Integration Key To Asset Optimization

Effective optimization of productive assets relies on input from information systems representing all parts of the enterprise. Open standards make it possible.

Manufacturing and production enterprises are under intense pressure to achieve maximum efficiency. The winners will be those that use their people and equipment assets most effectively. The objective is to optimize the utilization of all plant assets, from entire process lines to individual pressure vessels, piping, process machinery, and vital machine components.

Optimized asset profiles
But what does an optimized asset look like? To start on the road to optimization, it is vital to first decide on the metrics to define the state of optimized asset utilization. Input must be solicited from the engineering, operations, reliability, maintenance, purchasing, safety, regulatory, and risk management departments within an organization to develop these Optimized Asset Profiles (OAP). Members of this multi-disciplinary team bring their own slices of information to the group to use in specifying the required performance/uptime measurements and maximum cost metrics for each service location.

The OAP must be closely aligned with business objectives. The use of financial benchmark metrics is essential for gaining senior management support. A comprehensive OAP considers the total life-time financial impact that any asset installed at a service location has on production, quality, safety, hazardous waste disposal, and costs of maintenance, conversion, inventory, insurance, purchasing, installation, overhaul, and final disposal.

In the power generation industry, OAP metrics for a steam turbine generator system might include:

  • Asset kilowatt hour (kWh) output per year
  • Asset operations cost (steam cost, control systems, and labor) per kWh
  • Asset maintenance cost (preventive maintenance, health monitoring, spare parts, labor, major overhaul, and inventory) per kWh
  • Asset utilities cost (feed water and auxiliary electrical costs) per kWh
  • Asset insurance cost per kWh
  • Asset abnormal situation cost (annualized estimate of unbudgeted safety risks and mechanical failure risks) per kWh

One paper producer is attempting to measure daily asset profitability for each paper machine. The equation to calculate this number is:

Daily Asset Profitability ($) = Income from Sellable Tons Produced Today  All Daily Costs

The following items must be considered in the daily costs:

  • Cost of capital today
  • Cost of raw materials for tons produced today
  • Operations cost today
  • Maintenance cost today
  • Utilities cost today
  • Insurance cost today
  • Unplanned event risk cost today

Information required for optimization
Because business requirements change daily, the OAP also will change daily and need continuous refinement. Evaluating the current state of each process equipment asset versus its OAP also requires a constant feed of information. Performance, reliability, and asset health analysis is regularly needed in order for operations and maintenance to make adjustments to assets in order to align with the OAP.

An example of the need for continuously updated OAP data is the new deregulated power generation marketplace where power stations need to track the hourly cost of each kilowatt-hour of electricity they generate and compare it to the current market price. As the price of each kWh drops, the profitability of operating a higher-cost plant diminishes. If plants have implemented OAP metrics, management has access to the information it needs to make timely, optimum decisions.

Information paths that have an influence on optimized equipment asset utilization are illustrated in the accompanying diagram. Each data node on the optimized asset utilization star has important asset information which needs to be synchronized with other data nodes and merged into comprehensive asset information. The goal is to make timely and informed decisions to safely and profitably maximize the value of the respective assets.

The data domains that affect asset optimization include the following sectors:

  • Engineering design and configuration management
  • Operations planning
  • Safety, regulatory, and insurance compliance
  • Process execution
  • Reliability planning and analysis
  • Maintenance execution
  • Asset health monitoring and analysis
  • Inventory, MRO purchasing, and financial

Engineering design and configuration management
Design specifications for the process equipment and its function in a plant process or machine train are fundamental to asset management. Process and instrumentation diagrams, drawings, manuals, and revision histories for plant production processes and equipment functionality are obviously required to maximize the use of equipment assets. The configuration management data provide the understanding of the design of the process and the specification for the purchasing of the proper asset, which will meet the tolerances of the system without wasting energy resources.

Quantitative process and component-level risk assessments are also an important guide to understanding the most likely failure modes and the effects of these failures on the plant. These assessments can then guide the condition monitoring and nondestructive testing efforts. If a piece of equipment fails and a new one needs to be ordered, the design specification of the failed component is required to be certain that the new replacement asset meets all operational requirements.

Safety, regulatory, and insurance compliance
Understanding the safety issues related to the installation, operations, and maintenance of the equipment assets and production processes is also crucial. Safety concerns affect decisions on when to perform certain high-risk repairs and how long to operate an asset which is in critical need of repair.

Although the environmental regulatory requirements which govern the process (government-required pollution controls, hazardous material disposal, local noise regulations, etc.) may not vary on a daily basis, their proper interpretation is vital in making decisions related to operations and maintenance. An asset optimization team must understand these limits as it makes decisions to run, reduce loading, shut down, or schedule various maintenance tasks. An understanding of equipment repair and inspection regulations, such as regulatory pressure vessel codes, jurisdictional inspections for boilers and pressure vessels, and insurance-driven inspections, also is necessary.

Decisions regarding equipment assets can affect the availability, cost, terms, and conditions of purchasing insurance. A plant with a high asset failure history will normally be underwritten differently than one with a low frequency of significant failures. Understanding the business aspects of a process is essential to properly operating and maintaining it to an optimum level.

Operations planning
The asset optimization team needs to know the current, planned, and historical production and efficiency levels of the process line assets and have the ability to plan modifications to these levels. Demands for the current time period must be balanced with future needs. In some cases, over-production carries a penalty because of warehouse limitations or other business factors.

The incoming process inputs, fuel, electricity, steam, cooling water, etc., need to be reviewed for availability and quality. This is especially important where the process input varies widely. Scheduled downtime or turnaround times are also important information.

Many companies are turning to enterprise resource planning (ERP) systems as the core information technology for their operations. These systems can tie all aspects of the supply chain together, usually within a single data warehouse structure. Production planning and scheduling is one of the important functions of the ERP system.

Process execution
The operations execution plan with the actual scheduling of manufacturing personnel and production equipment is an important source of data. Understanding the backlogs or bottlenecks in the current production stream can assist in asset optimization.

The process control and monitoring systems are commonly called distributed control systems (DCS). These production control systems work in conjunction with local programmable logic controllers to control a process and monitor its current state. The actual production data on current load, speed, temperature, and other process variables are essential to understanding the current health of an asset.

Quality assurance stipulations, including compliance with ISO 90xx standards, are required in many industries. Data regarding the quality of manufactured goods during the production process should be accessible to the asset optimization team.

Reliability planning and analysis
Reliability planning is a vital step toward improving asset utilization. The process begins with the identification of appropriate business metrics, which then are communicated to the asset optimization team for tracking. Typical targets for improvement include unscheduled production downtime and slowtime, maintenance overtime costs, and the cost of spare parts.

After setting the targets for improvement, the next step involves the study of the criticality of all production assets related to their impact on future production requirements, safety, regulatory compliance, spare parts costs, and unplanned failure costs. The definition of what constitutes a failure for a piece of equipment is normally broadened to include speed and load reductions that impact production. Structured approaches such as reliability-centered maintenance (RCM) facilitate this study. The results of this study involve a customized maintenance plan for equipment assets, specifying an optimized combination of condition based maintenance (predictive maintenance), time/usage-based maintenance (preventive maintenance), and failure-based maintenance (reactive maintenance). The output of this analysis will shape reliability-driven maintenance execution and reliability feedback activities.

Reliability analysts also regularly review failures and near misses. After a failure occurs, reliability analysts perform structured root cause analysis to determine the causes of the failure, and modifications are then made in the reliability plan to prevent future occurrences. This might include monitoring additional factors that could have signaled impending failure. An enterprise asset reliability system captures the reliability plan and logs the failures. The system facilitates reliability studies using a variety of software tools.

Maintenance execution
Maintenance execution processes should be based on the output of the preceding reliability planning step. An enterprise asset management (EAM) system or computerized maintenance management system (CMMS) assists in planning and scheduling maintenance manpower and tools. Traditionally, the maintenance organization was defined by the number of major overhauls it could staff and manage, the overtime hours worked against budget, wrench time, control of backlog, and emergency response. Now, the targets are not activity-based, but focused on reliability metrics, increased production output, and expense controls.

Information related to maintenance execution is of great interest to the asset optimization team. Much of the required data relates to the asset nameplate data (manufacturer, model, and specification), maintenance tool availability, and problem histories. Work order planning, scheduling, and tracking are other data sources. This information is useful for knowing what steps have been completed and then specifying the future direction of maintenance activities.

Asset health monitoring and analysis
Most machine and process characteristics which affect quality, availability, capacity, safety, risk, and cost can be continually evaluated throughout the life of an asset. Because this information is a vital feedback loop to modify the current reliability plan based on real-time signals, enhanced reliability organizations are now focusing attention on finding signs of impending failure.

The actual conditions of an asset are conveyed through various sensors. Asset health monitoring, also called condition monitoring, measures critical areas from the reliability plan which were designated as requiring condition based maintenance. Monitoring techniques include vibration signature analysis, lubricating oil analysis, electrical circuit analysis, and thermographic imaging.

The current health of process equipment forms another important node of information for the asset optimization team. Data from operations, protection, on-line condition monitoring, and off-line condition monitoring systems are needed in order to synchronize the various signals for diagnosis and prognosis of asset health.

Best results are obtained by collectively evaluating a complementary mix of characteristics, selected to provide the most accurate measure of overall condition on the specific type of equipment. Specialized analysis tools such as operating deflection shape analysis, virtual sensor analysis, and transient data analysis assist the equipment analyst.

Operators do not normally desire the detailed raw monitoring data gathered by the various technologies, but do require an integrated health analysis, augmented with clear recommendations and forecasts. New enterprise asset health (EAH) systems combine all available health monitoring data to assist an analyst in recognizing abnormal patterns and diagnosing problems. These enterprise-wide systems contain a large database of all condition monitoring indicators and sophisticated multi-parameter alarming techniques. They also provide a platform for automated analysis and communication of health advisories and action requests to a process control system, an enterprise asset maintenance system, and an enterprise asset reliability system.

Inventory, MRO purchasing, and financial
The inventory of replacement assets and spare parts currently on site or in storage is important to the asset optimization equation. The asset optimization team requires information from this area in order to optimize the specification of additional spare equipment and parts. An oversupply of spares takes up costly storage space and ties up excess capital. However, too few spares could cause a lengthy production downtime.

The maintenance, repair, and operations (MRO) purchasing department houses information on preferred vendor arrangements and lead-time-to-delivery of replacement parts. This information avoids rush purchases and allows just-in-time delivery of parts. Cost savings from the use of preferred vendors are also facilitated.

Financial systems tie inventory, purchasing, labor, and materials costs together for management reporting. These systems normally need to be fed information on the utilization of the asset and the manpower utilized.

Data integration issues
Integration of data between various asset software systems is the key to providing timely information to decision-makers to safely and profitably manage equipment assets. The challenge of communicating with the same language between engineering design (CAD and parts library), operations planning (ERP), operations execution (DCS), reliability, maintenance execution (EAM and CMMS), asset health monitoring and analysis (EAH systems), inventory, purchasing, and financial systems is formidable.

Most software providers within each system group are accustomed to a single information and functional structure. Many lack awareness of the potential value of information from other sources and characteristics that must be accommodated to gain full value.

Today, most systems store their information in a proprietary database format with little concern for external program requests for maintenance histories, spare parts availability, and failure events. Process control systems generate archive log data, each with its own file format and structure. Complementary condition measurements are typically gathered by separate systems that cannot communicate or share data for collective comparison. The process is so difficult, expensive, and time-consuming that vital comparisons to confirm accurate status and to predict lifetime are seldom made.

The results of vibration analysis, oil analysis, and other crucial tests are not easily available to a complete machinery diagnostic/prognostic expert system, or to a maintenance system for maintenance or operations to be adjusted. Data from the process control system are not readily available to a vibration condition monitoring system to analyze exception events. The needed link between engineering, enterprise resource planning, process control, maintenance management, and asset health systems has never materialized for many plants and is thwarting the promise of optimum asset utilization.

The value of integration The value of integrating asset systems can be seen from documented results at the largest power-producing utility in the United States, Southern Co. In a 2-year integrated monitoring and maintenance pilot system across five plants, the company has documented more than 100 instances in which information available from equipment health analysis was used to influence maintenance decisions.

During slightly over 1 year, potential savings and avoided costs of about $1 million resulted from deferring planned maintenance on healthy machines and from identifying problems in time to schedule repairs and avoid equipment failures.

In one case, time-based preventive maintenance was eliminated for major plant fans. Technicians now rely on vibration, oil, motor current, and temperature condition based monitoring techniques to determine which fans, gearboxes, and motors to maintain. In one planned plant outage, this resulted in savings of 340 man-hours because the fans did not have to be individually inspected for potential repairs. This reduced maintenance hours associated with these fans by 54 percent.

Open path to integration
Industrial users who desire to integrate their systems have three choices: attempt to buy all software from one vendor, launch in-house integration efforts, or utilize industry-standard open system interfaces from equipment software providers.

Arguably, there is not one software provider that provides a complete system for optimum asset management today. Some companies offer a much broader array of software with a single database platform that will operate with each other.

Today, users who want to provide interoperability between their plant information systems seem to be left with little choice except to hire a system integration company to piece the various systems together. This is usually cost-prohibitive and requires regular updates to the glue software any time one vendor's database format changes.

The cost of developing custom links between various systems can be extremely high and the cost of maintaining each of these links has been estimated at an annual rate of 40 percent of the initial development effort. For example, an $800,000 integration effort will require an on-going annual cost of $320,000 for software maintenance and upgrades.

A better long-term strategy is to purchase systems that utilize industry-standard open system interfaces. The benefits include:

  • Lower cost for electronic exchange of vital information between proprietary systems
  • Freedom to assemble plug-and-play information systems from multi-source best-for-application components
  • Assurance of continuing least-cost upward growth and expansion to gain maximum advantages from improvements in knowledge, technology, practice, performance, and product features
  • Increased value through maximum use of economical high performance consumer components with proven reliability, multi-source support, and rapid evolution to meet requirements of larger markets
  • Reduced need for costly integration software
  • Reduced integration software maintenance costs

Partners for integration
Currently, there are four organizations that are addressing industrial standards for system integration: International Standards Organization (ISO), Open Applications Group (OSG), OPC Foundation, and Machinery Information Management Open Systems Alliance (MIMOSA). In a system integration project, a company should review the specifications from these groups to see if an open protocol can be utilized. An overview is provided in the section Organizations for Open Systems Standards. The choice of suppliers who will partner with a plant in supporting its goals for optimizing the utilization of its assets is critical. Plants may wish to avoid software systems that utilize proprietary closed databases and architectures. A plant should consider the following questions before purchasing manufacturing technology systems:

  • Does the supplier have a history of providing systems that are open and utilize industry standards wherever possible?
  • Do the modules I purchase from this supplier integrate among themselves, possibly using different databases and architectures?
  • Are the products I purchase certified as compliant with current industry standards?
  • Are the software modules I am purchasing from this vendor costly to interface to other systems?

Plants are being forced to achieve higher profitability. To increase a plant's profitability, the optimized utilization of equipment assets is essential. To perform this optimization, plants require timely access to integrated data. The cost of this integration is normally a barrier to many plants moving to this optimization level. The use of open systems is lowering this barrier and allowing plants to begin to make strategic use of vital information. Manufacturing companies who commit to partnering with suppliers who provide systems that support open integration architectures will speed down the road to optimizing their valuable equipment assets. MT

Ken Bever, who serves on the board of directors of MIMOSA, is strategic project manager, Advanced Enterprise Systems Group, ENTEK IRD International, 1700 Edison Dr., Milford, OH 45150; telephone (513) 576-6151; e-mail This e-mail address is being protected from spambots. You need JavaScript enabled to view it ; Internet