New technology advances help manufacturers across industries move away from inefficient maintenance processes, increasing machine uptime and plant productivity
In the era of IoT and Industry 4.0, almost every organization has some strategy and vision around the digital transformation. This catch-all term can include many initiatives – everything from increasing automation in operations, implementing new ERP and customer relationship management systems, and utilizing cloud services rather than investing in on-premise computing and storage up to using AI and machine learning technologies to enhance production. For manufacturing and processing facilities, digital transformation relates to capturing data from smart devices and analyzing that data to make informed decisions.
Still, getting buy-in to invest in new technology or change processes often proves difficult. The best use case example to show a solid ROI is the implementation of condition-based monitoring (CBM).
What is condition-based monitoring?
Also referred to as condition-based maintenance, CBM is a machine and facility maintenance strategy that monitors the real-time condition of an asset to proactively determine when a failure might occur. This strategy is considered the most reliable and most labor efficient for keeping a plant or facility running.
Traditional maintenance strategies
In order to understand why CBM is considered the most efficient option, we’ll take a look at traditional forms of machine and facilities maintenance.
Breakdown maintenance
Breakdown maintenance is straightforward: As the name suggests, machines run until they fail and then require repair or replacement. This strategy is the costliest approach from several perspectives. First, the facility must be able to react quickly to a failed machine to get production back up and running. Rarely does an asset failure occur at an ideal time, which means costly unscheduled downtime. The facility may also need to pay overtime to service crews. In cases where the machine needs to be replaced, the facility could be down for many days or weeks. This can also severely reduce the service life of a machine or process.
Time-based maintenance
Time-based maintenance (TBM) is the most common maintenance program used by organizations. TBM is maintenance performed on equipment on a set calendar schedule and utilizes preventative maintenance strategies. This is a labor-intensive process that is planned in advance where many machines and processing units are maintained at the same time. This requires a large-scale effort and leads to extended shutdowns of facilities.
TBM is an inefficient process as the machines are often running perfectly and do not require any maintenance. While it is a vast improvement over a breakdown maintenance strategy, there is still the risk of a machine breaking down while a process is running and therefore can cause even more downtime. Additionally, TBM strategies require organizations to keep an excessive inventory of spare parts on hand.
Why condition-based maintenance is worth consideration
As mentioned earlier, CBM monitors the real-time condition of an asset to proactively determine when a failure might occur. By using this maintenance strategy, the facility can reduce the number of spare parts that must be kept in inventory, while also preventing secondary damage to the equipment.
With many more smart devices coming to the market with advanced functionality along with the IoT and analytics capabilities of modern control systems, CBM is becoming much simpler to implement than in the past. While there is a higher upfront cost to implement a solid CBM strategy, the overall cost reductions in labor, spare parts and planned or unplanned downtime will show that condition-based monitoring is an element of an overall digital transformation strategy that proves a solid return on investment.
If you’re interested in learning how to implement a condition-based maintenance strategy to boost your digital transformation, contact Beckhoff today.
Jesse Hill is the Process Industry Manager for Beckhoff Automation LLC.
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