Advances in open technologies, fieldbus integration and information technology are extending the reach of enterprise asset management
To many plant-level professionals, the term “asset management” is synonymous with equipment maintenance or field device management. But, to business managers responsible for process manufacturing operations, asset management implies the effective deployment of all assets within their operational domain to meet business objectives. These assets include: plant equipment, energy, raw material, products, people, facilities, instrumentation, automation, information and even time.
Maintenance is certainly one important element of an overall asset management solution set, but maintenance improvements by themselves will not maximize the business performance of the manufacturing asset base. In fact, attempting to optimize plant operations while improving maintenance, without regard to the operational consequences, or vice versa, actually can degrade performance. True business optimization requires a holistic balance of tradeoffs between maintenance and operations—as dictated by the corporate profitability strategy, not by the isolated improvement objectives of either maintenance or operations.
Five years ago or so, balancing requirements of maintenance and operations across the enterprise, affordably, was more of a vision than a reality. Today, serviceoriented architectures, systems integration standards, high-speed networking and numerous other technologies have advanced to a new level of performance and economy, making platforms that unify maintenance, plant floor, business and customer systems a reality.
Balancing availability and utilization
Maintenance functions typically strive to maximize asset availability while the operations functions strive for maximum asset utilization. Although there are no industry-standard definitions, asset availability often is represented by the percentage of time the plant asset base is available for operating over any given period of time, and as the percentage of total output from an asset base divided by the theoretical maximum output over a period of time. Because it is impossible for a refinery to be 100% available and 100% utilized simultaneously, the only way to manage assets from a business perspective is to manage both holistically, according to the business measures such as plant profitability. Asset performance management (APM) is the holistic approach that has emerged to describe the practice of balancing availability and utilization around business performance.
APM includes what traditionally has been known as enterprise asset management (EAM), but that is only part of it. Although the initial EAM vision did indeed seek to bring together business and operations enterprise functions, in practice, it has focused primarily on optimizing availability. Traditional EAM tactics for optimizing availability have included maintenance repair and operating (MRO) inventory management, condition based maintenance and preventive maintenance. Although these are indeed critical to refinery health and success, most of the maintenance strategies are still at the isolated unit and equipment level—and of these, many are focused even further on instruments and valves.
Similarly, tactics to optimize utilization have been traditionally isolated at the advanced process control level, including such technologies as model-based production management, multivariable control, recipe management and online process optimization.
Moving to APM
Moving from traditional EAM to APM requires extending the scope of traditional EAM systems in at least two directions. One direction involves seamless integration with business and customer systems; the other involves seamless integration with production and production optimization systems. This extension includes the following elements:
- Comprehensive enterprise asset management system with reliability centered maintenance (RCM) and extended condition based maintenance
- Integrated and open field device management
- Condition management, not just condition monitoring
- Knowledge management
- Decision support
- Effective measurement systems
- Improved communication and collaboration
EAM is still pivotal
EAM remains very much at the core of APM. It automates management of the complete lifecycle of plant assets from the device level up to the overall plan. The core capabilities of the Enterprise Asset Manager are as follows:
- Work requests/work order management
- Work crew planning and scheduling
- Workflow and approvals management
- Maintenance cost tracking and analysis
- MRO inventory management, shipping/receiving and supply chain management
- Contract and warranty management
The EAM function also provides a central collection point and access point for asset information, such as cost, performance and history. The EAM component adds value in a number of key operational areas. A study by A.T. Kearney found that the following benefits are achievable from EAM:
- Improved throughput—uptime increases within 10-25%
- Reduced operating expense—labor productivity increased between 20 and 30%; overtime costs reduced between 20 and 35%
- Reduced inventory—MRO Inventories reduced 15-25%; with MRO Supply Chain Savings between 15 and 25%
- General improvements—improvement in health, safety and environmental compliance, reductions in costs of outages and emergency repairs
Benefits such as these are heightened when EAM also includes integrated field device management.
Multi-protocol field device management
Field device management improves flow of operating data from field devices to the EAM system. One of the main benefits of fieldbus technology is the capability to utilize advanced device management applications in host systems that can interact with asset performance diagnostics resident in their intelligent field devices. But EAM systems have had little access to such information when host and field devices come from different vendors.
Although each device had Device Description technology that supported its configuration, this alone was inadequate and, until recently, there were no other standards. However, a consortium of process manufacturers and vendors has collaborated on an open field device toolkit (FDT) that, when combined with recent enhanced data description language (EDDL) developments, has changed the picture significantly.
FDT technology is ideal for making advanced “plug-in” applications, including highly capable valve testing plugins that attach to the host’s device management software in a standard manner. And, through the efforts of the multi-vendor EDDL cooperation teams, the recent EDDL enhancements address one of the key limitations of earlier device description technology by allowing the device vendor to organize the data shown on simple live data screens on the host system and provide the menus to organize the user selection of displays. Invensys, for example, has recently introduced a field device management toolset that lets users take advantage of any EDDL, Enhanced EDDL and/or FDT host deliverables supplied by the device vendor.
In cases where the device vendor supplies only traditional device descriptions (EDDL), the Invensys field device manager lets the users add functions, such as organizing their own live data maintenance screens and watch windows for each model of field device. The field device manager also lets users set up templates for the commissioning behavior and attach supporting manuals, repair procedures, and any other Windows files they find useful in device maintenance.
If the device vendor supplies enhanced device descriptions (Enhanced EDDL), this reduces template setup work because the device vendor has already organized many of the configuration and maintenance displays. Those displays may contain gauge style indicators, trend waveforms and graphic images.
And, if the device vendor supplies both enhanced device descriptions and an FDT device type manager plug-in, users can realize maximum device management capabilities. FDT technology enables the device vendors to go beyond the capabilities of even enhanced device descriptions. With FDT, the device vendor can program a rich graphical user interface (GUI) application as a plug-in to any other FDTcompliant host system engineering application. The plant maintenance staff would call up this application when they want to analyze the health and performance of a specific model of field device or run comprehensive diagnostic tests and archive the test results.
Field device management that supports both EDDL and FDT helps boost engineering and maintenance productivity over the entire lifecycle of an intelligent field device. Reusable engineering is facilitated through customizable templates for each FOUNDATION fieldbus device model, making it easier, for example, for technicians at all skill levels to correctly replace a failed device.
The value delivered by effective field device management can be considerable. In most complex process environments, up to 20% of the ongoing maintenance cost is associated with intelligent devices, sensors and other devices that act as the eyes and ears of the plant. By using a common toolset that works on the wide diversity of intelligent devices from multiple vendors, this cost can be reduced by up to 40%. For a shop with maintenance spend of $50,000,000, these savings can amount to several hundred thousand dollars per year. Customers are able to greatly increase the number of loops managed per individual, where on average, clients are doubling the loops managed per person.
Field device management enables advancement from condition monitoring, which is characteristic of conventional EAM systems, to condition management, which is essential for the new era of asset performance management.
Where many technologies provide basic condition monitoring, describing what is happening with the system, field device management enables condition management, which guides in improving asset performance to achieve specific business objectives. Condition management helps move from the reactive or preventive mode of operations to a proactive and predictive environment. Ultimately, it is this linkage between the real-time and operational environment that moves an organization from asset management to asset performance management.
Condition management has three phases: collecting information (which is comparable to traditional condition monitoring); analyzing information to spot trends and areas requiring action; and acting on the results. Also, where traditional condition monitoring tends to be equipment or area focused, condition management takes a complete contextual view in bringing together operations, maintenance and engineering to resolve critical business issues. Where the previous era of condition monitoring focused on gathering plant level data and making it available as information, condition management goes the next step, advancing information to knowledge and action.
The difference is much more than semantic. Where condition monitoring will help you estimate when a valve might need to be replaced from a wear perspective, condition management might add the business context, assisting you in balancing the risks and gains of replacing that valve this month or next and also ensures that all the key stakeholders are engaged in the decision.
Condition management also extends to fully integrate with DCS/PLC, safety and equipment diagnostic systems, ideally presenting information from these systems through business intelligence frameworks.
The value of condition management is clear. A recent industry survey shows that on average, more than 5% of production is lost every year to unplanned or unexpected outages. For a plant with a total production value of $50,000,000 per year, this amounts to $2,500,000 annually in lost production. The role of condition management is to monitor the key assets that have the largest impact on production, providing early warning of any impending failure, allowing the plant personnel to proactively deal with the issue before it causes a costly shutdown and/or extended outage. In our example, using a conservative estimate of a 30% reduction in outages yields an annual return of more than $750,000.
This predictive capability is further extended by condition management’s ability to collect key performance data to support RCM (Reliability Centered Maintenance) analysis. Based on an independent industry survey conducted by Invensys, more than 50% of preventive maintenance, while valuable in terms of preventing outages, is unnecessary and can often introduce problems. By analyzing the RCM data collected via condition management, organizations can greatly reduce the level of unnecessary maintenance, delivering a further 10-20% reduction in maintenance spending.
Condition management also fuels decision support systems that further integrate and present data from additional sources, including all other components of the EAM system: real-time, historical and analytic plant operations data and other plant and business information, including (especially) financials and customer order management systems.
Such data can be presented through role-specific “digital dashboards” (similar to Fig. 2) tailored to show only the information that users require to make informed decisions within their roles and in the context of the key performance indicators and dynamic performance measures for their department, plant or overall operation. These dashboards can combine multiple formats—meters, graphs/charts, tables, raw statistics and spatial data, with full drill-down and drill-around capabilities.
The real-time integration is much more than a simple process of catching an alarm/alert and generating work requests. It requires full workflow capability that enables engagement of key individuals in the resolution, including operations, engineering and maintenance with full visibility at the management level. It also requires direct connection to devices, system and process alarms/alerts through control system historians and equipment condition monitoring solutions to provide the complete set of information required to understand the context of the potential issue.
In addition, this integration must extend to an HMI in the control/operations environment to allow the operations personnel to spot potential issues immediately, drill down into the details and history and fully interact with the maintenance team and maintenance application(s).
The information solution must further include the ability to capture all the key readings and trends for the critical assets that are necessary to support reliability and availability analysis, which is fundamental in supporting the move to a proactive and predictive approach to operations and maintenance.
Today’s technologies allow us to more effectively capture this wealth of data. Knowledge management is the process of capturing the context and interrelationships of the data points to deliver usable and actionable information. With the “greying” of the workforce, a systematic and automated approach to knowledge capture is fundamental —and a critical element in the move to APM.
The measure of success
Although general descriptors of asset availability and utilization provide a sense of the operation of an asset base, they are lacking in specificity and in any real-time context. Both are required to provide operations and maintenance with an effective performance measurement system. A more specific approach would be to measure the following dimensions:
- Effective Asset Availability—the maximum output possible from an asset set in the current state divided by the theoretical maximum output.
- Effective Asset Utilization—the current output from an asset set divided by the maximum output possible in the current state.
These definitions preserve the integrity of the initial descriptors, and provide real-time context, as well as more accurate assessment of the performance of the operators and maintenance teams. Regardless of which definition is used, it is clear that there is a strong relationship between availability and utilization. It turns out that the relationship tends toward the inverse (Fig. 1) as availability and utilization approach their maximums. This inverse relationship presents a challenge to the maintenance and operations teams in industrial plants because the better they do their individual jobs, the more they will tend to negatively impact each other.
Balancing these factors requires an effective business measurement system that can provide business value insight into the desired operational balance between effective availability and effective utilization. Invensys has a patented approach to real-time business measurement that does exactly this: dynamic performance measures (DPM). DPMs measure the business value of base assets, asset sets or groups of asset sets as a real-time vector that represents the true value that they generate. Instead of optimizing availability or utilization, manufacturers are now able to optimize the business value.
The real-time business performance data (DPMs) enables a much more effective approach to true asset management. Rather than merely managing the availability of some instrumentation, plant personnel can drive business performance from asset sets, up to and including the entire plant. To bridge the gap between the traditional approach to asset management and asset performance management, a threelevel model has been developed (Fig. 2).
In this model, the Base Asset Management level represents the narrow approach traditionally deployed in industrial plants in which base assets, such as instruments and valves, were independently managed from an asset availability perspective. As a matter of fact, even this level is an expansion on the traditional approach to asset management since it includes effective utilization as well as effective availability improvements.
The second level, Asset Set Optimization, goes beyond traditional asset management by combining assets into logical production sets through the use of advanced technologies, such as first principle models so an entire logical set of assets can be effectively managed.
The third level, Business Performance Management, is an all-encompassing level in which advanced technologies and business measures, such as predictive maintenance and multivariable predictive control, can be used in balance with each other to maximize the business value generated of groups of asset sets.
Almost all organizations have the core elements in place that are required for utilizing asset performance management data to drive business value. When implementing this approach, however, it is important to evaluate the current state of the plant. In particular, there are five key elements that must be assessed:
- What is the culture of the company? Are the company and employees ready and willing to change and do they recognize the issues involved with changing?
- Do the employees have the skill base that is required for implementation?
- What are the current business processes in place? Business processes must be evaluated to see if they are current, optimized and built on best practices and benchmarks.
- What is the current technology level? The technology must be assessed to see if the company is based on current and open standards, and what level of enterprise integration is employed.
- Is corporate knowledge readily available and accessible?
While being up-to-date on all these elements is not necessary, all must be evaluated to determine the current status of the plant and how and where to move forward. This will aid implementation, help to identify risks and establish a phased plan for full implementation.
Neil Cooper is vice president, Asset Performance Management Solutions, a key member of the Invensys Process Systems (IPS) Global Marketing Group. Prior to joining Invensys four years ago, Cooper was the president of Indus Canada.