piece of equipment, these managers must develop a maintenance schedule that fits the needs of their business. This post will breakdown the two major methods that most businesses use, preventive and predictive maintenance.
The former strategy is likely the most common of the two. It is a common staple for maintenance in many industries around the world. Preventive maintenance is a strategy that includes performing maintenance on each piece of equipment in an organization’s fleet at routine intervals throughout the year. This may seem counterintuitive at first, but the truth is for a majority of organizations it is effective. The frequency at which machines receive maintenance is largely based on age and average run-time. For example, older machines may require more maintenance throughout the year than newer machines. The same way that machines that have a longer average run-time will likely require more routine maintenance than those with a shorter average run-time.
The newer alternative to preventive maintenance is predictive maintenance. This strategy disregards a majority of the philosophies of its counterpart. Rather than having scheduled maintenance for equipment or machinery at different times of the year, this approach relies on information fed from each piece of equipment to determine when maintenance is necessary. This requires a unique set of technological systems to be installed into an organization’s fleet but will in turn provide organizations with a much clearer representation of when maintenance is required. The downside? Its exuberant costs compared to the traditional preventive maintenance strategy.
Despite being more costly, implementing a predictive maintenance system is becoming increasingly easy. The number of technologies within the Internet of Things space continues to increase, which in turn increases the compatibility with manufacturing equipment around the world. Once properly implemented, these systems are able to capture, report, and analyze the performance and external data that affect any piece of equipment’s condition. With this information, it becomes much easier to predict when any given piece of equipment will require maintenance and what specific maintenance it will require. This, in turn, can lead to greater efficiency and less downtime for critical pieces of equipment.
While the benefits for these predictive maintenance systems may seem staggering, it’s equally important to consider where these systems fall short. With such high barriers to entry, not many businesses can justify the cost in regards to their estimated risk. In addition to high start-up costs, these systems also require a critical understanding of new technology platforms that your employees have no knowledge of. In other words, your employees will likely face a rigid training course in order to properly work alongside these systems. This sort of challenge is not easily overcome and will likely require a great deal of time. However, if your organization has the capital and other resources available, predictive maintenance is likely the best strategy to default to.
If you believe your organization’s manufacturing operation is due for a reconsideration in the way they handle their maintenance, take a moment to review the infographic paired alongside this post for more information on which method is right. Infographic courtesy of Industrial Service Solutions.
