Having it all: How to use all your data for plant asset management
October 22, 2012 By Kristina Urquhart
An estimated one-third of maintenance expenditures are wasted due to improper or unnecessary practices. According to a report issued by the E.I. duPont de Nemours Company, “The largest single controllable expenditure in a plant today is maintenance, and in many plants the maintenance budget exceeds annual net profit.”
Maintenance averages 14 per cent of the cost of goods sold in many industries, making it a prime target for cost reduction efforts. Traditional belt tightening and budget slashing can negatively affect quality, productivity and employee morale. A better solution is using emerging technologies such as smart instruments and Plant Asset Management (PAM) systems designed to streamline maintenance practices and reduce waste.
It is common for control systems to be significantly under-performing, with more than half of all control loops showing some form of serious performance issue.
Intelligent or smart instruments are those that have self-diagnostic capability, either for a complete analysis or a simple checkup, depending on the manufacturer. They have sensors to monitor and send information to the microprocessor that uses special firmware to indicate the instrument’s condition and, in the event of failure or calibration deviation, send this information to the interfaces managing the system.
Unfortunately, it is estimated that as many as 85 per cent of the 25 million most common “smart instruments” in use (a HART device) cannot directly connect digital data to systems that manage, monitor and control industrial plants. Each of these HART-enabled devices contains 35-40 data items that can be used to improve the performance of an industrial plant.
A large part of the reason all this data is stranded is that data is often isolated as “islands” because of the need to convert data from one format or system to another via middleware. Unfortunately, it is the management of all the data flowing back and forth between the different components of control system, maintenance system and enterprise resource planning / scheduling software that are the keys to success. Doing so has traditionally required building custom bridges.
These data, associated with the self-diagnostic of the instruments, make proactive maintenance possible. The operational statistics predict the degradation of the devices liable to cause imperfections or failures and can be used to reduce the process variability to determine if/when the device needs immediate fixing. By comparing the data from the manufacturer and site history, this information may be used to estimate when the device may fail, determine the state of the device in its instrument life cycle and discover the operational condition of its critical parts. Operational statistics are data stored in the instrument to inform how much it has been used; or how many times a specific or an abnormal condition occurred.
To be able to access the information in these smart devices, the system must support Electronic Device Description Language (EDDL) and Field Device Tool / Device Type Manger (FDT/DTM) technology for the efficient, convenient configuration and diagnosis of Foundation fieldbus, HART, Profibus PA, Profibus DP and DeviceNet field devices.
New, integrated on-line condition monitoring and protection systems can now significantly increase production throughput by communicating directly with control system field devices via the controller I/O cards the existing control network architecture without proprietary racks or networks.
When online monitoring of device alerts is interfaced with an Enterprise Asset Management system, users are automatically notified if a device needs maintenance and work orders are immediately generated. The work order usually includes the ID number of the device, its priority and its location in the plant.
Of importance for interoperability is the use of open standards regarding syntax and semantics for the information exchange between engineering control systems. In addition to the use of standardized communication protocols, the consistency of the structure and importance of information in particular are crucial in this context.
Advanced (PAM) systems include inputs from process control data historians and include sophisticated state-aware condition monitoring technology – automatically setting multiple “baselines” for equipment based on variable operating loads, speeds and other process conditions. This allows the system to be sensitive to the current operational “state” so as not to over-alarm or under-alarm.
The purpose of a PAM system is to provide timely information about developing faults in a wide range of critical plant assets to operations and maintenance (O&M) personnel so that corrective actions can be taken before production is impacted or before safety is compromised.
The net result is that by using all the data available to them, maintenance personnel can use the predictive information sent from the PAM system to develop optimized schedules based upon the actual asset condition instead of the manufacturers’ recommended PM interval and, in the process, significantly lower overall operating costs with each dollar saved going straight to “the bottom line.”