Maintenance is a necessary and ongoing part of doing business for manufacturers and supply chain management experts. Maintaining optimal performance levels of the many machines, tools, pieces of equipment, and vehicles takes a dedicated effort. This is crucial to business success, as downtime in any single component within an operation can lead to costly delays and missed deadlines. This is where the smart maintenance model comes in to play.
Traditionally, maintenance performed by manufacturing and supply chain organizations is reactive as opposed to being preventative. A machine or piece of equipment gets fixed after it breaks down. It’s as simple as that. While this may have worked in the past, reactive maintenance has proven to have its shortcomings. Issues aren’t addressed until they become a problem, which leads to downtime and added cost.
Recently, many manufacturers and supply chain management firms have turned to a smart maintenance model to avoid this.
The Smart Maintenance model and supporting technologies
Typically, the smart maintenance model consists of five specific approaches, each supported by specific staff, processes, and tools. These five approaches are integrated with each other to make sure there is a comprehensive approach to overall maintenance. Each approach also requires specific support, including staff, processes, and technology.
As discussed, the first approach in the smart maintenance model is reactive maintenance. The least amount of technology and planning is required for this approach but is an essential piece of an overall maintenance plan. After all, no amount of forecasting or planning can predict every incident – issues are bound to arise. When this happens, reactive maintenance is effective.
Reactive maintenance can also be a practical approach for tools and equipment that are part of the manufacturing process, but their function isn’t vital to production. This approach is best used with small items, those that are rarely fail, and any redundant or inexpensive items. Until recently, reactive maintenance has been popular because it is the least costly form of maintenance and requires little supporting technology or background effort. The only requirement is to train workers to spot issues and maintain an inventory of parts needed to make repairs.
Preventive maintenance is considered to be the preferred maintenance approach and is based on data and predictive algorithms. For example, changing the oil in a machine or vehicle every 3,000 miles. Data shows that running an engine for more than 3,000 miles on the same oil can lead to issues. Preventive maintenance is the option for items that see heavy use, are expensive to repair or replace, have many moving parts, or are critical to your manufacturing or supply chain operations.
In order for preventive maintenance to be effective, you need to establish a maintenance schedule and the required maintenance of each machine, vehicle, or piece of equipment. Once this is in place, a maintenance team must be trained in the maintenance schedule and processes. Creating your preventive maintenance plan in an ERP solution can provide for timely and accurate maintenance processes, which can amount to long-term financial benefits.
Remote condition-based maintenance
Remote condition-based maintenance begins with the principles of the preventive approach but adds to it wireless sensors or cameras incorporated into a system. By doing this, maintenance managers are provided real-time data on equipment status.
Remote condition-based maintenance offers the accuracy needed to maintain even the most complex and valuable pieces of machinery and equipment. This approach can also be used to monitor items that can fail without warning, in addition to those that have distinct operational parameters such as temperature, pressure, and air flow.
Technology, including remote sensors and a software solution that provides data capture, notification, analytics, and reporting features is required to support a remote condition-based maintenance program. This approach also necessitates trained maintenance experts who can address issues identified by the system.
Predictive maintenance is another information-driven approach. This approach involves the use of trend data to forecast when a piece of equipment or machinery may require attention. Predictive maintenance uses data modeling and can help you deal with issues before they arise and keep components operating at optimal performance.
Predictive maintenance is a practical solution for items that have identified failure patterns or in cases where equipment is likely to wear out. A predictive maintenance approach requires highly trained experts who are knowledgeable in how the principle works and can perform any known maintenance process. A technology platform capable of capturing data, analyzing it, and creating easy-to-read dashboards is also needed. An ERP solution is a terrific option for supporting the predictive maintenance approach.
Cognitive maintenance is the highest level of smart maintenance as it automates much of the maintenance process. With the use of smart sensors, a cognitive maintenance solution can identify an issue, alert the maintenance manager, requisition any necessary replacement parts, and arrange the repair, all without the input of a staff member.
Cognitive maintenance is the best option in high production facilities with numerous machines or components. This approach does necessitate the highest level of technological support, including an application able to capture and analyze data so maintenance experts can be notified, and replacement parts can be ordered automatically. An ERP solution with intelligent learning capabilities is the perfect foundation for cognitive maintenance.
The benefits of the Smart Maintenance model
- Expanded lifetime of machines, vehicles, equipment, buildings, and facilities
- Reduced cost due to machine failures and unexpected shutdowns
- Improved quantity and quality
- Increased uptime and productivity
- Better and more secure working conditions for staff