Providing the most reliable monitoring systems for remote and difficult conditions is a task that plant managers are faced with daily. New manufacturing techniques, such as Machine to Machine (M2M) and “Human-Free” plants, have recently begun to rely on remote wireless monitoring to improve safety and reliability conditions. Gone are the days of maintenance pros climbing ladders or placing their hands in turbines to collect machinery health information  instead, all of that information is sent to a central repository and analyzed by trained analysts 24/7 so maintenance personnel fix only the equipment that needs attention at that moment.

Joe Van Dyke, vice president of operations and business development of Azima DLI, explains how manufacturers can best integrate remote wireless monitoring into their plant operations to improve the safety conditions for employees, increase productivity and reduce downtime.

What value do remote wireless technologies provide to facilities?

A value of major significance is the low cost of installation. In vibration monitoring, for example, the hardware costs sometimes pale in comparison to the expenses related to installing power lines and communications cables to accommodate a wired solution. And this does not consider the pre-requisite “red tape” that can prove completely prohibitive in some industries. Remote wireless technologies do not disrupt current workflows; in fact, they create new information acquisition channels that make data collection more efficient.

What specific functions are aided by remote wireless technologies?

Remote wireless monitoring can provide extensive timely “at-a-glance” assessments of critical plant assets and processes. When that information is stored and screened intelligently, it can be extremely useful — and even critical to avoid unplanned downtime, allowing engineers to detect and fix more problems on site.  In traditional condition monitoring environments, maintenance professionals may not know about problems and needed repairs until they have manually analyzed the data.  Intelligent continuous or “online” monitoring systems remove this inefficiency.

Wireless sensors allow maintenance departments to expand the number of machines included in the scope of their continuous condition monitoring program. These sensors and associated devices have the ability to monitor machine process parameters, quality and safety, environmental factors and machinery health indicators. This coverage is significant and can be obtained at a relatively low cost with minimal production interruption while providing an even greater level of transparency into a plant’s machinery health.

How can facilities utilize remote services beyond mere wireless communication?

When wireless data systems push their data to common access platforms, it allows secure collaboration by experts inside and outside the immediate organization for strategic decision-making. Examples of common access platforms include databases and data reduction systems inside plant IT systems. These internal systems can also be accessed by distance support providers via virtual private networks (VPN) or other means of remote controlling computers at the plant site.

Other models offer remote access by systematically screening and storing a stream of data from wireless sensors and communicating this to an outside data processing analyst. This data can also be stored within an archival service provider where it can be accessed by plant personnel and third-party service providers via web applications or other tools for distance support.

Can you discuss a customer who has successfully implemented and is using remote wireless services?

One of our nuclear power plant customers uses wireless vibration and temperature data acquisition devices installed on critical equipment. Readings from these devices are screened on-site using an artificial intelligence platform and then the raw data and automated diagnostics are stored at an off-site datacenter via secure message queuing.

Once screened and stored, the information is fed back to the plant process information PI system for immediate display and at-a-glance situational assessment. The data and automated diagnostics are available for in-depth manual analysis and the system is tunable for optimization. The system provides good surveillance, alarming, asset health awareness and trending data.

How critical is the training process for employees working with remote wireless technologies?

It is important for individuals to understand the limitations of the wireless system. It is crucial to understand how it reacts to communications issues like dropped or interrupted signals and what vulnerabilities that it may have to intermittent events, electrical interference or power supply issues. Recognizing and distinguishing faults in the monitoring hardware is critical to any system’s success.

Do you believe that remote wireless technologies will soon be a necessity across facility maintenance departments?

Yes, given the recent advances in wireless sensors and wireless-based remote monitoring solutions. Plant managers are seeing increased advantages through wireless technologies including decreased downtime, enhanced safety conditions and improved visibility into facility-wide data reports. Also, these sensors and monitoring solutions offer advantages,  as compared to traditional wired solutions, that will become a standard design specification and expectation across most industries.

During Joe Van Dyke’s career at DLI Engineering, he managed commercial and government engineering activities and was a member of the company’s senior management team. Joe is the original designer and developer of the automated diagnostic system software that is contained in the ExpertALERT predictive maintenance systems. Joe is a recipient of the US Department of the Navy’s Reliability, Maintainability and Quality Assurance Award in recognition of the contribution to the overall fleet readiness made possible through the development and deployment of Azima DLI’s ExpertALERT software. Joe holds a master’s of science degree in mechanical engineering from the University of Washington and is a licensed mechanical engineer for the State of Washington. He is the author of several papers on the subject of automated diagnostic techniques for machinery.

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