Pile on the SavingsThis article includes Online Extra Material.
Measurements from automation and control sensors and attached equipment—such as pressure, temperature, vibration, and acoustic and fluid levels—have been collected on clipboards for years to help schedule maintenance. With enough analysis, formal or informal, predictive maintenance can take over for reactive or scheduled maintenance.
AT A GLANCE
Save assets with predictive maintenance
Strategic knowledge, not just uptime
Integrate maintenance, controls
Hardware, software, networks feed maintenance
Sidebars: Intel says predictive maintenance is key to uptime Better by design: Toolholder extends life
Measurements from automation and control sensors and attached equipment—such as pressure, temperature, vibration, and acoustic and fluid levels—have been collected on clipboards for years to help schedule maintenance. With enough analysis, formal or informal, predictive maintenance can take over for reactive or scheduled maintenance. Even so, at some facilities there’s the magical “third-shift Larry,” who’s been with the company forever, serving as a roving sensor, monitor, and alarm. Just by resting a hand here and turning his head to listen there, he seems to figure out when something needs attention.
As such artful intrinsic knowledge gives way to more replicable, consistent, and interconnected processes, organizations are finding new software-based analytical methods for sorting through inputs, creating models, and notifying users well in advance of exactly what maintenance should be performed and when. That’s not only attainable, but with some out-the-box thinking, capital can be moved from one area to another, and maintenance and controls budgets treated as respected assets. Information can be collected with handheld data collection devices or industrial networks (wired or wireless) to expedite analysis. In some cases, real-time, closed-loop responses are possible.
Entire companies or divisions of companies devote themselves to the area of providing maintenance and related optimization. These areas encompass hardware, software, processes, and network communications applied at the weakest points or plant-wide. A layer of software can provide an overview of multiple disparate systems to deliver the right information as needed.
Parameters of influence include:
Process design and material flow, amount of flexibility a line needs, frequency of product changes, and throughput;
Human factors, such as staffing levels and expertise;
Connectivity (including equipment that phones home to the central office or to the manufacturer to state its needs);
Equipment design and age (newer products can have longer-lasting materials, fewer moving parts, and components less likely to fail; and
Visibility (data from disparate systems and devices analyzed over time can provide information to various areas within the organization, helping to optimize decisions at multiple levels).
Benefits abound. Predictive maintenance can, according to U.S. Department of Energy’s Pacific Northwest National Laboratory: increase component operational life/availability; allow for preemptive corrective actions; decrease equipment or process downtime and costs for parts and labor; improve worker and environmental safety and morale; and save energy.
Proactive or reactive?
Are you among the enlightened? Less than 10% of manufacturing facilities practice a proactive maintenance strategy through predictive maintenance; the vast majority is reactive or planned maintenance, estimates Richard Schiltz, a director for the Integrated Condition Monitoring Solutions business group of Rockwell Automation Global Manufacturing Solutions division.
Predictive maintenance significantly reduces maintenance expense and increases operating performance, Schiltz suggests. Common means of analyzing rotating machinery include vibration measurement and oil analysis, including moisture in lubrication. Online systems can integrate with the control system, work on the same network, acquire data, and provide trending information. Rugged, distributed modules can be located close to the process, near the sensors that gather information. Schiltz advises connecting critical assets first; critical doesn’t have to mean large or costly. If a failure occurs, the process is significantly impaired or stopped. In a semiconductor facility failure of just a vacuum pump can cause a catastrophic amount of damage to product.
Matt Dentino, who covers the software side of Entek products, says that an effective system will take information, provide analysis, determine course of action, and send notifications through alarms or e-mail about equipment conditions. A system may also feed an enterprise maintenance management system to generate work orders, the human-machine interface, or the control system in closed-loop operations. Economic pressures are encouraging wider interest and adoption, he adds.
Tying it together
Maintenance and controls operate with many hardward/software devices and systems to acquire and relay information. Collaborative MIMOSA and OPC Foundation efforts air to standardize data types, structures, and protocols.
To help make connections among diverse systems happen, several industry organizations are banding together to unify data types and structures, in essence to ensure everyone’s speaking the same language, according to Alan T. Johnston, president of MIMOSA, an operations and maintenance open systems alliance. To avoid future Towers of Babel, they’ve collaborated with OPC to develop OpenO&M, a coordinated set of open standards for operations and maintenance information. Recently, MIMOSA, OPC, and the ISA SP95 Committee have announced formation of a Joint Working Group intended to harmonize their standards in the manufacturing domain.
“What we’re doing is filling some historically natural information gaps between real-time and transaction-oriented systems… We have a strategy based on collaboration, where we concentrate on our core Asset Resource Management (ARM) competencies while collaborating with other appropriate organizations to enable the real-time enterprise incorporating plants, facilities, and fleets,” Johnston says.
Data to information to savings
While information from controls and maintenance systems is important, information needs to fit into a broader context, agrees Bert Mijten, product manager, Real Time Production Intelligence, ABB Inc. “We have to move toward real-time production intelligence systems that monitor controls and equipment, looking for losses in manufacturing production operations, loading, scheduling, supplies, quality, and equipment availability.” Manual data collected, if it ever sees light of day, too often lacks the speed to do the organization any good, no matter what the agreed-upon key performance indicators (KPIs) are.
“Measuring in real time and combining that with root cause analysis provides an opening to the hidden plant and hidden capacity,” says Mijten, such as when a CNC machine, independent of the operator, monitors and notifies the warehouse when a new tool is needed, saving time and energy.
In one example, a growing tractor manufacturer revised estimates for uptime higher, decreasing a planned capital purchase from 30 to 25 CNC machines, a $6 million savings. In another case, correcting a machine flaw by identifying a pattern of unneeded shutdowns and calls to maintenance saved 3,000 production hours a year.
Data patterns, alarms
Software providing some SPC/SQC function in the background can analyze data deviation patterns. Paul Rogers, systems engineer at Elk Corp. roofing shingle manufacturing plant, saw this function in action recently when pump pressure fluctuations told of a pump failure or blockage in an asphalt line at the plant.
“The idea is to receive and react to the alarm, e-mail, or page before it becomes a show-stopper,” says Rogers, who moved to controls from the IT department. He smiles slightly when he says he now listens to motors instead of desktop computer users. In one situation at Elk Corp., the software is used to create an alarm to check or change out wheels that are part of the catching mechanism causing increasingly frequent jams in shingle catchers (after lamination and before bundling and palletizing). In another, monitoring the location of a painted-on nail line maintains quality.
Increased throughput—without counting benefits like quality and satisfaction—results in $45,000 in annual savings, Rogers says, compared to cost of $20,000 for the site implementation of an SPC system, which included SPC Pro from Wonderware. Other products, such as Wonderware Industrial SQLserver and InTouch HMI also help.
Dashboard performance
People in operations, maintenance, and engineering, as well as the plant manager, all understand the need to move away from reactive decisions and the way things have always been done, says Neil Cooper, a director for Avantis asset management, after recent interviews Invensys conducted with 75 people at manufacturing firms.
“All said their bottom-line focus now is how to drive up plant contribution to the business,” Cooper says; the challenge lies in turning data into knowledge. Applications fire tons of data but lack the infrastructure to move data across departments for meaningful decision-making. As companies have downsized, they often lost those most able to decipher. This problem will worsen as a vast retirement bubble moves over the U.S. and Europe in the next 5-10 years.
Further, “Intelligent technologies are great, but if instruments deliver 27 kinds of information without any context, what good is that?” he asks. It adds complexity without value, Cooper explains, so vendors need to offer knowledge services, interpret readings, create a decision tree and rule-based approach to deliver information in a dashboard approach where needed and when.
Remote diagnostic data
Ability to easily and quickly diagnose a problem adds value. Dave Skelton, Phoenix Contact director of automation, says his company’s Interbus-related products include diagnostics, therefore they’ve pursued that path with other network-related products, as the protocols allow. A shortcircuit for instance, can trigger hardware to send an error code; HMI or an OPC server could display, message, alarm or send the info to another system. Most diagnostic features are used for reactive maintenance, Skelton admits; in-depth process knowledge can help in establishing a setpoint that can alarm as a component shows signs it’s starting down the path to failure, but still is within allowable limits, in time for appropriate dispatches to maintenance and operations departments.
In automotive applications, Phoenix Contact Diagnet software is bundled with Iconics Genesis32 visualization for use in body shops and final assembly. For instance, Skelton says, when light intensity of fiber-optic communications to a robotic arm starts to degrade, cable maintenance is needed prior to unscheduled downtime. Motor starter currents, power supply output, and temperature sensor outputs also can signal need for pending maintenance.
Put data to work
Remote I/O modules, PLCs, and industrial networks, especially those that support diagnostics, can report maintenance needs to the user, through the HMI and/or via an Ethernet module than can e-mail or page, says Bill Cummings, Omron Electronics market manager, Food & Beverage. Monitoring the timing between relays closing could signal a problem with a hydraulic cylinder or actuator. Any threshold exceeded, appropriate to the device monitored, can send a message or alarm.
For instance, voltage changes and communication errors can tell of a number of conditions, depending on context, such as an eminent cable break. Newer HMIs show the alarm, and lead the operator through visual troubleshooting and start-up screens, similar to copy machines now, Cummings says. Software eventually will interconnect all data available, providing even more intelligence.
So how’s your facility stack up? Hopefully you’ll be able to integrate and automate controls and maintenance monitoring and alarms to pile on the savings—and intelligence—for your organization.
Intel says predictive maintenance is key to uptime
For Intel, a few hours of downtime can result in millions of dollars in losses. Incorporating predictive maintenance as a key component of its uptime strategy, the company’s 24 manufacturing, testing, and assembly sites have collectively achieved a healthy 99.6% uptime.
“The reality is that replacing a fan or pump motor is a fraction of the cost of having a fabrication line down for any amount of time,” said Mick Flanigan, a predictive maintenance program manager and project leader at Intel’s Northwest Regional Operations facility. “If production is down for even one or two hours, the lost revenue would far exceed the cost of a replacement motor, or any other ancillary component.”
Historically, Intel’s facility maintenance department has minimized downtime using a sophisticated preventive strategy that incorporates redundant machines to protect critical facility systems. For example, on its water and chemical treatment systems, Intel may employ three pumps on a single skid. The first operates the equipment, the second sits in hot-standby mode and the third serves as a backup to the second. If the primary pump fails, the second will go online immediately. Although functional and fairly reliable, this “uncontrolled” switchover approach is not ideal, because even a minor disruption or “hiccup” in the switchover can cause a slight pressure or temperature fluctuation, resulting in lost production and product waste.
Project at a glance
A rundown follows of Intel’s facility in Hillsboro, OR.
Technicians use Entek Datapac handheld data collectors to gather equipment data. With a total of 108 routes, each technician is responsible for two or three routes, averaging three hours each.
Information gathered using handheld data collectors can be downloaded directly into Emonitor Enshare software from Rockwell Software, which can then be shared among various production sites. Emonitor Enshare software analyzes equipment condition data, measures the data against preset parameters and provides advance warning of equipment abnormalities and potential points of failure.
Ninety-four percent of the Hillsboro facility’s equipment is now involved in the predictive maintenance program. Intel has since identified several hundred major vibration problems, helping to avoid thousands of dollars in production downtime.
As the program expands across Intel production sites, the team continues to add new enhancements and predictive technologies designed to further drive down costs—while increasing Intel’s output and chip performance. Also on the horizon is the gateway from Enshare to MRO’s Maximo and the implementation of a wireless solution to further remove the workload from technicians.
For the full story of Intel’s advances in predictive maintenance, see this cover story online, at
Better by design: Toolholder extends life
Upgrades can reduce downtime and maintenance simply by better designs. Mapal Head Fitting System (HFS) toolholder line, is an example said to increase tool life up to three times with a design that reduces runout. Concentricity inaccuracies can put chipload on a few teeth of the tool. Adding face contact to a taper connection is said to provide longitudinal positioning accuracy equal to one-piece tools. Using HFS, manufacturer MTU Aero Engines increased reaming tool operation from 2,000 to 6,000 pieces per tool.
Online Extra for March cover story
Pile on the Savings Integrated controls and maintenance allow hands-off monitoring
Mark T. Hoske, Control Engineering
Cover story for Control Engineering March 2004 edition includes the following Online Extras.
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Intel’s predictive maintenance strategy boosts equipment reliability, minimizes downtime Intel Corp. has stepped up its predictive maintenance strategy to boost equipment reliability and minimize downtime. Information sharing across multiple facilities leads to further cost-savings advantages. Benefits include identification of several hundred major vibration problems, helping the company avoid estimated lost-production costs of more than $1.4 million in a recent calendar year. Maintenance has shifted to as-needed, instead of “whether it needs it or not.”
Moore’s Law– coined by Intel cofounder Gordon Moore – holds that microprocessors will double in power and halve in price approximately every 18 months. For more than three decades, Intel has adhered to this axiom as it pioneered key technologies that have helped propel the computer and Internet revolution.Intel’s success over its history – and particularly in the last 10 years – can be attributed in part to aggressive product development. Economic conditions today require the ability to produce more powerful microprocessors at lower prices, while maintaining a high level of profitability.Beginning in the late 1990s, Intel implemented aggressive programs aimed at reducing costs and increasing output through investments in new manufacturing and assembly technology and processes. In semiconductor manufacturing, a few hours of downtime can result in millions of dollars in losses, so success is measured by uptime across the company’s 24 manufacturing, testing and assembly sites. Unlike most manufacturers, the cost of equipment repair or replacement compared to the cost of lost production is minimal for Intel. As a result, maintaining production is a top priority for all — from engineering and assembly to facility maintenance.
Since 1998, Intel’s maintenance department has gradually embraced predictive maintenance as a key component of its uptime strategy. Using integrated condition monitoring tools from Rockwell Automation, Intel has designed and implemented a comprehensive program that allows it to effectively monitor, analyze and track equipment performance– observing operating conditions locally as well as remotely, across multiple production sites. If any part of manufacturing fails, such as power supply, HVAC or water and chemical treatment systems, production could come to a rapid – and costly – standstill.
“The reality is that replacing a fan or pump motor is a fraction of the cost of having a fabrication line down for any amount of time,” said Mick Flanigan, a predictive maintenance program manager and project leader at Intel’s Northwest Regional Operations facility. “If production is down for even one or two hours, the lost revenue would far exceed the cost of a replacement motor, or any other ancillary component.”
Historically, Intel’s facility maintenance department has minimized downtime using a sophisticated preventive strategy that incorporates redundant machines to protect critical facility systems. For example, on its water and chemical treatment systems, Intel may use three pumps on a single skid. The first operates the equipment, the second sits in hot standby mode and the third backs up the second. If the primary pump fails, the second will go online immediately. Although functional and fairly reliable, this “uncontrolled” switchover approach is not ideal, because even a minor disruption or “hiccup” in the switchover can enough of a pressure or temperature fluctuation to cause lost production and product waste. With a preventive strategy, equipment repair and replacement is carefully planned and timed to avoid process interruptions or unwelcomed deviations in process parameters.
“Our primary goal is to make our preventive maintenance work invisible to engineering,” Flanigan said. “If engineering doesn’t have to worry about reliability issues and can focus on improving the manufacturing process, we have done our jobs.”
As part of the predictive maintenance program, technicians use infrared scanning, vibration, temperature and oil-composition analysis tools to monitor machine conditions and gather information necessary to identify when a controlled switchover is warranted. According to Flanigan, the majority of Intel’s maintenance activities will always be preventive-based, but they are now using predictive maintenance tools to flag conditions in the field well in advance of a failure.
“In the past, we would tear a machine apart without any data that could help identify the specific nature, extent or cause of the problem,” Flanigan said. “As a result, the job scope was often more extensive and costly than necessary. Now, we’re able to pinpoint the problem much quicker and attack it directly.” Technicians at Intel’s facilities in Hillsboro, OR, use Entek Datapac handheld data collectors from Rockwell Automation to collect equipment data weekly or monthly, depending on the type of equipment. Each technician is responsible for two or three of the 108 routes. A route takes an average of 3 hr to cover. During first-quarter 2003, the Hillsboro facility logged 450 data collection hours.
Prior to the program, technicians would record data on a clipboard, and then manually input the information into a system. Now, after collection, data can be automatically downloaded from the handheld data collectors directly into an analysis system. Rockwell Software Emonitor Enshare Enterprise Asset Health software analyzes the data, measures against preset parameters, and provides advance warning of equipment abnormalities and potential failure points.
When your job is to prevent certain events from happening, going unnoticed is usually a good thing. But, for Intel’s maintenance department, this “invisibility” also presented a unique challenge: justifying and demonstrating the value of its predictive maintenance program. For example, how do you measure the cost savings of a potential event that was ultimately prevented, but never happened? Or, why is it important to monitor or sustain equipment when it’s cheaper to replace it? To illustrate the value of the department’s predictive maintenance program, Flanigan and his team worked to develop a solid business case for the program. They started by using real application examples and carefully documenting uptime performance results.
“To a large degree, we are dealing with an intangible when we’re talking about the potential of downtime events and the value of loss avoidance,” Flanigan said. “In the end, after developing a justification using two separate methods, we were able to develop both hard, tangible results, along with significant‘soft’ cost- avoidance projections.” Flanigan’s team used much of the same cost projection and performance data to show other Intel production sites the value of a predictive maintenance program. But selling the idea to other facilities was challenging–some “old school” technicians at other facilities felt predictive maintenance would be a waste of time. To convince the skeptics, Flanigan used metrics from the Hillsboro facility to validate the program’s results. At the same time, to build support among potential supporters, his team developed customized training courses based on the program’s vibration-analysis technology and capabilities. The strat-egy worked, and Flanigan and his team ultimately succeeded in persuading other sites to join the program.
“With the work we did in Hillsboro, people across the maintenance organization were able to see the real cost savings, as well as the long-term strategic benefits,” Flanigan said. “Once our technicians used the tools and saw that they really worked, they were able to dramatically cut the time they spent in the field chasing problems. It let them focus their energies on more pressing issues.”
As the predictive maintenance program spread across sites, it led to the selection of a variety of different software for similar and varying purposes. Flanigan co-chaired an internal group called the Vibration Analysis Working Group, which searched for a way to share information across sites. The group also worked to find one software package that could be used universally among Intel facilities. The Vibration Analysis group found Emonitor Enshare capable of supporting most Intel condition-based monitoring data while also sharing information across disparate Intel sites. With database storage capabilities, the Enshare system also served as a central repository for the information gathered from the assembly sites. It was used to examine equipment lifecycle trends and determine if common failures occurred on specific types or models of equipment.
At Intel’s Hillsboro site, where the predictive maintenance program began in 1998, approximately 4,000 pieces of equipment (94% of qualified equipment) are now monitored. Since the program was implemented, Intel has found countless minor vibration issues and identified several hundred major vibration problems, helping the company avoid prolonged production shutdowns. More specifically, Intel Oregon realized a five-to-one return on investment. The program helped the company avoid estimated lost-production costs of more than $1.4 million in 2002 alone. Intel Oregon has not had a catastrophic equipment failure since early 2002. Additionally, the technology has allowed Intel to evolve into a more predictive-based maintenance organization. Instead of reacting to failures, Intel can make informed decisions based on performance data. It can now provide “real need” maintenance instead of calendar-based, “whether it needs it or not” maintenance.
Today, Intel technicians use Datapac data collectors to gather information from more than 8,000 pieces of equipment at several different facilities. Fourteen of Intel’s 19 global production sites are either already part of the program or plan to enroll. Included are facilities in Colorado Springs, CO; Hillsboro, OR; Rio Rancho, NM; Ocotillo, AR.; and Santa Clara, CA– as well as international locations in China, Costa Rica, Ireland, Malaysia and the Philippines.
Areas of expansion have included acceptance testing for newly purchased equipment before and after installation, prior to warranty start dates, to ensure it meets Intel’s strict manufacturing standards. If new equipment is brought online without meeting Intel’s specifications, process abnormalities can and do occur, causing a “hiccup” in the manufacturing process– a delay or error not caused by wear and tear on older machinery. For example, even the slightest vibration can shift chip-making equipment calibrations. By testing equipment against written specs for vibration and sound, Intel is able to verify that machines meet standards before they are installed. Today, nearly three-fourths of the predictive maintenance program’s condition-monitoring efforts are focused on acceptance testing.
“Now, we’re not tagging equipment as ours until it meets our vibration criteria, our infrared criteria and many other processes as well,” Flanigan said. “When we bring this equipment into our facility, we have better assurance that it’s going to last beyond the warranty. Surprisingly, this is the area of the program where we’ve seen our biggest hard cost savings.” As the program expands across Intel production sites, the team continues to add enhancements and predictive technologies designed to further drive down costs, while increasing Intel’s output and chip performance. Also on the horizon is the gateway from Enshare to MRO’s Maximo and the implementation of a wireless solution to further remove the workload from technicians. And, even as the validity of Moore’s Law continues to be tested and debated by industry pundits, the maxim continues to fuel Intel’s vital progress and investment in fabrication facilities, process technology and employee ingenuity.
Partnerships, information software extend controls, maintenance efforts Honeywell Process Solutions’ https://www.acs.honeywell.com partnering agreements help relay information from devices into knowledge-based systems, such as Honeywell’s Experion PKS (Process Knowledge System) and Asset Effectiveness Solutions. Partners include Dresser Flow Solutions Masoneilan, Endress+Hauser, Flowserve Flow Control Division-Valtek, Honeywell Industrial Measurement & Control (another division within Honeywell) and Krohne, according to Honeywell’s Dick Verville, PKS Advantage program manager.
R.L. (Rick) Gorskie, Global commercial and operations manager for Honeywell @sset.max, told Control Engineering that the business focus is on increasing return on assets, increasing plant productivity, reducing operating assets, and extending the lifecycle of existing assets. Operations and maintenance areas have the greatest potential to save money. In most facilities, Gorskie says, it costs three to five times as much to fix something on an emergency Saturday night shutdown compared to an orderly shutdown. “Open systems are not enough,” Gorskie says, “It’s what you do with the information once you get it.” Verville adds that moving from 95% to 98% availability could add $100,000 to several million dollars per year to the bottom line.
Honeywell Equipment Health Management Solutions suite includes @sset.Max Alert Manager, also part of the Control Performance Solutions suite, and IntelliScout; @sset.MAX Alert Manager, designed to automate decision support, provides a means of identifying and solving asset problems into symptoms and faults. IntelliScout is the first fully automated method of modeling equipment performance using advanced empirical models. It automatically detects and alerts operators or other appropriate personnel about changes in operating conditions, sensor degradation, and performance changes for a variety of equipment types.
Recently introduced Business.Flex PKS 130 is a suite of software solutions that deliver significant and sustainable production performance improvements for process industries. Release 130 of Business.Flex PKS unifies business goals and production automation to improve decision-making and execution, help-ing users achieve more reliable operations, and increased manufacturing flexibility and business optimization. With Business.Flex PKS, companies typically increase production by 3-6%, while decreasing costs 1-2%. The software integrates with Honeywell systems, such as the Experion Process Knowledge System (PKS), next-generation automation system, as well as TPS, and third-party systems. Honeywell says the solution drives business targets to optimum levels, allowing operators to more effectively make use of whatever platform they have, and execute plans and schedules in line with business objectives. Release 130 also works with Uniformance PHD, Honeywell’s advanced process historian system for plant information.
Maintenance software caters to calibration MRO Software’s Maximo 5 Pharmaceuticals solution–an extension of the MRO’s Strategic Asset Management software, provides capabilities including enhanced calibration, full support for electronic records and signatures (U.S. FDA 21 CFR Part 11) and validation capabilities for companies regulated by the U.S. Food and Drug Administration (FDA). Maximo 5 Pharmaceuticals is part of MRO Software’s Industry Solutions program, which delivers solutions to address industry specific requirements for key vertical markets.
Enhanced workflow and e-signature capabilities support the FDA’s 21 CFR Part 11 requirements; help keep all maintenance activities on time, on plan and on budget; and provide an audit trail for compliance requirements. Features include a set of templates to help reduce the time and cost it takes to validate Maximo and a wireless calibration module to provide mobile employees with the ability to record compliance activities in real-time, with handheld computers. MRO says flexibility provided by a Web-based platform delivers significant cost savings over older, capital-intensive, client-sever systems and provides security and scalability. Flexible architecture allows the software to interface with other enterprise applications providing a comprehensive view of as-set management.
MRO Software says it currently provides asset management solutions for most of the worlds’ top pharmaceutical companies, six of which deploy Maximo as their global standard. MRO Software, based in Bedford, MA, says it’s “the leading provider of strategic asset management solutions.” For more,
How much? Here’s a sampling of numbers on preventive maintenance For any machine-tool or plant-floor application, maintenance should be considered as part of the lifecycle cost. Here are some numbers related to maintenance.
A CMMS [computerized maintenance management systems] Best Practices Benchmarking survey, topic of Feb. 24, 2004, paper at National Manufacturing Week, showed that more than 60% of 650 companies showed lack of return on investment in their CMMS implementation. Cmmscity.com helped do the study
Preventive maintenance can save 8-12% in energy costs, according to Electric Power Research Institute.
Acronyms, terms for maintenance and controls Knowing acronyms and terms related to maintenance and controls aids understanding. Here are some.
CBM condition-based maintenance CM&D condition monitoring and diagnostics of machines CMMS computerized maintenance management systems (or software) DT downtime EAI enterprise application integration EAM enterprise asset management FFT fast fourier transform algorithm helps identify repeating signals by analyzing frequency spectrum of an input signal. IAM industrial asset management Maintenance costs include parts, labor, and can also incorporate costs of down time. MIMOSA machinery information management open systems alliance: a not-for-profit trade as-sociation dedicated to developing and encouraging the adoption of open information standards for operations and maintenance. MRO maintenance, repair, and operations; or maintenance, repair, and overhaul MTBF mean time between failures MTTF mean time to failure O&M operations and maintenance—often separate areas need to talk more; spending a little in one could save a lot in the other. ODHS operational data historian systemsOvertime labor costs that can be associated with unplanned repairs PAM plant asset management systems PLC programmable logic controller PM or PDM predictive maintenance PMO plant maintenance optimization Predictive anticipate before it breaks; parts can be ordered as needed; uptime is preserved. Reactive fix it after it breaks; downtime, capital and personnel costs are high. RCM reliability centered maintenance ROA return on assets ROI return on investments RT real time, in maintenance terms, it can mean diagnostics that pinpoint what needs attention, notify and even schedule resources. Scheduled, calendar-based maintenance , based on past or manufacturer-anticipated wear. Less disruptive than reactive, but because it’s based on historical, rather than actual wear, it may include unneeded work. SPC/SQC statistical process control/ statistical quality control TCO total cost of ownership (lifecycle cost, beyond initial capital investment) TPM total production maintenance XML extensible markup language
Additional reading…
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