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Manufacturers must make better use of intelligent device management

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Device suppliers have made tremendous progress over the last decade incorporating value-added functionality into intelligent devices. This includes enhanced visualisation and health monitoring functionality to facilitate predictive maintenance (PdM). Despite these technological advancements, many manufacturers are not utilising digital device diagnostics to their best advantage, Paula Hollywood writes.
 
Device suppliers have made tremendous progress over the last decade incorporating value-added functionality into intelligent devices. This includes enhanced visualisation and health monitoring functionality to facilitate predictive maintenance (PdM). Despite these technological advancements, many manufacturers are not utilising digital device diagnostics to their best advantage.
 
Consequently, plant operational efficiency has not improved significantly nor have costs due to device-related accidents decreased.
 
To address this issue, the International Society on Automation (ISA) has recently formed a new standard committee, ISA108, to characterise intelligent device management in the process industries. The committee will define standard templates for best practices and work processes based on information derived from intelligent field devices, including models and terminology, implementation guidelines, and detailed work processes.
 
ARC defines PAM systems as hardware, software, and services that assess plant asset health by monitoring asset condition periodically or in real time to identify potential problems before these can affect the process or escalate to a catastrophic failure. Asset monitoring, one set of applications falling under the asset performance management umbrella, also includes enterprise asset management (EAM), mobility, reliability, ERP systems, and other sources of information.

These include energy management systems (EMS), environmental, health, and safety (EH&S) systems, and sustainability. APM systems provide a compelling case for reducing operational costs while simultaneously improving operational performance. APM leverages the power embedded in various operations and maintenance applications to improve asset availability.

However, to date, the emphasis has been on monitoring production assets. ARC research indicates approximately 75 percent of monitoring investments target production assets. As illustrated above, most production assets contain moving parts that are subject to wear and degradation. Vibration technology is used extensively to monitor these assets.
 
The evidence indicates that automation assets are taking a backseat when it comes to monitoring asset health. According to Ian Verhappen, co-chair of ISA108, "More than 80 percent of smart instrument data is not being used or even connected to an online data collection system." ARC believes that this is counter intuitive given that production asset monitoring frequently requires additional external equipment, while most automation assets already contain a high degree of embedded intelligence. While the level of digital technology implemented in field devices is evolving operational enhancements will not be realised if organizations continue to underutilise the available functionality.
 
Given that intelligent devices and products are widely available, there is a consensus that end users are not utilising the available device diagnostics. Traditional maintenance work processes often exacerbate this situation.
 
Poorly defined problems, for example, waste time and effort. Maintenance for non-critical devices is frequently deferred. Scheduled inspections and testing that reveal nothing are necessary, but wasteful.
 
Formed in August 2012, the ISA108 committee is charged with defining standard templates of best practices and work processes for the design, development, installation and use of diagnostic and other information provided by intelligent field devices in the process industries.
 
[Paula Hollywood (phollywood@arcweb.com) is Senior Analyst, ARC Advisory Group.]

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