Condition monitoring is increasingly becoming a sought-after solution to solving the needs of industrial plant maintenance. But condition monitoring is typically expensive and complicated to set up.
In this post I'll detail why condition monitoring is so attractive; but I'll also explain some shortcomings of traditional condition monitoring solutions.
The Industrial Internet of Things (IIoT) “would-be-edge” is populated with millions of industrial machines. To fully participate in IIoT, data from industrial machines must be obtained. Typically, Condition Monitoring sensors can provide that data, but with a caveat. Condition Monitoring is typically an expensive, labor intensive, and complex solution.
Condition Monitoring is one of three typical maintenance strategies:
Because Condition Monitoring is expensive and labor intensive, the “run to fail” maintenance strategy is the most common approach; unfortunately, the cost in downtime is over $2.5T according to the US Department of Energy’s Advanced Manufacturing Office.
Preventative Maintenance gives a false sense of security, because paying for maintenance based on a date, and not based on evidence, is spending money on the hope of preventing downtime. Why? Because preventative maintenance, typically, does not provide visibility into machine operating health.
For many maintenance practitioner professionals and leaders, a condition monitoring program begins with a mix of hope and skepticism. Unfortunately, for the past 25 years Condition Monitoring (CM) has evolved slowly, if at all. A contributing factor is cost. Condition monitoring, on a per machine basis, can cost between $15,000 - $20,000 (USD) for hardware, software, and service. There are additional lifecycle costs as well such as employee training to operate the condition monitoring equipment, and understand the complex data output.
Many Condition Monitoring products are “portable” requiring maintenance engineers to walk from machine to machine acquiring the data manually or via Bluetooth. The most common data capture method? Pen and paper (68% of firms) per Plant Services magazine in 2016.
The challenges are not just the condition monitoring product’s CapEx price, data complexity, or staffing limitations. Many industrial machines are not designed to provide operational health data; therefore, a sensor solution is required. Typically vibration meters are used to gather this data; but vibration data loggers, like enDAQ sensors, and complete standalone vibration condition monitoring systems provide the opportunity for more data capture.
The common denominator among most Condition Monitoring sensors is the requirement for either wired power or replaceable batteries to power the sensor.
There are a few power options for condition monitoring sensors, detailed below. They all have different pro's and con's, but energy harvesting combined with batteries presents an interesting solution.
|
Power Source |
Description |
Pro's |
Con's |
|
Wired |
Plug-in AC power |
High-availability |
|
|
Batteries |
Replaceable (or rechargeable) power source |
|
|
|
Energy Harvesting |
Utilizes ambient energy such as vibration to power the sensor |
|
|
|
Combination of Batteries and EH |
Sensor design includes battery and external add-on (1) EH source |
Extends battery life |
|
There is another, less obvious, issue for today’s condition monitoring programs. The outcome is data for one machine, or data for only a few individual machines. Thus, the data is limited to those few machines and not across the plant.
While a few critical machines may have condition monitoring, many other machines deemed essential and important are not which means most of the plant is either A) running to failure, B) over paying for preventative maintenance, or C) a mix of both.
Today, the strategic competitive advantage from condition monitoring is operational effectiveness. In other words, maximizing machine up-time.
GE has improved efficiency in operations in existing gas turbine equipment through data analysis of more than 100,000 million hours of operating data — sourced from 100 physical and 300 virtual sensors on each upgraded gas turbine. Leveraging internal expertise to monitor 1,600 assets has resulted in improved performance — more output (5% to 10%), better efficiency (1% to 2%) and lower emissions.
For asset-intensive companies, operational excellence is shifting from physical equipment to information assets derived from that same equipment. More specifically, the search for competitive advantage is starting to focus on companies' ability to capture information from a wide spectrum of sources, and then visualize, analyze, propagate and contextualize it in a way that will drive the next wave of business transformation.
Mandates from C-leaders to increase profitability via asset management efficiencies, such as condition monitoring, is driving convergence of multiple technologies across wireless communication, smart sensors, cloud computing, analytics, and smart factories.
For many companies, the ubiquitous combination of mobile, applications and connectivity generates not just insights, but opportunities to influence outcomes. For businesses that know how to leverage their analytic data, outcomes can be influenced proactively, and not just reactively.
The value of IIoT resides not just in the device, but in the end-to-end solution, the data produced, and the actions taken to generate savings along the firm’s value chain. IIoT reflects the growing number of smart, connected products producing data that not only generate insights, but also can enable firms’ agility producing desired outcomes.
For more on this topic, visit our dedicated Wireless Vibration Monitoring Systems resource page. There you’ll find more blog posts, case studies, webinars, software, and products focused on your condition monitoring and maintenance needs.