IoT has dominated maintenance technology trend reports for years already; and, in all likelihood, it will continue to affect maintenance and reliability organizations for years to come.
And for good reason: declining sensor prices; anywhere, anytime mobile connectivity; advanced analytics powered by cloud computing services; and an aging workforce have combined to make IoT an increasingly affordable — and often necessary — investment.
Lured by the estimated $20.4 billion (by 2020) size of the IoT pie, many organizations that have traditionally served maintenance and reliability staff have jumped into the pool, joining startups in creating a proliferation of new IoT-based technologies and services.
Here’s five emerging, IoT-enabled technology trends sure to affect your maintenance organization in the near future:
- Sending drones where humans have gone before
Many organizations find drones an increasingly capable, affordable, and efficient means of inspecting assets and gathering operating data — particularly when data needs to be collected from confined, hazardous, or remote locations.
Drones and robots today can be customized to fit a wide variety of applications. For example, Boston, Barcelona, and other wastewater utilities have used remote-controlled drones equipped with lights, cameras, and sensors to inspect sewer lines for sediment and FOG deposits at quicker speeds and longer distances than traditional camera inspection methods allow. This winter, NYPA used drones to monitor ice booms on Lake Erie, at a cost savings of more than 90% compared to manned helicopter flights. Duke Energy and Southern Company use drones equipped with cameras and thermal imaging sensors to assess power lines and smokestacks; AT&T uses them to check cell towers. Bridges, oil pipelines, wind turbines, solar farms, and railroads have also been shown to benefit from drone-based inspections.
At the same time, these drones and robots need to be charged, maintained, and repaired, creating new tasks for maintenance staff.
- All your data belongs to us
Gone will be the days of running and exporting a report from one system to upload into the next. End-to-end, automated, fully integrated software promises new efficiencies and insights; however, first you need clean data.
Generating clean data will create new requirements for maintenance staff — such as collecting asset nameplate data that wasn’t recorded on purchase and/or install, gathering operational data where you lack IoT- or SCADA-connected sensors, and completing work orders in a timely manner with appropriate failure and cause codes.
- The computer will see you now
Predictive maintenance, long the stuff of science fiction, is increasingly real and tangible — shifting maintenance away from tactical work order execution and towards more strategic facility and asset management. However, prescriptive maintenance may be a surprisingly near-term technology.
Prescriptive maintenance uses algorithms to troubleshoot issues and recommend best-practice remedies or corrective actions. Ubiquitous sensors and growing reams of condition-monitoring and work-order data will inform future prescriptive practices.
Already, IoT enables us to feed together data from disparate sensors and other sources to make smarter maintenance recommendations. For example, at Motors@Work, we’re developing use cases that look for trends in multiple sensor values to identify what a doctor would call “co-morbidities”— or simultaneous conditions that point towards a different cause than when the conditions occur separately.
In addition to aiding with fault diagnosis, prescriptive maintenance will likely feature AI-driven help — making the content more interactive and conversational.
- Experience your own (augmented & virtual) reality
One-third of all workers are over age 50. As part of the Great Generational Shift that’s currently underway, 2.7 million highly skilled Baby Boomers will retire by 2020 — and be replaced by Millennials and post-Millennials.
Training Boomers for highly skilled positions took years; for example, electric utility linesmen apprentice seven years to reach journeyman status. But we won’t have that much time to train Millennials to fill these vacancies.
IoT-enabled augmented and virtual reality are helping to bridge the skills gap. For example, immersive, IoT-connected, virtual-reality-based job training programs are being used to reduce the learning curve for new utility workers. In addition to accelerating training, IoT-connected augmented reality ensures that every worker uniformly applies best practices to each task — improving worker safety, work quality, and ultimately, asset reliability. Because of these benefits, IDC expects industrial and public infrastructure maintenance to attract the largest investments ($5.2 billion & $3.6 billion, respectively) in augmented and virtual reality by 2021.
- Knowing your odds
With recent updates to ISO 31000 and IoT’s ability to generate and update MTBF estimates using performance data in near-real time, more organizations are choosing to build their EAM hierarchy based on risk.
As opposed to performing interval-based (e.g., annual) risk analyses that assign a rough criticality rating to each asset, risk-based hierarchies turn your EAM into a continuous risk analysis. Where it may be difficult to quantify the probability of an asset’s or process’s failure, this methodology breaks the asset down to replaceable and repairable subcomponents whose MTBF is known. Then, performance data, using near-real-time updates, re-calculates expected remaining useful life and residual value. Combined with a catalog of maintenance and/or replacement costs, and production — and, hence, revenue — expectations with maintenance costs (i.e., consequences), reflect real-time risk.
What emerging maintenance trend will affect your organization the most? Have suggestions for new trends we should watch? Contact Nicole at firstname.lastname@example.org.