From Reactive to Periodic Maintenance
In the past, most assets went unmonitored in the field until they failed—this is called reactive or unplanned corrective maintenance. This type of maintenance is by far the most expensive and least effective method, but service departments were constrained by the technology of the day and the high cost of labor.
As manufacturers evolved, service organizations began to monitor the assets in the field through visual inspections during daily sweeps, preventive maintenance tasks, or once the unit failed and required corrective maintenance. Higher priced assets might have on-site staff perform daily sweeps to check on simple machine performance readings or customers might complete the sweeps and submit the results to the service organization over the phone or electronically. Eventually, service organizations utilized statistical data to determine periodic checks and schedule maintenance to try and prevent problems before they occurred.
This “Preventive Maintenance” was generally scheduled by either calendar days, which were not reflective of the actual use of the equipment, by duty cycle (the number of times the asset was used), or by usage counts (the count of its actual output). For example, digital printers were serviced after a certain number of prints were produced, or electronic equipment was serviced on a weekly, monthly and/or quarterly basis. Neither of these methods accurately took into account the condition of the asset or whether it was actually in need of maintenance, just that it had hit a predetermined number of days or cycle counts, so it should be serviced to prevent a failure.
IoT Enables Condition-Based Maintenance
Condition-based maintenance, which refers to scheduling maintenance based on the actual condition of the asset in the field, is a huge advantage over unplanned maintenance, instrument inspection, or preventive maintenance. Once the asset is deployed to the field, if it is IoT enabled and connected to an edge device that can transfer the performance data over the internet, the condition of the asset can be monitored remotely. If the asset’s temperature begins to rise, vibration increases beyond a predetermined threshold, or fluid pressure increases/decreases, a work order can be created and scheduled before the asset fails.
This is important when it comes to cost for a few reasons. First, the scheduling of the service visit can be optimized ahead of time. Dispatchers can assign and dispatch someone who is already near the asset, they can schedule that service call and plan for additional calls nearby to increase the density of service calls, or they can alert the customer of the issue and, if possible, have the unit taken offline until maintenance can be scheduled and completed. The second benefit is that the unit’s problem can be identified before the entire unit fails. Often the uncheck failure of one part of a system can lead to the failure of the entire unit. For example, think of a bearing failing over time on the shaft drive of an engine. If the bearing deteriorates over time but that deterioration is not noticeable to the user, the final failure of that bearing can severely damage the entire engine. If the asset was being remotely monitored with vibration sensors, and the bearing started to fail, the sensors could register the increase in vibration days or weeks before the actual failure and initiate a service request. The service technician would replace the failed bearing during a scheduled maintenance call at a far lower price than replacing the entire shaft or engine.
Another benefit to remote monitoring is that it allows you to understand the characteristics of an asset when it is operating perfectly. As that operational profile begins to deteriorate over time, the changes in the performance metrics can be noted. Once a failure occurs, engineers can look at the past performance data and determine when the profile indicated the likelihood of the failure. Eventually, algorithms can be created to track equipment performance and failures. Using equipment profiles and business rules that describe what changes in performance data constitute a likely asset failure, the system can identify when those changes are met and generate a predictive work order for service. Over time, and a large sampling of an asset type, all possible failures will be identified and the ability to predictively maintain a fleet of assets will significantly improve equipment availability and uptime.
The Next Step: Outcome-Based Service
Once organizations have high a level of confidence in the performance of their assets and know they can significantly reduce and control downtime, they can explore new and more profitable contract strategies. The transition from selling equipment and associated service contracts to more outcome-based services, or servitization, offers many benefits to both the equipment provider and their customers.
The end customer does not necessarily want to be an expert on non-core equipment and associated services, but under traditional contracts where they purchase those assets, they must be. Because they take title to the equipment, they must do all of the due diligence and learn what the best and worst characteristics of that asset type are in order to purchase the most applicable one for their needs. And they need to maintain that level of knowledge to continue to manage the process. In reality, all they want is the output or outcome of these assets. When service providers have more confidence in their ability to monitor and manage the condition of the assets in the field and predict when they will need maintenance, they also have more confidence in ensuring, or guaranteeing, the output of those assets.
Outcome-based services transform customers and suppliers into partners. For example, a company that sells electrical equipment to a manufacturer with service agreements is generally looked at as a supplier. They sell the equipment to the manufacturer and respond when that equipment breaks to fix it. If they transition to selling that customer availability to electricity at a guaranteed level of utilization, the customer no longer has to worry about what kind of equipment it is, how it’s installed, and how it’s maintained—all they need to know is that they have guaranteed access to the power they need to operate. The vendor can use any type of equipment they desire, they can cycle in refurbished equipment, they can add to, or remove equipment as appropriate, all without needing customer approval. All they need to do is make sure that the power is on. They go from selling a product to providing a fully integrated, end-to-end solution.
In summary, the utilization of IoT allows for the evolution from selling assets and fixing them when they break, to monitoring assets in the field and learning more about how they perform in their specific environment, to seeing how their performance degrades over time, predicting when they will need service and intervening before they fail, to gaining such a level of confidence that organizations are comfortable offering the output of their assets as a service. This end state empowers them to truly manage their assets in the most profitable and advantageous way, all the while providing a fully integrated, end-to-end solution to their customers.
IoT & ServiceMax’s Asset 360 for Salesforce
Our focus on equipment and asset maintenance has recently culminated in our development of Asset 360 for Salesforce. Asset 360 for Salesforce combines Salesforce’s industry-leading CRM and Scheduling & Optimization applications with ServiceMax’s expertise on the maintenance and repair of complex assets. We provide the ability to fully view every aspect of an asset’s performance data, history, and economic output in real time. Access to all of an asset’s performance data and history is critical to many parts of an organization including R&D, Supply Chain, Asset Sales, Equipment Service, Finance, and Customer Success. Every part of an organization can gain incredibly valuable insight from a custom view of real-time asset data.
Understanding how assets are used, when they are used, what an asset’s reliability is, how often and how long it has been worked on, what the overall total cost of ownership is, is critical in planning sales cycles, maintenance plans, rental cost structures, and ongoing product development and improvement. ServiceMax, through our innovative and market-leading Asset 360 for Salesforce platform, can deliver these insights and custom views by connecting machine performance data, maintenance history, and parts utilization data to company strategy through seamless integration with the Salesforce.com platform.
The opportunity to combine the power of Asset 360 with the ability to monitor the condition of assets in the field will only amplify the benefits of Asset 360 for Salesforce. Using Connected Field Service to digitally connect assets through the internet of things—utilizing sensors, controls, and edge computing devices—will allow service organizations to receive real-time data from assets while they are operating in the field. This asset service data provides a wealth of information on the health and reliability of the asset that service organizations can use in several different ways.
To learn more about ServiceMax’s take on IoT, read our POV on The Internet of Things & the Future of Field Service.