Myths and realities of asset optimization
Fueled by the introduction of intelligent field devices and automation platforms capable of collecting and reporting asset health information, much has been written about asset management and asset optimization recently. Consequently, there are a number of perceptions and misconceptions about what these terms mean, what they do and what is driving demand for them.
Fueled by the introduction of intelligent field devices and automation platforms capable of collecting and reporting asset health information, much has been written about asset management and asset optimization recently. Consequently, there are a number of perceptions and misconceptions about what these terms mean, what they do and what is driving demand for them.
A real solution? Or more marketing-speak?
So many different messages have been delivered on the subject that some think asset management and asset optimization are simply marketing ploys and that they provide no financial benefit.
This perception couldn’t be further from the truth. Executing an effective asset optimization strategy has become central to survival in today’s competitive world.
Over the past two decades, discrete manufacturing and process industries have made great productivity gains through effective implementation of advanced automation technologies. However, in the face of increasing global competition and the ever present demand to meet investor expectations, these productivity gains are simply not enough to ensure future success. This has forced many industries to re-evaluate their business models and implement continuous improvement initiatives across all aspects of their operations.
In many cases, operational excellence initiatives have been established to drive profitable, sustained growth throughout the enterprise. The focus of many of these initiatives is to maximize operational asset performance while lowering costs — specifically maintenance costs.
Key performance indicators are commonly established to measure maintenance costs, maintenance utilization, maintenance effectiveness, maintenance over time, equipment downtime, percentage of emergency repairs and percentage of completed preventive maintenance inspections. The goal is to use KPIs to drive down maintenance costs without jeopardizing production. Many KPIs can be directly affected by establishing an integrated asset optimization strategy based on asset health to avoid unplanned downtime and allow for greater production control.
One measure is overall equipment effectiveness (OEE), which combines equipment availability with production rate and quality to provide a true measure of how effectively operational assets are performing. An effective asset optimization strategy increases both equipment availability and production rate by providing insight into asset health, corrective action instructions and organizational visibility.
Executing an asset optimization strategy to increase OEE and reduce maintenance costs can be a highly effective means to remain competitive in the market place while achieving profitability goals.
Asset management vs asset optimization
Another point of confusion is in the definition of the terms “asset management” and “asset optimization.” Are the two simply different descriptions for the same capability? No.
There is a very distinctive difference between asset management and asset optimization. Unfortunately, the term asset management can mean different things to different people. To some, it means managing repair vendors or reducing inventory levels based on inventory turns against the installed base. Others focus on collecting and analyzing data for predictive purposes. In the context of an automation system, it might mean a feature within an automation platform that monitors alarms and events to be used to dispatch maintenance when tolerances are exceeded. Most often, asset management is deployed tactically at the device level.
More than a way to manage devices, asset optimization is more than a product feature or a series of disconnected tasks. Asset optimization is a strategy that provides the capability to optimize all aspects of the operational asset in order to extend the asset’s life, reduce life-cycle costs and ensure availability. It goes well beyond simply identifying fault-oriented maintenance requirements.
Predictive maintenance strategies can be employed by integrating real-time asset health with a Computerized Maintenance Management System. Early detection of pending failures can trigger work orders in an integrated CMMS well in advance of a failure. As a result, labor, work instructions and parts can be allocated and coordinated between the maintenance and production organizations, thereby avoiding unplanned downtime, production losses and unnecessary overtime expense.
An effective asset optimization strategy combines the needs of the production and maintenance organizations. Its ability to share contextual information to those who need it — when they need it — reduces time-to-decision and coordinates production and maintenance activities. The primary benefit of asset optimization is to provide maximum production output at minimum cost. Asset management and asset monitoring are components of an asset optimization strategy, which includes integrating device health with the automation platform and a CMMS. Consequently, asset optimization is deployed on a more strategic level.
Valuable information? Or too much data?
A significant part of effectively managing assets comes from collecting and analyzing data. So much emphasis has been placed on this activity that some believe the value stops there. In fact, many are afraid that they will have too much information and won’t be able to identify real problems when they occur. For example, a flood of alarms may naturally occur during a startup or coast down situation. When this occurs, operators typically acknowledge and ignore these alerts. However, some of them should not be ignored.
An effective asset optimization strategy ensures that this overload does not occur. It consists of more than just monitoring alarms and events or collecting and analyzing asset data. Intelligent alarm management, coupled with separate operator and maintenance workplaces, eliminates the flood of nuisance alarms and prioritizes rules-based alarms to the appropriate people.
An asset optimization strategy becomes an integral part of establishing an effective maintenance strategy that is based on asset condition to reduce costs and increase availability. It provides a means to share critical asset information throughout the enterprise so that operations, maintenance and engineering can work together to maximize productivity.
Benefits beyond maintenance
Implementation of an asset optimization strategy is typically the responsibility of the Maintenance group — regardless of whether it is a component of an operation excellence initiative or a part of a reliability centered maintenance (RCM) strategy. The reason is clear: maintenance is charged with reducing unplanned downtime, increasing reliability and reducing maintenance-related costs. However, maintenance is not the sole benefactor of an asset optimization strategy. While the initial focus may be on reducing maintenance cost, understand that unexpected failures and poor product quality can be devastating to profit goals.
The task to drive improvement falls squarely on the shoulders of the maintenance manager. The challenge is to effectively manage workforce utilization and reduce maintenance expenses, while ensuring plant availability with minimal interference with production.
No short-term actions
A common response can be to batten down the hatches. These actions may include deferring preventive maintenance activities, limiting outside repairs, reducing spares inventory, placing price reduction pressure on parts and services vendors, reducing staff, installing a CMMS package or leveraging asset management.
While these actions may result in lower period costs initially, they serve as more of a Band-Aid approach. They do not provide the long term sustainable savings that can be realized by an effective asset optimization strategy.
Developing a successful asset optimization strategy begins with understanding the organization’s long terms goals, including those of the production group as well as those of the maintenance group. The next step is to benchmark the operation relative to appropriate KPIs and other like operations. Unplanned downtime, maintenance overtime hours, number of emergency repairs, equipment availability and OEE are typical measures.
The next step is to determine asset criticality. Once the critical assets have been identified, the method of extracting appropriate asset health data can be determined. From there the methodology of providing the necessary information to operations and maintenance is determined. With these steps completed, device-specific maintenance strategies are developed.
Following these simple steps, an asset optimization strategy can help to reduce maintenance costs by establishing equipment-specific maintenance strategies that, in the long term, squeeze the most use and value out of the asset. By incorporating current asset health information with historic data, the appropriate device-specific strategy can be developed. Establishing a device-specific strategy will reduce unplanned downtime by helping to establish condition-based preventive maintenance schedules, thereby supporting RCM strategies.
If a device indicates a fault, asset monitors can provide root-cause data, fault diagnosis and recommended corrective actions. A work order request is sent to the integrated CMMS system along with troubleshooting information and suggested resolutions. The result: reduced time-to-decision and reduced time-to-repair, leading to less downtime and lower maintenance costs.
You can start small
Some think that an asset optimization solution must be applied enterprise-wide for the strategy to be effective. This is probably one of the greatest misconceptions about asset optimization. These strategies can be implemented in stages and still provide immediate payback. It is not uncommon to begin a strategy around a particular machine, line, process, location or asset type.
The key is to define an overall asset optimization implementation strategy that includes advanced maintenance strategies. Then, establish the metrics required to truly measure the effectiveness of the new asset optimization strategy. Increasing equipment availability and improving yield are two quantifiable measures. Combining OEE improvements with reduced maintenance expenses provides a solid ROI in an asset optimization strategy.
Closing thoughts
These are a few of the current perceptions and myths regarding asset optimization. The reality is that the implementation of a well-managed asset optimization strategy can greatly contribute to achieving operational excellence and improve financial performance.
Much ado has been made recently about the capabilities of the technical solution. But that’s just the tip of the iceberg. This article has presented the real value that comes from leveraging a truly integrated asset optimization strategy that presents the right data to the right people at the right time so that sound operational decisions can be made that impact OEE and maximizes maintenance by changing maintenance practices and assessments as needed. These capabilities are what differentiate asset optimization from asset management.
The Bottom Line…
There are many perceptions about what asset optimization means, what it does and what drives its need.
Executing an asset optimization strategy to increase OEE and reduce maintenance costs can be a highly effective means to remain competitive in the marketplace.
The primary benefit of asset optimization is to provide maximum production output at minimum cost.
Author Information |
Brian Reierson is the director of asset optimization business development at ABB Inc. His experience in sales, marketing and service management positions spans 30 years, with emphasis on asset optimization and condition monitoring during the past eight years. |
Myths and misconceptions about asset optimization and asset management
Misconception : Confusing descriptions — what are they, really?
Misconception : Asset management and asset optimization are different names for the same thing
Myth : Asset optimization is used basically to manage devices
Myth : The job is done once the data has been collected
Misconception : The only focus of asset optimization should be to reduce maintenance costs
Myth : Short-term measures will effectively achieve our goal
Misconception : Asset optimization solutions must be big to be effective.
How can you optimize assets to improve your financial return?
Questions to ask:
How do you compare to world-class performers?
What has the greatest impact on shareholder value for you: asset effectiveness, or reduced costs?
How do you deliver actual, lasting improvements?
How can you improve the reliability and safety of your operation?
Where are hidden improvement opportunities; how worthy are they?
An effective asset optimization program consists of these major components:
Benchmark study
Criticality assessment
Development of an asset plan
Skills alignment
Tools and training
Performance metrics
Participate in maintenance benchmarking survey; results in PLANT ENGINEERING
Klaus Blache from General Motors Corporation will conduct a maintenance benchmarking survey modeled after a similar study done several years ago while he was chairman of the Society of Maintenance and Reliability Professionals.
The purpose of the study is to compile current maintenance benchmarking information and viewpoints by repeating parts of two past studies done (1991 & 1997). Blache conducted the earlier analysis, and these results will be compared to looks at trends.
Survey participants also will be given the resulting report. As before, the survey uses ratios and percents for anonymity and no company names are ever mentioned. A summary of the findings will be published in PLANT ENGINEERING .
To participate, download a PDF version of the survey, which can be found atkmb-mail@hotmail.com.
Participate in maintenance benchmarking survey; results in PLANT ENGINEERING
Klaus Blache from General Motors Corporation will conduct a maintenance benchmarking survey modeled after a similar study done several years ago while he was chairman of the Society of Maintenance and Reliability Professionals.
The purpose of the study is to compile current maintenance benchmarking information and viewpoints by repeating parts of two past studies done (1991 & 1997). Blache conducted the earlier analysis, and these results will be compared to looks at trends.
Survey participants also will be given the resulting report. As before, the survey uses ratios and percents for anonymity and no company names are ever mentioned. A summary of the findings will be published in PLANT ENGINEERING .
To participate, download a PDF version of the survey, which can be found atkmb-mail@hotmail.com.
Participate in maintenance benchmarking survey; results in PLANT ENGINEERING
Klaus Blache from General Motors Corporation will conduct a maintenance benchmarking survey modeled after a similar study done several years ago while he was chairman of the Society of Maintenance and Reliability Professionals.
The purpose of the study is to compile current maintenance benchmarking information and viewpoints by repeating parts of two past studies done (1991 & 1997). Blache conducted the earlier analysis, and these results will be compared to looks at trends.
Survey participants also will be given the resulting report. As before, the survey uses ratios and percents for anonymity and no company names are ever mentioned. A summary of the findings will be published in PLANT ENGINEERING .
To participate, download a PDF version of the survey, which can be found atkmb-mail@hotmail.com.
Participate in maintenance benchmarking survey; results in PLANT ENGINEERING
Klaus Blache from General Motors Corporation will conduct a maintenance benchmarking survey modeled after a similar study done several years ago while he was chairman of the Society of Maintenance and Reliability Professionals.
The purpose of the study is to compile current maintenance benchmarking information and viewpoints by repeating parts of two past studies done (1991 & 1997). Blache conducted the earlier analysis, and these results will be compared to looks at trends.
Survey participants also will be given the resulting report. As before, the survey uses ratios and percents for anonymity and no company names are ever mentioned. A summary of the findings will be published in PLANT ENGINEERING .
To participate, download a PDF version of the survey, which can be found atkmb-mail@hotmail.com.
Participate in maintenance benchmarking survey; results in PLANT ENGINEERING
Klaus Blache from General Motors Corporation will conduct a maintenance benchmarking survey modeled after a similar study done several years ago while he was chairman of the Society of Maintenance and Reliability Professionals.
The purpose of the study is to compile current maintenance benchmarking information and viewpoints by repeating parts of two past studies done (1991 & 1997). Blache conducted the earlier analysis, and these results will be compared to looks at trends.
Survey participants also will be given the resulting report. As before, the survey uses ratios and percents for anonymity and no company names are ever mentioned. A summary of the findings will be published in PLANT ENGINEERING .
To participate, download a PDF version of the survey, which can be found atkmb-mail@hotmail.com.
Participate in maintenance benchmarking survey; results in PLANT ENGINEERING
Klaus Blache from General Motors Corporation will conduct a maintenance benchmarking survey modeled after a similar study done several years ago while he was chairman of the Society of Maintenance and Reliability Professionals.
The purpose of the study is to compile current maintenance benchmarking information and viewpoints by repeating parts of two past studies done (1991 & 1997). Blache conducted the earlier analysis, and these results will be compared to looks at trends.
Survey participants also will be given the resulting report. As before, the survey uses ratios and percents for anonymity and no company names are ever mentioned. A summary of the findings will be published in PLANT ENGINEERING .
To participate, download a PDF version of the survey, which can be found atkmb-mail@hotmail.com.
Participate in maintenance benchmarking survey; results in PLANT ENGINEERING
Klaus Blache from General Motors Corporation will conduct a maintenance benchmarking survey modeled after a similar study done several years ago while he was chairman of the Society of Maintenance and Reliability Professionals.
The purpose of the study is to compile current maintenance benchmarking information and viewpoints by repeating parts of two past studies done (1991 & 1997). Blache conducted the earlier analysis, and these results will be compared to looks at trends.
Survey participants also will be given the resulting report. As before, the survey uses ratios and percents for anonymity and no company names are ever mentioned. A summary of the findings will be published in PLANT ENGINEERING .
To participate, download a PDF version of the survey, which can be found atkmb-mail@hotmail.com.
MHIA touts growth, alliances at conference
It was a positive message coming from the Material Handling Industry of America during its press conference, held Tuesday March 28 as part of the NA 2006 trade show at Cleveland’s I-X Center.
MHIA executive chairman Brian McNamara, president of Southworth International Group, said there were positive signs for the industry.
“Life has been good,” said McNamara as he cited growth the industry has seen over the past three years. In 2005, new orders grew at an annual rate of 28.1% to close at $23.6 billion, and shipments grew 25.6%, closing at $21.9 billion. Imports grew at an annual rate or 26.3% to $4.8 billion, while exports grew 32.4% to $3.2 billion, and net trade value grew at an annual rate of 15.2% to $1.6 billion, he said.
“With the unfulfilleds, with the imports, with the exports, if you add it all up, you get $23 billion,” McNamara said.
McNamara said growth will continue, but decelerate. New order growth should slow to between 11% and 13% in 2006 and drop again to between 3.5% and 5% in 2007, McNamara stated.
“We’re going to continue to grow, but we’re going to continue to grow at a decelerating pace,” McNamara said. “It’s a pretty strong picture as we look out ahead.”
MHI chairman John Nofsinger offered an overview of the organizations affiliated with MHIA. Of note are the College-Industry Council on Material Handling Education (CIC-MHE) and the Material Handling Education Foundation, Inc. (MHEFI). Both groups have worked to support students in preparation for careers in material handling and logistics, and to support workers currently in the industry.
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