The primary benefits gained from a well-implemented maintenance management system include improved overall maintenance efficiency, compliance, safety, and plant availability. For Alliant Energy’s plant personnel to extract maximum value from the CMMS investment, the integrity of plant equipment data needed to be very high.

Whether embarking on a new implementation or a re-implementation, building a reliable knowledge base of equipment and engineering data demands significant man-hours, specific skills, timing, and project teams that are often beyond the ability of a plant to support in its entirety.

Need to revise master equipment list
When the Burlington (Iowa) Generating Station, a facility owned and operated by Interstate Power & Light, a division of Alliant Energy, began evaluating the process required for the implementation of a CMMS, it turned to Black & Veatch, a global engineering, construction, and consulting company, to assist with project deliverables. “To achieve the maximum return on our assets and increase shareholder value, we needed to implement a CMMS at our facility,” said Ken Wilmot, Burlington plant manager.

“ In this period of volatility within our industry, it is paramount that we understand and predict our equipment failures and the corresponding impacts on load and revenue to our facility.” To achieve the desired outcome, one of the first steps was to update the critical plant drawings as well as revise the master equipment list.

To support Alliant Energy’s CMMS and lockout-tagout implementation projects, Black & Veatch assisted with the re-establishment of databases for plant equipment—nearly 7000 records. With teams of specialists walking down each plant system, the project also updated critical piping and instrumentation drawings (P&ID) and electrical one-line drawings and delivered them in full vector AutoCAD format.

Through improved access to complete, reliable information, and improved work processes and technologies to maintain it, this effort has increased plant operation and maintenance (O&M) efficiencies and safety for plant personnel.

Kickoff meeting vital to project
Project guidelines were developed during the project kickoff meeting. This is a critical stage to establishing mutual expectations—introducing project engineers to plant staff, establishing daily lines of communication with plant leadership, and collaboratively establishing the in-scope and out-of-scope boundaries.

In this case, 3 days of project scoping discussions were held. All standard conventions were documented, including abbreviations, equipment naming rules, equipment numbering schemes, plant equipment classes, system names, plant orientation, database field widths, system lists, location ID, and physical location.

This was followed by a one-day trial run, after which the project guidelines were issued to the project team. Trial run results generated a lot of useful clarification issues and provided the first opportunity to measure project team productivity. Early returns revealed that nearly 80 pieces of mechanical equipment were surveyed per person, per day, and this number quickly rose to more than 120 pieces. Electrical equipment collection rates were much higher, as this equipment is more closely arranged and repetitive.

Significant consideration was given to project safety. Data was collected from grating level, or 6-ft ladder height. It was agreed that field staff would not be allowed to open any equipment enclosures or electrical or control panels.

Equipment specifications
Establishing plant equipment classes, or specification templates, was a separate project by Alliant Energy that provided the team with more than 100 equipment types and attribute sets for each. These were to be the basis for matching equipment data to values, conforming to a standard attribute list across all equipment.

“ We needed to identify as much equipment, and equipment history, as possible within our facility,” said Patrick Kelleher, Burlington maintenance systems engineer. “With the fleet using the same general equipment naming and specification templates, we are able to report on what type of equipment works well and what types do not.

“ I can see at a glance if a 25-hp motor, in a particular situation, is not doing well across the fleet. We can look at the data, make educated decisions, and plan accordingly. Additionally, the fleet now has greater accuracy in the information used for centralized stores and procurement.”

With well-designed field forms, reference lists of equipment templates, and naming rules, the field staff walked light, had rugged low-cost tools, and captured data quickly—with no lighting issues, no reboots, and no lost data. Since field work requires the skill level of domain specialists who understand the parts, equipment, systems, and safety issues, and for the cost that this implies, it was important that once data collection started there would be no technical delays.

When the data was delivered and training conducted, the staff was working on a complete equipment database of nearly 7000 records of data. “The trust in the new system was immediate,” Kelleher said.

Since Alliant was tackling two projects at once—the CMMS and a new lockout-tagout system—the scope encompassed collecting all equipment nameplate data for all potentially energized equipment, including mechanical, electrical, steam, and hydraulic. In some cases, skid mounted systems were specified as one asset, but routinely included the main breaker, vents, drains, and isolation valves as unique assets.

Options tried in building database
Early in the project, various approaches to building the database were tried. Most were centered around attempts to use in-house labor, a decision that inherently has a schedule impact to project deliverables.

Alliant Energy’s first attempt to create the equipment list was a drawing takeoff exercise in which a maintenance professional, who was tied to a desktop, populated a database with available drawing details such as equipment name, asset number, P&ID number, drawing coordinates, and location ID, among others. In many cases, this can be an excellent starting point, but plant drawings can miss important assembly and subassembly details. They also lack the important OEM nameplate, procurement data, and location details.

“ However, having a pre-populated database that can be loaded onto a handheld computer is an excellent option when there is sufficient pre-existing data that merits this approach,” project manager Andy Carroll said. Data collection performed using handheld computers and pen and paper are both appropriate methods depending on circumstances and cost.

The ultimate decision is primarily driven by whether the project is a data validation exercise or one of data creation. In the case of the Burlington station, existing databases were incomplete and not trusted. Therefore, existing data would be used more as a quality assurance (QA) check, rather than as a data source to prepopulate the new equipment list.

One other option that was considered, but dismissed, was for the O&M staff to collect the equipment data during their downtime, an option that is most often very slow and disjointed. In these times of lean organizations, this can be an empty promise because staff rarely has any downtime. The bigger dangers include the impact to overall project schedule and the staff response to using a system that seems to have some good data, as well as some unvalidated data.

The longer this activity takes, the less QA tends to stay with the effort, and the likelihood that labeling and naming rules are not followed increases. Alliant decided that careful development of data rules was required up front, followed by a rapid execution of information gathering, QA, and final delivery.

For this project, it was decided that field personnel would be provided hard-copy field forms and use pen and paper to collect all new data. Low-cost data entry services were used to transcribe the data using a simple but powerful application that Black & Veatch and Alliant Energy co-developed. Ryan Deschaine, Black & Veatch programming engineer who also managed the data entry activities, added some QA and data entry monitoring routines.

The more important features included ones that constrained any assumptions that a data entry clerk could make. For instance, when a clerk determined that there was missing data or unreasonable data, the instructions were to flag the record, create a trouble log entry, and move on. The log then was reported back to the field for investigation or for reconciliation during final punch list activities.

Drawings converted to AutoCAD
A second major deliverable for this project was the conversion of approximately 80 engineering drawings to full vector AutoCAD format. Considering the age of the plant and the quantity of physical changes that had been made over the years, the plant staff was not sure how much it could afford for drawing updates, but knew there is no better time to capture as-built plant information than when a team of specialists is walking down each plant system.

However, converting 30,000 drawings to full vector format is an exorbitant expense. Therefore, a compromise had to be made. In this case, the AutoCAD conversion project included all P&ID and electrical one-line drawings. All remaining drawings continue to be scanned to either a TIF file or CAD overlay. All files are managed then in the corporate document management system.

Considering that the database is the most critical issue when implementing a CMMS, it is paramount to understand that the database is only as good as its plan for ongoing development and upkeep. “Having a good database to start with is important; however, as maintenance is performed and changes to the operation occur, it is just as important to revise any affected documentation, including engineering, OEM, and operational procedures, and then change the CMMS database accordingly,” Kelleher said. “Drafted prints are the link between the CMMS database, plant staff, and engineering.”

The database is comprised of many slices of information—equipment data (current and historical), preventive maintenance tasks, inventory (including critical spares lists and bills of materials), job plans for work orders, and links to other data sources. “We developed a library at our site so we could accurately track our documentation,” Kelleher said. “In that effort, we scanned 5 GB of documents.

“ In our CMMS, we have the ability to link these documents to the respective levels of the database. This not only will cut down on general research time, it will aid in finding fast answers about equipment in question. One of the most enjoyable parts of implementing a CMMS is taking the pass-down knowledge and handwritten practices and transferring that knowledge and information into formal PMs and routes, which are automatically generated, and seeing the old card file be transformed into daily, weekly, and monthly lube schedules.”

“ Based on the milestones and deliverables that were established for the project, Black & Veatch exceeded our expectations,” Wilmot said. “We are now well on our way with the implementation of the CMMS at the Burlington Generating Facility and have demonstrated the value of this type of partnering arrangement with others within the Alliant Energy organization.” MT

One of the most interesting areas of wireless networking in the past couple years has been the emergence of community Local Area Networks based on sharing network access using the 802.11b standard (commonly known as Wi-Fi or WLAN).

According to U.S. officials, more than 20 million people will be using wireless Internet access worldwide by 2007. Lufthansa, SAS, United, and Delta have already begun to turn their fleets of planes into large Wi-Fi hotspots. McDonald’s restaurants in New York, Chicago, San Francisco, and Canada are offering Wi-Fi to customers. Schlotzsky’s Deli restaurants also offer free Wi-Fi.

Cities such as New York; Long Beach, CA; Gainesville, FL; Athens, GA: and St. Louis, MO, have set up large outdoor downtown Wi-Fi Zones or Clouds where the Wi-Fi signals have a greater range than the typical 100-300 ft. This is largely an unplanned movement, working to share access for free or free with some sort of purchase. Even RV owners are choosing campgrounds based on free high-speed Wi-Fi access.

Paid Wi-Fi service providers include several major phone companies. Sprint is launching a service that will offer Wi-Fi access to customers across the country. Sprint’s PCS Wi-Fi Access network will include more than 800 public locations later this fall and 2100 locations by year’s end. SBC Communications Inc., the No. 2 U.S. local telephone company, unveiled a plan to offer a new Wi-Fi wireless Internet service to customers in 6000 locations over the next three years. AT&T and MCI also have big plans for Wi-Fi network services.

What Is Wi-Fi?
Wi-Fi, or wireless fidelity, is a term used generically to refer to any product or service using any type of 802.11 wireless networking protocols. Wi-Fi networks operate in the unlicensed 2.4 and 5 GHz radio bands, with an 11 Mbps (802.11b) or 54 Mbps (802.11a or g) data rate, respectively. Wi-Fi is popularly known as 802.11b. Apple Computer sells Wi-Fi cards as Apple Airport. Intel now includes Wi-Fi functionality with processors known as Intel Centrino.

The Wi-FI Alliance is a nonprofit international association formed in 1999 to certify interoperability of wireless LAN products based on IEEE 802.11 specification. Currently the Wi-Fi Alliance has 198 member companies from around the world, and 865 products have received Wi-Fi certification since the program began in March 2000.

To connect to a Wi-Fi hotspot, you will need a wireless/Wi-Fi enabled laptop or other Wi-Fi enabled device like the Palm Pilot or iPAQ handheld. Most recently manufactured laptops are configured for wireless and some may come equipped with a wireless adapter card. Otherwise, you’ll need to purchase an adapter card ($35-$90).

A Wi-Fi wireless connection allows you to do anything you would normally do from home or the office. You can surf the web, check your e-mail, or connect to your corporate network (be sure to use a secure VPN connection). Check the security details of any network you log onto.

There are several new web sites that make it easy to find the location of Wi-Fi hotspots. www.Wi-FiZone.com allows users to search a database of about 1600 hotels, airports, restaurants, and other wireless access points in 23 countries. www.wifi411.com is another popular directory. Free Networks offers a directory of free Wi-Fi hotspots.

Recently a collaborative effort launched between the University of Kansas’ Information & Telecommunications Technology Center and Kansas Applied Remote Sensing Program created an advanced wireless 802.11b mapping and network visualization method. This new procedure uses wireless network data collected from walking and/or driving scans, aerial photography, and interpolation techniques to create highly detailed network coverage and signal strength maps. Another Wi-Fi mapping site is the Atlas of Cyberspaces.

Unplug today and send us an e-mail from your local park Wi-Fi so we can let other MAINTENANCE TECHNOLOGY readers know how you use Wi-Fi to make your online experience more productive. MT

Previously, the online data reporting system for its boilers fed information to the boiler manufacturer’s headquarters. There, the manufacturer could anticipate maintenance and repair problems from the operation data. In turn, it could advise the customer’s local service representative of adjustments the customer should make on site. In addition, some adjustments could be made online from headquarters.

Now, Baylor’s on site boiler operations staff can receive feedback similar to what was formerly available only to the boiler manufacturer.

Need for usage trends
Baylor wanted the system to ensure an uninterrupted supply of process and heating steam for its campus of buildings enclosing 1.4 million sq ft. The director of facilities, Rock Morille, and project engineer, James Kisiel, wanted the benefits of the new feedback technology in addition to switching from firetube to watertube boilers.

“We like to know what is happening with our equipment so we can extend the life cycle, conserve on energy, reduce emissions, and operate in a safer manner,” Kisiel explained. Morille added: “This was the best and most efficient way for us to get the campus ‘usage trends’ information that we must track in order to comply with regulatory standards. For instance, it will be a good thing to see a trend for low water cutoffs. It also validates what we are doing.”

Baylor has to contend with greater restrictions from government regulatory agencies. Texas has mandated that Houston plants have continuous metering of their gas usage to ensure compliance. Kisiel commented that “one of the great benefits of our particular brand of watertube boiler is that it allows you to add sensing and measuring devices and record critical operating information which then is seen in the software package that organizes and displays the other measured points.

“ The monitoring system feeds back gas-related data in a number of forms (focusing the operator’s attention on total system performance). There is data on high and low gas pressure, how long the boilers actually run in high fire or low fire, fluctuations in flue gas temperatures, etc. This feedback from the monitoring system can verify that a plant is in compliance.”

Flame signal failure solved
Joe Regini, supervisor of the Baylor Central Plant, noted the new feedback system has already eliminated costly service calls. “Recently, I had a flame signal failure. It is supposed to read 5 V on the flame signal, but it did not.” The flame signal failure showed up on the boiler monitoring system’s day-by-day, 31-day report of data from the various signal, pressure, temperature, conductivity, and gas usage (square cubic ft/hr or SCF) monitors.

Regini was puzzled; “The boilers were operating perfectly, but I could not get a flame signal.” With the boiler monitoring system, the company has a choice: diagnose a problem or call the boiler manufacturer, who receives more complex diagnostic data—the “black box” information on the 4 sec before shutdown.

The manufacturer can select the reports or “signatures” on all the operating data related to steam pressure, flame signal, water levels, surface blow down valve, feed water pump, damper position, and conductivity sensor. The signature also shows the last 4 sec measurements of the scale monitor, temperatures, conductivity, mode timing, etc., as bar graphs.

Regini decided to call the manufacturer for a diagnosis. The manufacturer identified the flame signal connections as the source of the problem. The connections are in a little plug, similar to a headphone plug, and they were loose on the controller. “Once I plugged them completely in, they were fine,” Regini said.

Switch to watertube technology
Baylor’s decision to switch to newer watertube technology from firetube boilers evolved over time. As Baylor expanded, it increased its firetube boiler capacity to 2100 boiler hp. The 21st century physical plant that Baylor is striving to complete had to confront redundancy, capacity, regulatory, and space issues.

Morille and Kisiel evaluated conventional systems as well as systems differing from standard U.S. installations in order to find the best fit for the campus. “It became evident that if the performance and advanced computerized monitoring promised by Miura Boiler worked, it would offer substantial and measurable benefits to the campus,” Kisiel said.

Regini, who has been with Baylor for 15 years, felt the old firetube boilers were not meeting Baylor’s needs, “The firetubes take a long time to bring up steam pressure. If you start one from cold, it would take you at least an hour to an hour and a half to bring it up to steam pressure. We wanted an on-demand steam generator and we needed redundancy built into our system.”

To meet its on-demand steam needs, Baylor decided to switch to watertube boilers. According to Regini, “They only hold about 78 gal of water, each. So instead of heating a firetube boiler that holds thousands of gallons of water that I have to keep bubbling and hot all the time, I’m heating a smaller surface area and I’m directly changing the water into steam at a much more efficient rate. I’m running, virtually, a one-pass system. Water is coming in the bottom and going out as steam at the top. It is not sitting there simmering like a pot on the stove. With the watertube boiler, I could be cold-start to full-fire in less than 5 min.”

At the time of the switch from firetube to watertube, Baylor replaced 2100 bhp of firetube boiler capacity with seven 300 bhp watertube boilers, retaining one 600 bhp firetube boiler. The seven boilers fit in the footprint of two 600 bhp firetube boilers.

Daisy chain the boilers
The redundancy Baylor wanted is provided by a multiple installation (MI) terminal. The MI terminal daisy chains the seven boilers. It keeps track of run time, letting demand on the system determine how many boilers go on or off line. According to Regini, “When you have a multiple installation, the MI controller can start and stop each of the boilers at will, so I have the seven boilers in automatic standby mode.”

In the hard-wired daisy chain, one cable going from boiler to boiler transmits data. As many as 15 boilers can be included in the daisy chain.

The computer that formats and displays the data can be up to 3000 ft from the boilers. Thirty-one days of operating data can be viewed on the screen. The customer can see everything that is transmitted by modem to Miura headquarters, except for the event summary, that last 4 sec diagnostic view.

With the Miura Boiler Monitor (MBM), the customer can do basic troubleshooting on site. According to Mark Utzinger, vice president of the company’s USA operations, “For instance, if they get flame failure, their qualified personnel can make their own adjustment. But for analysis of the flame failure, they would call us. MBM would not tell them where in the sequence the boiler went down.”

Boiler data organized
The monitoring system is an intuitive approach to the organization of boiler data. Since an operator always wants a reminder of what a boiler’s settings are, the settings are grouped on one screen. Another screen pictures (in diagram form) the real time, current boiler status (valves on or off, temperatures, psi, and conductivity).

Once the current situation has been checked, the operator can monitor three aspects of boiler feedback—the alarms, cautions, and combustion—by looking through historical data to see if there are any indications of a development that needs attention. The alarms, cautions, and combustion histories are on separate screens. Alarms totals include various flame, water level, power, temperature, and pressure alarm totals. Cautions totals include times reminded about filters, blowdowns, softeners, batteries, sensors, etc. The combustion history records the time period’s cycles, low and high firing, blowdowns, and blower and pump cycles.

A scrolling screen shows the various signal, pressure, temperature, conductivity, and SCF monitors that are listed, day by day, for the prior 31 days.

And, finally, a monthly report screen provides a recap of the month with comparative data from the prior month, including a gas consumption graph when an optional gas flow meter is installed.

Regini finds the system easy and useful. “The screen information is user friendly. It is Windows based and gives me all the pertinent information that has to do with this boiler. It gives me a history; I can go back 31 days, I can go back 48 hours, and so on. It can tell me how many times the boiler has fired high fire and how many times it has fired low fire. The automation of the system makes it user friendly. All our operators (the boilers are manned 24 hours a day) are qualified to handle anything that comes up.” MT

Information supplied by Mark Utzinger, Miura Boiler, Inc., 600 Northgate Pkwy, Ste. M, Wheeling, IL 60090-3201: (847) 465-0001.

Important lessons were learned while developing and testing guidelines that a company might consider as it goes about implementing a new program—or expanding an existing one—to capture valuable undocumented knowledge from departing or other potentially unavailable workers. The guidelines consist of a process to follow and specific methods and tools to elicit, store, retrieve, and present valuable knowledge.

While the study (see accompanying section “Background of Research Project”) was done specifically in the energy industry, its results can be applied in any industrial setting.

Some of the lessons stemmed from development and testing of a process for capturing undocumented knowledge and for developing knowledge modules that contain the valuable knowledge for use by others.

Identify experts with valuable knowledge
An initial activity is to identify key employees who may be leaving their current jobs for whatever reasons, or may have knowledge so valuable that it should be available to others when they are absent due to travel, vacation, illness, etc. Methods to identify these key employees may range from simply asking managers to identify key employees with valuable undocumented knowledge to corporate-wide workforce surveys performed periodically.

Some of the factors to consider when identifying experts from whom knowledge may be elicited include:

• Individual should be recognized by his/her or other managers and peers as being the only expert about something of high importance, or one of only a few local site experts. Such an individual’s knowledge may be even more valuable if he/she is generally recognized as being one of only a few experts about something of importance within the entire company.

• Individuals with expertise in handling rare or infrequent events (e.g., repair of a unit that fails on average once every 10 years, or handling extensive repairs necessitated by a hurricane in areas not normally experiencing hurricanes) should be given serious consideration.

• Individuals with expertise for systems, etc., that are going to be replaced with different technology involving different skills should not be identified (e.g., “old” computer system being replaced about the same time the expert on that system retires).

Determine if experts are willing to provide knowledge
Following identification of the experts, it is important to determine if these workers are willing to permit their valuable tacit knowledge to be elicited and made available to others.

Many workers are willing—and in some cases eager—to share their knowledge. There are a variety of reasons for this positive response. For example, a worker may view it as an honor to be recognized as an expert. Others may feel an obligation to share their valuable knowledge with others in the company because of the benefits received during their careers—or because “it is the right thing to do.” Others may participate because their manager has asked them and made time available. It is simply “part of the job.”

It has been found, however, that some workers are not willing to share their expertise for a variety of reasons, including:

• Knowledge is viewed as an individual’s “intellectual property,” and may be used by that person as a basis for consulting work or another job.

• Fear of layoff because of the perception that the unique knowledge provides job protection, and making it available to others may increase vulnerability.

• Alienation against the company for some real or imagined reason (e.g., a lower-than-expected salary increase or being passed over for promotion).

• Belief that he/she does not possess any valuable knowledge, even though the person has been selected as an expert.

• Expectation that elicited knowledge will go “into a file cabinet and never be seen again,” thus wasting the time of the expert (may be based on previous experience at the company).

• Current work assignments leave no time available to participate in knowledge elicitation.

• Fear of loss of status because he/she no longer will be recognized as the expert in the organization.

Use existing resources to the extent possible
Most utilities already have programs to capture and disseminate expert-worker knowledge. For example, most companies have training groups and programs, procedure groups, human resources organizations, etc., that routinely identify, collect, and disseminate important information. In addition, some companies have effective mentoring, apprentice, job rotation, and cross-training programs.

To the extent feasible, existing resources and infrastructure should be used to collect and disseminate valuable undocumented knowledge from experts. Thus, time and costs to initiate a new program may be minimized. In fact, in many organizations, a very important step will be to assign an existing department, group, or individual with the responsibility for any expanded undocumented knowledge capture efforts.

Develop plan for knowledge capture and presentation
A plan should be prepared to elicit, store, and retrieve valuable undocumented knowledge from each individual selected. The plan should identify the specific knowledge elicitation method(s) selected for each expert or group of experts with similar skills, define the methods for storage, and describe how the stored knowledge will be retrieved.

Development of this plan will require consideration of a number of factors, such as type(s) of knowledge, availability of the departing expert, and capabilities and resources of the personnel responsible for knowledge elicitation.

Prepare knowledge modules and keep current
When this plan is implemented, the elicited knowledge should be formatted and packaged in a knowledge module. A knowledge module is explicit knowledge related to a specific task, activity, job, etc., that is retrievable when needed after having been elicited from an expert; evaluated, edited, and formatted to be in a form usable by others; and stored in electronic and/or hard-copy form.

There are at least two issues to consider when preparing knowledge modules. One issue relates to the use of the expert knowledge: Is it going to be incorporated with other material used by those receiving the information, or is it going to be used in stand-alone fashion? For example, the expert knowledge could be incorporated into a training class together with other training material. Alternatively, the expert knowledge could be linked to a step in a procedure, automatically appearing when it is time to perform that step. An example of stand-alone use involves a person in the field who inserts a CD-ROM in a laptop computer to receive guidance on how to perform a task, either just before or during task performance.

A second issue relates to the characteristics of the person using the knowledge module. If that person is not expected to be familiar with some of the technical terminology used or with the location of parts or tools discussed by the expert, then additional information may be required.

The knowledge modules must be stored appropriately and in accessible locations. Their existence must somehow be made obvious to potential users at the critical time that the knowledge should be accessed, and they must be presented in a timely fashion when needed.

It is essential that the knowledge modules be updated and corrected, as appropriate. Changes will occur in equipment, processes, procedures, practices, regulations, responsibilities, etc., over time. For a knowledge module to be useful over an extended period, it must be updated as needed. Also, with use, some of the knowledge may be found to be incorrect. It is essential that the errors be eliminated and correct information provided. Knowledge modules that no longer have value should be eliminated.

Other valuable lessons were learned during testing of knowledge elicitation methods at four sites.

Knowledge elicitor should be familiar with the domain
The person(s) responsible for eliciting the expert knowledge should be somewhat familiar with the domain about which the knowledge is to be elicited. The elicitor(s) may have the required familiarity through previous experience, or he/she may be given time to be bootstrapped into the domain prior to knowledge elicitation.

There are several reasons why such domain knowledge is necessary. Most importantly, it permits the knowledge elicitor to understand specialized domain terminology, be able to ask intelligent questions, and have some recognition of the specific areas to probe further to obtain the valuable undocumented knowledge.

Knowledge elicitors need guidance

Most elicitors should be provided with some guidance regarding the valuable domain knowledge to be captured. This may not be necessary if the elicitor is extremely familiar with the domain and the valuable knowledge that needs to be captured. Without this depth of knowledge, however, he/she may need to rely on someone else for direction regarding what needs capturing.

In many cases, the expert has a wide range of expertise, some of which is unique, and some that is also known by others. The expert is likely to be most familiar with the areas of knowledge that are of greatest importance and should be captured for transfer to others. It should be noted, however, some workers who are identified by their managers as experts may say, “I don’t have any valuable knowledge; other people know what I know.” It is not uncommon for an expert not to realize he/she has valuable knowledge not known by anyone else. Some experts assume that others have the same knowledge, even though that may not be the case.

Experts are usually extremely busy because they are the ones assigned the most demanding and difficult tasks, and may be consulted by others needing access to their unique knowledge. It may be difficult for the knowledge elicitor to have much time with the expert. Therefore, that time must be used wisely to capture the knowledge that is most valuable and not available to others.

In any event, the expert’s manager or other people most familiar with the situation should be queried regarding the specific knowledge to elicit. Such people will have an understanding of the knowledge areas that are important. They will be able to identify the most valuable and needed information that should be collected and subsequently made available to others.

Knowledge elicitation usually takes place in stages
Knowledge elicitation efforts usually take place in stages, and the nature of the knowledge is a major consideration in selecting the appropriate elicitation methods. The first stage is for the elicitor to develop an understanding of the general knowledge of importance available to the expert. Methods are available to develop a high-level description or overview of the expert’s valuable knowledge, e.g., the concept mapping method. The description created by applying the method can be reviewed with the expert and his/her manager to select areas to drill down to the levels at which the most valuable undocumented knowledge is held.

Following selection of the specific areas of importance, the elicitor may drill down to a deeper level of expertise applying the same methods used to create the high-level overview of the expert’s knowledge. Alternatively, another method may be selected that is more appropriate for the nature of the knowledge. For example, if the knowledge is based in large part on significant events occurring in the past, then an interview approach using the critical incident method or critical decision method may be appropriate.

Other approaches may be more suited to knowledge that relates to operations and maintenance processes and equipment. Such knowledge may be elicited with the help of simulations and scenarios using mock-ups or actual equipment. The simulations and constructed scenarios method and the think-aloud problem-solving method involve encouraging the expert to describe what he/she is doing and also thinking about as he/she performs the simulated or actual tasks. Video or audio recordings and photographs may be taken at appropriate times during the elicitation sessions, and then after editing and indexing be made available to others when access to the expertise would prove beneficial.

It may be desirable to drill down to even a more detailed level of knowledge at certain points during the elicitation process. For example, the expert may report that he/she senses almost unconsciously that something is in alignment, and that one “thing” can be inserted into another. If this capability to perform the action more quickly and better than anyone else has high value, then an unstructured interview approach might be applied to ferret out the important cues that are present. The elicitor may ask about visual, auditory, and tactual cues that are being used, possibly at almost an unconscious level.

Knowledge storage, presentation, and use must receive attention
Previous researchers working in the field of expert systems and knowledge management have observed the existence of a knowledge acquisition bottleneck. The knowledge elicitation methods described above, applied appropriately in the context and situation, can alleviate serious knowledge acquisition bottleneck problems.

Despite such reduction of knowledge acquisition bottlenecks, however, care must be exercised to facilitate the subsequent steps of knowledge storage, presentation, and use. The very methods that can, under certain circumstances, alleviate bottlenecks in knowledge acquisition can create time and effort barriers for subsequent stages of the process. For example, methods such as structured and unstructured interviews that rely on audio recording of elicitation sessions can create a transcription bottleneck. Transcription, editing, and reviewing audio records of interview sessions are time-consuming activities. Techniques to minimize the editing required to format knowledge for use by others include careful and selective audio recording and, for certain kinds of knowledge capture, use of video recording.

Computer speech recognition might be considered as an approach for avoiding the transcription bottleneck. At this time, the technology is not yet advanced enough to make this approach feasible. Both the elicitor and expert would need to train the speech recognition system in their respective voice patterns, and technical terms not in the speech recognition lexicon would need to be entered prior to the elicitation session. Speech recognition technology is moving ahead rapidly, and it may help reduce the transcription bottleneck problem in the near future.

No right or wrong knowledge elicitation method
The process of capturing valuable undocumented knowledge hinges on the development of an effective plan. It is important to determine whether potentially valuable undocumented knowledge will be lost with unavailability of experienced personnel; evaluate whether this knowledge is worth capturing; select appropriate method(s) to use in eliciting knowledge; and store, retrieve, and present this knowledge when needed.

The importance of each of these steps does not, however, imply that there is a “right” or “wrong” knowledge elicitation method or set of methods. The choice depends on a range of considerations, some of which may not come into play until knowledge elicitation is under way. For example, the knowledge elicitor may find that an elicitation method not considered or selected during planning may be more appropriate for the type of knowledge used by the expert. In such instances, it may prove desirable to revise the plan as the knowledge elicitation moves forward. Thus, understanding and access to a range of methods, and the flexibility to alter methods being used or planned, will result in greater benefit from the knowledge capture endeavor.

This article is based on two papers presented at the IEEE 7th Conference on Human Factors and Power Plants, September 15-19, 2002, in Scottsdale, AZ. MT

Lewis F. Hanes is employed part-time by EPRI as a project manager. Since his retirement from the Westinghouse Electric Co. Science and Technology Center, he has worked as a consultant to several organizations, and for three years was a full-time EPRI employee managing the nuclear human performance program.

BACKGROUND OF RESEARCH PROJECT

The EPRI 1999-2001 Strategic Human Performance Program included a multi-faceted research project, “Capturing Undocumented Worker-Job-Knowledge,” to assess the problems related to this potential loss of tacit knowledge, to determine and assess possible approaches to deal with them, and to develop practical guidelines for use in energy industry settings.

The overall project objectives were to deliver practical guidance for identifying employees who possess valuable undocumented knowledge; evaluating whether the knowledge is worth capturing; eliciting and storing the valuable knowledge; and retrieving and presenting this knowledge to other personnel when needed.

During an industry telephone survey as part of the research project, 92 percent of the respondents reported that loss of unique valuable expertise would pose a problem within the next 5 years, but only 30 percent of the respondents indicated that a planning effort was in place to address this problem of retaining knowledge from experienced workers in a manner that would make it accessible and usable by new or replacement members of the utility workforce.

Developing and testing the guidelines, which consist of both a process to follow and knowledge elicitation methods, occurred over the three-year period. The process and methods were implemented and tested at four utility sites with 20 workers/teams representing a range of organizations and work types. The process and methods were refined based on test results, and the final guidance report developed.

The guidelines were expanded and refined in 2002 for application to nuclear power generating sites. Detailed process flow charts were created that provide guidance on how to (1) identify experts from whom valuable knowledge would be captured, (2) develop a plan to capture the expertise and make it available when needed, and (3) implement the plan to develop knowledge modules and make them available when needed. Methods and techniques were identified and described to support accomplishment of the steps in the process flow charts.

EPRI, the Electric Power Research Institute, was established in 1973 as a nonprofit center for public interest energy and environmental research.

The head of a corporate reliability group for a worldwide consumer products company was having difficulty hiring maintenance personnel who possessed the skills the company required. He was adamant that troubleshooting skills cannot be taught. “Troubleshooting industrial equipment is an art more than a learned skill. You either have it or you don’t,” he said.

I totally disagree with this concept. There are many seminars, programs, and methods of teaching troubleshooting skills. However, most of these methods require considerable time and are not conducive to a factory floor setting.

Prerequisites to troubleshooting
The key to troubleshooting industrial equipment lies beyond the process itself. A prerequisite to troubleshooting is the knowledge and understanding of the equipment. Knowing how the equipment functions, what each component installed on the equipment is, what the component does, how the component does what it should, and how the components interact are essential in applying any troubleshooting methodology or process.

Information about the equipment can be taught to anyone. Employees with a maintenance background, whether mechanical or electrical, will learn much more easily than those who have no maintenance experience.

A company that expects to hire someone who possesses these so-called troubleshooting skills and expects to provide no equipment-specific training will undoubtedly be disappointed.

Is it feasible to train every maintenance technician on every piece of equipment in the plant? No, of course not. That would take more time and money than any company has in its budget. But is there a way to teach individuals to train themselves how to learn about specific equipment? Yes, I believe there is. A standardized process of learning is essential.

Apply a standardized process
How is this accomplished? Let’s take a look at the automotive service industry. A training program supports every major automotive manufacturer through one or more outside facilities throughout the United States.

In most cases, before an individual can start a program specific to a manufacturer he must be a graduate of a nonspecific program. These programs involve a curriculum of generic classes such as fuel systems, computer systems, brake systems, etc.

Once the prerequisites are accomplished, an individual may enroll in a manufacturer’s program. These programs include equipment-specific training. The individual, schooled in the specifics of component function, now learns how those components function together in an integrated system within a specific automobile. Once the systems are learned, diagnostics of the systems can be learned. In today’s automobiles, troubleshooting has become a computer-aided science. Diagnostic outputs are built into many of the computer-driven systems.

This sequence from the automotive service training industry is directly applicable to manufacturing and almost every industry where equipment is involved.

An industrial curriculum including training on hydraulic systems, bearings, drive systems, etc., would be a prerequisite to equipment-specific maintenance training. Once the generic maintenance skills are learned, individuals may begin to train on equipment-specific functions.

Once the equipment is well understood, troubleshooting methods can be taught and then applied directly to the equipment on the factory floor.

Getting equipment-specific training
How does a company provide its employees with equipment-specific maintenance training without actually presenting a training class for every piece of equipment? The answer is simpler than it seems.

If an employee, for example, is knowledgeable on pneumatic systems then he can look at a piece of equipment containing a pneumatic system and identify the components that are involved in, for example, a functioning air cylinder. With a little creativity, and without a manual or blueprints, a maintenance technician would be able to identify the source of power (air) and the various air lines, solenoid valves, flow control valves, regulators, etc., that are involved in the operation of that cylinder.

This methodology can be expanded to the other systems within the equipment.

The first step is to identify the sequence of operations within the machine. Every machine, no matter what the function, has a sequence of operations in which a specific input triggers a specific output and so on. Once the inputs and outputs of each operation are identified, the components involved in that operation can be identified. It is easier to use a chart for this purpose (See accompanying “Machine Information Chart”).

Once the components are listed, identify the element of power for the component. In other words, what makes this component work?

Next, identify the function of each individual component. For example, a solenoid valve switches a valve to supply air to a cylinder or, a flow control valve adjusts the airflow to the cylinder thus adjusting the speed of the cylinder.

After every operation of the machine is identified and all the components and their functions within the machine are listed, then apply a troubleshooting methodology or process.

Most troubleshooting methods teach a systematic approach or thought process. Using the newly acquired information about the machine, follow these steps:
•Identify or clarify the problem. What was the unwanted result?
•Identify the operation that this result (wanted or not) is controlled by.
•List the components involved in that operation, using the machine information chart.
•List the power needed for each component.
•Identify logically whether or not each component could have caused the unwanted result.
•Test the components that have not been eliminated thus far.

Using this methodology effectively eliminates every component not involved in the specific operation where there is a problem. This can be as many as 90 percent of the components of the machine.

These skills and this process work very well for operations personnel as well as maintenance technicians. The more operators learn about how the machine functions and what specific components actually do, the better they can operate and maintain the equipment. MT

Randall Quick is a senior partner with Manufacturing Solutions International, Birmingham, AL. The company provides a variety of reliability training and consulting services. He can be reached at telephone (205) 919-4741

MACHINE INFORMATION CHART

• We speak a different language.
• We see things differently (even though we are looking at the same thing).
• We judge things technically, without the “business point of view.”
• We fail to explain why maintenance and reliability are crucial to business success.
• When we are invited, we tend to beg off because we have “real” work to do.

The perception in the end is that whenever we are invited, we “don’t have a clue.”

I have heard over and over the lament by fellow compatriots in the field of maintenance, reliability, and physical asset management that “we are not listened to by upper management,” that “we are never invited to the big table.”

Unfortunately, I have heard from upper management the refrain that not only is it difficult to convince operations management to invite maintenance management to the big table, but also that whenever maintenance management is invited, it comes to the meetings without a clue as to why it was invited, or why it is there.

So what is happening? And what should we do about it?

First, it seems to me that we do not know the “business side” of our own business—maintenance—well enough to market ourselves and sell our value to the organization. Can you answer these questions: What is the value we provide? What is it worth? How do we measure it? What is the business case—the ROI—for maintenance and reliability?

We claim maintenance and reliability provides a competitive advantage in the marketplace. But we seem to have a difficult time quantifying the value of that advantage. Most of our maintenance metrics are focused only on maintenance and reliability. They are relevant and necessary, but they tell us only how well we are managing maintenance.

Where are the metrics that demonstrate the ROI of maintenance relative to the products and/or services that our companies provide? How, for example, do we demonstrate that as a consequence of investing a certain amount of money into maintenance and reliability, the business gets a positive return? How do we demonstrate reduced operational costs, increased productivity, fewer losses, increased sales, or satisfied customers?

This is tough to do. Much of the argument is philosophical; very little of the argument is demonstrable via quantifiable financial measures. So it is natural that at the senior management level, maintenance is viewed as a cost, not an investment. No one doubts it is necessary, but from the business perspective, the perceived measure of maintenance effectiveness is “cost per unit of production.”

So the primary management strategy regarding maintenance is cost control. That is how most business managers view maintenance. And, unfortunately, that is how many maintenance managers view maintenance. So it is not surprising that upper management, who views its role more toward strategic planning, operations management, and optimization of profit, views maintenance as a small part of the whole.

But it is nevertheless true that maintenance and reliability is a critical part that fits into the core of most businesses. But to sell that to upper management we must change our ways.

That is one of the reasons concerned maintenance and reliability leaders formed the Society for Maintenance & Reliability Professionals (www.smrp.org). One of its mission objectives is to support maintenance and reliability as an integral part of business management.

It is going to be a hard sell, and will take perseverance and persistence to sell the message that maintenance and reliability are investments that lead to a competitive edge in the marketplace. It will be difficult to change the image of maintenance from that of a technician to that of a professional and businessman.

The most critical element in that transformation will be you, the individual; you must change your own mindset and knowledge of business. We must learn the business of business as well as the business of maintenance and reliability.

We must become the best-of-the-best in our endeavors and we must become equally so in the business arena.

Robert C. Baldwin, CMRP, Editor

One of the professional development resources on the Internet that caught my eye is the Open Courseware initiative rolled out last year by the Massachusetts Institute of Technology (MIT). I counted more than 200 courses for which material has been made available at www.ocw.mit.edu. The university says it expects to have virtually all its course material online by 2007.

As pointed out on the OCW website, the program is for publishing MIT course materials, free and open to the world. It is not a degree- or certificate-granting program, nor an MIT education.

All types of course materials are served up, including syllabi, calendars, readings, lecture notes, video lectures, assignments, exams, and projects, but the amount of material for each course varies. I browsed through some of the offerings and found them promising.

I reviewed several video lectures, including “Educational Technology Initiatives in Business Education in the Sloan School of Management” by Toby Woll, director of learning technology initiatives.

She pointed to three explicit and two implicit elements of education. The obvious are delivery of content, practice and application, and learning from peers. The less obvious implicit elements, in a school setting, are socialization and babysitting.

The latter two elements are important in adult education also. The socialization element becomes networking and the development of friendships. The babysitting element is turned inside out to provide a “time out” from the normal working environment to allow learning to take place in a different atmosphere where it should be more effective.

This suggests that the smart manager will budget some time for off-site training at conferences, courses, and workshops. Opportunities abound. Check our event calendar (page 9) and Professional Development Quarterly (page 23) for specifics. MT

The analysis of a vibration spectrum of a machine in the context of linearity and nonlinearity provides an additional basis for understanding why spectra look as they do and how the appearance of a spectrum relates to machine health. Here is an overview of the concept, augmented with straightforward illustrations and examples.

Linear systems
If a linear system is thought of as a black box, it can be said that what comes out of the box is directly proportional to what goes in. This concept is called proportionality. In Fig 1. we can see that the output motion is directly related to the input force. If the input force increases, the resulting motion also increases proportionally (click for Figs. 1-8 ).

Another quality of linear systems is superposition as demonstrated in Fig. 2. Superposition means that if we have two or more input forces, the output motion will be proportional to the sum of the input forces. In other words, nothing new is created. If we add a whole bunch of forces at the input, the output motion will still be directly proportional to the sum of those forces.

Nonlinear systems
Consider a dense metal cube sitting on ice. If you push the cube, it will slide proportionally to how hard you push it. This is a linear response. Now consider that the cube is made out of gelatin. When you give the gelatin a push it may slide a bit, but it also will wiggle and wobble. This is an example of a nonlinear response. The gelatin does not move only in the direction of the push, it also wiggles around in different directions. Therefore, we can say that the output motion is not directly proportional to the input force and therefore the gelatin block is nonlinear (Fig. 3).

Nonlinear systems also do not follow the law of superposition. This means that the output response is not proportional to the sum of the input forces. In a nonlinear system, the inputs combine with each other and produce new things in the output that were not present in the input (Fig. 4).

When one plays a stereo at a relatively low volume, the music comes out clearly. If one raises the volume slightly, the music comes out of the speaker more loudly, but still sounds good. This is a linear response.

We reach a point, however, where if we make the stereo loud enough, the music becomes distorted, and we begin to hear new sounds that were not recorded on the CD. This is a nonlinear response. The key again to understanding when something is nonlinear is that the output contains things that were not present in the input.

Linearity and nonlinearity in vibration
Now that we have described the basic concepts of linearity and nonlinearity, it is time to discuss them in terms of vibration signals. Simple mass-spring systems as shown in figures 5 and 6 will be used for this discussion.

An ideal mass-spring system (Fig. 5) can be described by the equation

F = kX

where F is the input force, k is the spring stiffness, and X is the resulting displacement of the spring. This is a linear system. If we input a sinusoidal force, the resulting displacement is also sinusoidal and proportional to the input.

If the stiffness of the spring changes as it is stretched and compressed (Fig. 6), the system is nonlinear. When we input a sinusoidal force, the resulting displacement is not sinusoidal, and thus this is a nonlinear system in which we get out something that looks different from what we put in.

If we remember the basic rules of vibration and the Fast Fourier Transform, the displacement sine wave in Fig. 5 will produce a single peak in a vibration spectrum. The displacement wave in Fig. 6 will produce a peak in the spectrum with harmonics or multiples. This brings up another important point—the harmonics in this case are the result of nonlinearity.

Machinery vibration
When we look at the vibration spectra for a machine in the context of linear and nonlinear systems, we can make a very general statement that as machines deteriorate and develop faults they become less linear in their responses. We also can say that many machine faults create nonlinearity. Therefore, also in very general terms, we can expect the spectra from a healthy machine to be relatively simple compared with the spectra from a machine with faults. If we consider mechanical looseness as a common machine problem, we can demonstrate this.

When the machine is not experiencing looseness and is in good health, its spectra may look like that in Fig. 7, which shows the shaft rate peak (the big one on the left) and a couple of harmonics of the shaft speed. The same machine with a looseness problem (Fig. 8) might show considerably more shaft rate harmonics at higher amplitudes. This is very similar to the example of the two mass-spring systems in that when the mass-spring system was linear, only one peak was produced in the spectrum, i.e., the output looked like the input. When the mass-spring system was nonlinear, the output waveform was not sinusoidal and therefore produced harmonics in the spectrum.

If we take a step back, we can consider that the mechanical input forces in a simple rotating machine are coming from the rotating shaft. If the shaft is rotating perfectly (i.e., there is no looseness) and the response of the machine structure is perfectly linear, then we would expect to see only a single peak in our spectrum corresponding to the shaft rate. In other words, the output would look like the input. No machines are perfect, however, and shafts do not typically rotate perfectly around their centers; this is why we expect to see some harmonics in machine spectra (Fig. 7). However, as the machine becomes more nonlinear, due to a condition such as looseness, foundation cracks, or broken mounting bolts, more harmonics with higher amplitudes appear (Fig. 8).

Note that if one views a spectrum with a linear amplitude scale, one may not see the harmonic content of the spectrum if the harmonics are much smaller in amplitude than the shaft rate peak. If one views the data using a logarithmic amplitude scale, more harmonic content will be visible on the graph.

Sidebands
Sidebands in a spectrum are another result of nonlinearity. Sidebands are produced by amplitude modulation.

The top waveform in Fig. 9 is an example of a modulated waveform. What we have here is a wave that repeats itself with a frequency X; however, the amplitude of this wave goes up and down at the frequency Y of the wave on the bottom of the diagram. The bottom wave is simply included to demonstrate the frequency at which the amplitude of the top wave goes up and down.

If one wishes to visualize this in mechanical terms, consider a set of gears where one gear is not centered on its shaft. We will say that the noncentered gear has 32 teeth. In one revolution of the noncentered gear we will see 32 tooth impacts. This would relate to frequency X. Since this gear is not centered on its shaft, the amplitude of the tooth impacts will go up and down as the gear moves closer and farther away from the second gear. It will take one revolution of the noncentered gear for the level of the impacts to go from maximum to minimum and back to maximum again. So, the frequency with which the levels of the impacts change (or are modulated) is the rotation rate of the noncentered gear. This would relate to frequency Y in Fig. 9.

The spectrum of these gears (Fig. 10) shows a peak at frequency X with one peak on either side of it Y distance away. Stated another way, we will see a peak at frequency X, another at X+Y, and a third at X-Y. The peaks at X+Y and X-Y are called sidebands.

Why is this system nonlinear? Because X+Y and X-Y are not found anywhere in the input signal but they do appear in the output. The only thing in the input is X or the rate of the teeth impacting. These impacts go up and down in amplitude at a rate Y, but there is certainly no X+Y or X-Y in the input.

The off-centered gear also may cause frequency modulation because the effective radius of the off-center gear changes as it moves closer and farther from the other gear. As the effective radius changes, the rate of tooth contact speeds up and then slows down repetitively. Frequency modulation is similar to amplitude modulation in that it also results in sidebands. In amplitude modulation, the amplitude of the impacts goes up and down in level repeatedly. In frequency modulation, the rate of impacts gets faster and slower repetitively. In this example, both would result in the same pattern in the spectrum.

Nonsynchronous tones
Rolling element bearing wear, gear defects, and motor-bar defects will produce sidebands. Rolling element bearings also will create nonsynchronous tones. These are new peaks that are not exact multiples (harmonics) of the shaft rate.

Figure 11 shows a machine with a serious bearing problem. Compare this with Fig. 7 and note the peaks that are not related to the shaft speed (1x). The two peaks with circles on them are bearing tones and the peaks with the arrows are sidebands. In terms of linear systems, we can say that this spectrum represents a very nonlinear response and suggests the machine has faults (which it does).

To understand why rolling element bearings create nonsynchronous tones and sidebands, consider the case of a horizontal machine with an inner-race bearing fault. As the shaft and inner race spin, a certain number of balls will impact the fault on the inner race and will produce a peak in the spectrum equal to the number of impacts per revolution of the shaft. This peak is called a bearing tone. The number of impacts will almost never be an integral amount. In other words, there will be 3.1 or 4.7 impacts per revolution, but rarely exactly 3 or 5 impacts. Thus, the peaks will not be direct multiples of the shaft rate and are therefore termed nonsynchronous. The higher peak marked with a circle in Fig. 11 is an example of a bearing tone at 3.1x the shaft rate.

Considering this example further, we also can see that the weight of the shaft will cause the impacts against the fault to be greater in amplitude when the fault is below the shaft. As the fault on the inner race rotates to the top of the shaft, the impacts will be smaller because there is less weight (load) on the fault. In one revolution of the shaft the fault will travel around one time—into the load zone, out of the load zone, and back into the load zone. Therefore, the frequency of the change of amplitude in this case is equal to the shaft rate and this also will coincide with the spacing of the sidebands around the bearing tone (the peaks with the arrows in Fig. 11).

A similar phenomenon occurs if there is a fault on a ball or roller. We will see a bearing tone at a frequency equal to the number of impacts the fault on the ball makes with the races in one revolution of the shaft. This peak also will be nonsynchronous and is called a bearing tone. The fault on the ball or roller also travels in and out of the load zone; however, it travels at the cage rate, not the shaft rate. Therefore, the sideband spacing around the bearing tone will be equal to the cage rate, which is usually in the neighborhood of 0.3x the shaft rate.

Vibration trending recommended
The concept of linear and nonlinear behavior gives us another way to think about a vibration spectrum and how its appearance relates to machine faults. Healthy machines should respond more linearly than machines with faults; in other words, as machines develop faults they likely will respond less linearly. As they become less linear we begin to see more and larger harmonics and/or sidebands in the spectra.

Because we may not know all of the details about the design of a machine or how its spectra will appear when it is healthy, it is still best to trend information over time. Look for more and larger harmonics and new peaks that were not there before as an indication that the health of the machine is deteriorating. MT

Alan Friedman has worked in software development, expert system development, data analysis, training, and installation of predictive maintenance programs at DLI Engineering, 253 Winslow Way West, Bainbridge Island, WA 98110; (206) 842-7656 . The author wishes to thank Glenn White who contributed to this article.

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By do many maintenance departments continue to fight fires—rushing from one breakdown to the next making heroic repairs? Answer: They lack planning.
Maintenance planning is the foundation upon which proactive maintenance organizations are built. Maintenance planning allows you to maximize the wrench time of maintenance technicians by having a daily plan with the right parts and tools available when needed.
How does maintenance planning allow you to make the transformation from reactive (firefighting) maintenance to proactive (planned) maintenance, if you still have the daily crises? The transformation takes place when you determine how much time you have for planned work and then start using this time to perform preventive maintenance work orders or repair/projects work orders.
This article will discuss how to start planning and how to keep it going. It will present a set of proven steps for conducting maintenance planning as well as helpful tips for successful planning.

Use work orders
First and foremost, if you do not use work orders, then start. Work orders become the communication vehicle for getting work done:
• A person writes a work order to request work.
• The maintenance planner reviews the work order and determines when/how to perform the requested work.
• Maintenance technicians receive the work order and perform the requested work.
• The planner receives the completed work order back and closes the work order.
• Finally, the requestor gets the work order back for final review.

Work orders also allow you to create a historical equipment record. This history will help later to identify trends for initiating continuous improvement projects and for calculating maintenance costs to justify new equipment purchases.

The actual work orders can take several forms: simple paper forms, multi-part carbon forms, or electronic (CMMS-based) forms. You can pick any of these options that fit your organizational culture, but start using work orders.

Set up scheduling system
Setting up a scheduling system means creating a process for deployment of maintenance planning. This process should include a method for receiving incoming work orders, distributing work orders to the technicians, and returning the scheduled work orders after the shift.

The process you design should allow you to move work orders through the system in a process flow. Create a basic flow that is easy to follow, but has a defined structure to prevent informal paths. Decisions that need to be addressed include how you will receive work orders, how they will get to the planner, how the planner will send work orders to the technicians, how the technicians will return the work orders to the planner, and how work orders will be closed.

If you are using a paper system to manage work orders, I suggest you use several centrally located mailboxes to receive the work orders. I also suggest you create a daily file system which becomes the vehicle for technicians to get work orders and return them at the end of the shift. With this file system, the planner puts the planned work orders in the appropriate shift folder for the day and shift; the technicians or shift supervisor then picks up the appropriate shift folder and completes the scheduled work orders. At the end of the shift, the technicians or supervisor returns the shift folder with all the work orders to the file for the planner to review.

When creating this system, consider the future opportunities to put this system in an electronic format. Eventually you may want to use electronic work orders and personal data assistants (PDAs).

Once you have the scheduling system set up, then train everyone on how to use the system. When you conduct this training, focus on what each group needs to know to use the system and not on making everyone a planner. Also, make this training visual with pictures and diagrams.

Determine how much time you have for planning
Once you have determined your planning system design, then determine how much time you actually have for planned work. Or more precisely, how much time is left over each day for planned work after considering breakdown, breaks, and lunches. When you begin building daily schedules, this quantity of time will become the amount of work you can schedule on any given day. Therefore, knowing the available time is the key to making realistic schedules and not over- or under-scheduling the technicians.

First calculate the total available work hours. This is the total time of the technicians less the time for breaks and lunches:

Total available work hours =
(Number of technicians x number of hr/shift) – time for breaks and lunches

To calculate the time available for scheduling, next determine how much time your technicians spend on breakdowns each day. Subtract this number from the total available work hours to determine how much time you have each day for scheduling planned work:

Time available for scheduling =
Total available work hours – time for breakdowns

Plan daily by day and by shift
The final two steps in implementing maintenance planning are to make a daily plan, and to keep doing it.

To start creating a daily plan, sort existing work orders by importance. As you perform the sorting process, estimate the time and number of people required to complete the requested work and if parts must be ordered. When you have sorted all the work orders, then begin determining when the requested work can be performed.

While many people want to make this step into an extremely complicated activity, it simply involves figuring out where everything fits within the constraints of time, people, and materials. To help in this step, use decision rules (see accompanying section “Decision Rules for Scheduling Work Orders”).

As you build the daily plan, always think in terms of how many available hours exist on each shift and which work orders fit into this timeframe. Be careful to not overload the shift schedule or the technicians will treat the plan as a smorgasbord—only working on those work orders that they want to do.

When you make the daily plan, review the work orders for clarity and direction. Make sure the work order recipient has enough information to perform the work and that you agree with the requested work. If the work order does not contain enough information or you disagree with the work request, return the work order to the requestor for clarification or changes.

Also, determine what parts are needed for the work order and have them ready for the shift that is scheduled to perform the work. If you determine that you do not have the necessary parts, then order them and schedule the work order when you receive them.

For complicated projects, consider scheduling the work order in two parts: (1) development of a plan and parts requisition, and (2) performance of the work.

This two-step process will allow you to complete more work orders while helping to develop your technicians into problem solvers.

When you have the daily plan completed, place it in the agreed location for the technicians or the shift supervisor to pick up and perform the work. At the end of the shift, they should return the plan to this location for review on the following day.

The review of the previous day’s plan will be the start of the current day’s plan. Work orders should be sorted by completed or not complete. Those work orders that are complete should be closed. Work orders that are not complete should be assessed for why they were not completed and dealt with accordingly.

The last step in finalizing maintenance plans is coordination. Make sure your production counterparts share your priorities and have scheduled equipment down as planned. Nothing wrecks a maintenance plan like the equipment not being available. Be advised that at first, production may be skeptical of your planning so let the results speak for themselves. As they see things getting done and uptime improving, they will begin to see the value of the plan and the importance of their cooperation.

Keep doing it
The last step sounds the simplest, but it can be the hardest. To keep maintenance planning from crashing and burning, you need to keep doing it. If you do not manage all those little pieces of paper, then soon you have no planning. Look at planning like daily exercise—at first your muscles are stiff and sore, but as you keep it up you feel better and you begin to see results. Maintenance planning will be the same way; you start small with a few work orders that fit into the available time and as the operation improves you have more and more available time for work orders.

This incremental process is how you improve the maintenance operation and move to proactive maintenance. By using the maintenance plan, you can get PMs and project work orders completed. If you don’t already have a good set of PM work order instructions, then use the maintenance plan to schedule work orders for building or improving them.

Your ultimate goal should be to reduce trouble calls to 15-20 percent of your total workload. Reaching this goal will take time and effort but it is attainable. Consider these opportunities for incorporation into your planning process:
• Schedule a weekly planning meeting with production to establish priorities and schedule downtime. This meeting must be a cooperative effort with give and take on both sides. Also, consider taking action items during the meeting to track requests and always come to this meeting prepared with your downtime requirements.
• Tie your purchase department into the work order process—see if parts can be “kitted.” When a technician gets a work order then, he is ready to perform the work instead of spending time withdrawing individual parts from stores.
• Create a metric chart to track trouble calls vs. planned work orders. If possible, track this metric by areas in your plant. Use this data for discussion in the weekly planning meeting and to identify maintenance continuous improvement opportunities.
• Consider creating a value stream map of your maintenance operation to see where you lose time and to identify waste. The future state map that you create then becomes the roadmap to proactive maintenance.

Remember, no plan is a plan for failure. To change the way your maintenance department operates, you must change how you do business. Maintenance planning is the change that will allow you to move from firefighting to proactive planned maintenance. This change takes place one step at a time, but the final results will be worth the effort. MT

John M. Gross, P.E., CPE, works as a lean manufacturing manager for a tier 1 automotive supplier. He is also the author of “Fundamentals of Preventive Maintenance” published by AMACON books and a Six Sigma black belt.

Decision Rules for Scheduling Work Orders

• Where do you have available hours (i.e., manpower)?
• What is the work order priority (i.e., is it routine work, a safety hazard, or an impending equipment failure)?
• When will the equipment be available?
• Which shift has the necessary skills to perform the work?
• When will all the parts be available?

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