Today, we extend the great customer experience we introduced in the previous blog post, into the every-day operations at the customer site. As our example shows, machine customer and manufacturer can review notifications and reports based on data from a machine’s sensors, connected within the internet of things (IoT) and sending data to the machine cloud. Reviewing this machine intelligence in the machine app or in the ERP and PLM systems, they can adjust the timing of maintenance actions and parts replacements to avoid outages and control expenses. They could also collaborate to design and test improvements to the machine, and the manufacturer could add machine innovation to the portfolio of customer services.
Proactive, performance-driven machine maintenance
As before, our sample scenario illustrates the advantages of the IoT and mobility, in general terms, when during the productive life of their machinery, customers can receive feedback from their machines through its IoT-connected sensors, which feed data into the machine cloud. Machine intelligence data broadcast by the machine to the cloud could, for example, automatically be assessed against maintenance policies and optimal performance levels. When the oil level in one of the machine’s systems is too low, this could trigger a notification through the machine app for an engineer, who can schedule a task to top up the oil level. To add this action to the task list is as simple as an additional click on the notification. The shop floor manager receives a simultaneous copy of this notification, which also tell her which engineer is tasked with topping up the oil.
At the same time, the system notices that a calibration was last performed several weeks ago and should be done again. A notification goes out to the shop floor manager, who sees it in her machine app. This notification also recommends that the same engineer who will top up the oil level perform the calibration, because he is available and familiar with the machine. The shop floor manager approves this recommendation with a simple click in the app. At that point, the engineer receives a notification to take care of the calibration. It includes a link to the right section in the manufacturer’s guidance document and to a video that illustrates the steps involved in the calibration. Even an engineer who has not performed a calibration previously could do so comfortably after reviewing this content. As before, the engineer clicks again on the notification to schedule the task.
For both the oil level correction and the calibration, the machine app notifications also include deadlines depending on their criticality. With colors and other design features, the app emphasizes that topping up the oil level is urgent and needs to be done within 24 hours. On the other hand, while the calibration also needs to be performed, its timeliness is not as essential. It should be handled within a week. The engineer can keep the tasks separate on the calendar or decide to perform them at the same time because that might be more efficient.
Going beyond machine maintenance to collaborative improvements
There is yet more the machine manufacturer can do in providing a great customer experience, however. A review of the machine data reveals that, while the oil level is good for now, the increased torque that resulted in larger-than-expected oil consumption is still the same. The tolerance of a key part is also a few millimeters too high. In consequence, that part will not last as long as anticipated. It needs to be replaced at an earlier time. In order to have it perform well until then, it should be lubricated every two weeks.
Communications between the manufacturer and the customer about these details will likely be a little different depending on the machine’s ownership and the roles involved. If, for example, the customer uses the machine within an equipment-as-a-service (EaaS) plan and no on-site engineer is involved because all maintenance is handled by the vendor, the manufacturer simply schedules activities and parts replacement at the right time and ensures the facility is accessible. If the customer owns the machine, they are probably also equipped to perform at least basic maintenance, and one of the customer’s engineers might perform the lubrication and the parts replacement. Documentation would be revised with updated information about the components involved and their maintenance.
Going from an enhanced customer experience to an effective collaboration to improve the machine’s components and performance, the machine manufacturer and the customer can work together to create a part that performs at least as well, lasts longer, and does not have the same lubrication requirements. This collaboration can be promising and profitable no matter whether the customer purchased the equipment or instead enjoys the use of it within a service agreement. We will get more into innovation as a service in the next blog post.
Do you see any customer experience and innovation opportunities in the synergy of machine intelligence, mobility, and ERP? We should have a conversation. Feel free to drop me a message through the form below. You can also find and follow me on Twitter at @lucianocunha.