MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_NextPart_01C9D09B.E5A47B40" This document is a Single File Web Page, also known as a Web Archive file. If you are seeing this message, your browser or editor doesn't support Web Archive files. Please download a browser that supports Web Archive, such as Windows® Internet Explorer®. ------=_NextPart_01C9D09B.E5A47B40 Content-Location: file:///C:/D11244C5/SmartApproachtoPredictiveMaintenance.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="windows-1252" Smart Approaches to Predictive Maintenance

The Smart Approach to Predictive Maintenance=

Alan R. Bessen, P.E.

 

A growing number of aggregate producers are using Predictive Maintenance (PdM) technologies such as vibra= tion analysis or infrared thermography.  Within the scope of a comprehensive maintenance program these techno= logies can be highly effective.   However,= by themselves, they bring absolutely no value.  It is the actions that result from condition monitoring that provide value. 

 

In an aggregates operation mo= st of this value will come from increasing the reliability and efficiency of equipment.  If a plant is running 90 to 95 percent = up time, reliability has already been achieved.  The primary benefit from PdM technologies will be in maintaining reliability by verifying preventive maintenance, equipment replacement and planned overhaul schedules.  If a p= lant is running at 85 percent up time or less there are 10’s or even 100’s of thousands of dollars available each year in potential cost reductions throu= gh improving the reliability of equipment.  <= /span>

 

Predictive maintenance is one= of the four basic levels of maintenance common throughout industry.  The four levels are: =

·      =    Reactive= - “Fix it when it breaks” : This is part of every maintenance philos= ophy because you can never eliminate or predict all failures.  However, relying on this level of maint= enance leaves little control over cost of repair and lost production. 

 

·      =    Preventi= ve - “Time-based action” : Visual inspections, filter changes, oil changes, overhauls, etc. are based on hours of operation or tons produced.<= span style=3D'mso-spacerun:yes'>  This is a crucial part of any program a= nd provides opportunity to perform maintenance and repair with minimal product= ion loss.

 

·      =    Predicti= ve - “Condition-based analysis” : Equipment is monitored during actual operation.  Technologies used inclu= de vibration analysis, oil analysis, infrared thermography and ultrasonics.   Data is collected, trended and used to predict component life.  The inform= ation is often used to establish Preventive Maintenance schedules.

 

·      =    Proactiv= e - “ Root cause analysis” :  Failures are analyzed to define base level cause and effort is made = to eliminate future failures by changing design, specification or procedure. <= /span>

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Good Maintenance Starts at the Top

The best maintenance programs include all four maintenance levels and are supported by a corporate-wide commitment to ensure the reliability of equipment.  Since maintenance and repair is seldom = done by corporate-level executives, program ownership must reside with those who= are doing the work.  This is particular= ly true for predictive maintenance since its function is primarily to provide information on the condition of equipment.  If nothing is done with the data, it is useless. <= /p>

 

Technology can enhance a maintenance program but will never replace good planning and a competent crew.  However, the regular applica= tion of vibration analysis and thermography demonstrates a commitment that, from= my experience, will cause the maintenance attitude within many crews to shift = away from a reactive maintenance approach to a preventive / predictive approach.  This increases the proba= bility that the necessary actions required to improve equipment reliability are willingly performed.

 

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What is = the Technology?

Predictive maintenance is the most technologically advanced element in a maintenance program.  It uses microprocessor-based technology= to evaluate the condition of operating equipment.   Two of the most frequently used methods are vibration analysis and infrared thermography.  =

 

Vibration analysis shows bear= ing faults, misalignments and imbalances in mechanical equipment.  Vibration data will not only identify a problem, but can accurately indicate the type and severity of problems in bearings, gear reducers and other rotating equipment.  Vibration monitoring equipment can also= be used to measure the structural competence and effectiveness of vibrating screens.  

 

Infrared thermography detects heat related faults such as loose connections and imbalanced phases in electrical equipment by measuring and displaying temperature variations. 

 

Information derived from a predictive maintenance evaluation provides current data on equipment condition.  The data is trended and= used to measure changes in condition, set alarm limits and enhance preventive maintenance services.

 

 

 

Implemen= ting the Technology

The relatively small size of typical aggregates plants, and the normal lack of technologically skilled maintenance personnel make it impractical to initiate a predictive maintena= nce program entirely in-house.  In fact, rapidly changing technology and the high cost of hardware, software and training make the use of a contract service specialist imperative at the beginning of most programs.

 

 Hardware and software for vibration anal= ysis costs approximately $30,000, infrared thermography hardware and software can easily exceed $50,000.  The expense= of acquiring and maintaining PdM equipment makes it desirable to share the ini= tial purchase cost over multiple locations.

 

Contracting PdM services will cost between $2,000 and $3,000 per evaluation for a typical 3,000,000 ton p= er year aggregates plant.  A plant alr= eady operating at over 90 percent up time may benefit from one or two general evaluations per year.  Plants opera= ting between 70 and 85 percent up time may benefit from three or more visits.  Annual contract service costs for a typ= ical 3,000,000 ton per year aggregates plant should not exceed $15,000 unless special problems requiring frequent monitoring occur.

 

To ensure local ownership of = the PdM process, it may eventually be desirable to train and equip local maintenance employees to become basic level vibration analysts.  A basic level analyst would be capable = of acquiring data and deciding whether or not a problem exists. This can be accomplished aggressively in 4 to 6 weeks using alarm set points within the software, an experienced technician for support, and a trainee with a strong mechanical aptitude, some computer competence and a desire to learn. <= /o:p>

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Predicti= ve Maintenance Examples

The following are typical examples from actual operating quarries illustrating the potential for avoi= ding lost production and reducing unnecessary repair costs.  

 

Tertiary Screen - = The scre= en’s poor performance was directly affecting quality and capacity.  Vibration assessment of the screen’s operation determined that the springs had deteriorated dampening its motion= .  Replacement of the springs returned the screen to normal operation and allowed management to cancel plans for a pla= nned overhaul at a cost of $25,000.

 

Dredge -      Intermittent electrical trips shut = down operations on average of three hours per day for over two weeks.  Basic electrical troubleshooting was un= able to identify the problem because of its unpredictable nature.  Infrared thermography revealed loose connections on multiple control fuses.  Repairing the connections solved the problem.  Estimated cost of lost production was $30,000.

 

Primary Crusher -<= span style=3D'font-size:9.0pt;mso-bidi-font-size:10.0pt;font-family:"Calibri","s= ans-serif"; mso-ascii-theme-font:minor-latin;mso-hansi-theme-font:minor-latin'> Lack of lubricant caused the west side bearing on a primary impactor rotor at a maj= or quarry to fail during a time of low inventory and peak demand.  Some shaft damage occurred but the bear= ing was changed with hopes of making it through the production season.  Immediately following the repair, the e= ast side bearing began running hot.  Qu= arry management began planning a full rotor change out requiring four down days = at a production and sales loss of over 50,000 tons.  Vibration analysis of the east side bearing showed no damage, high temperature was caused by over greasing.  Both bearings were monitored frequently for the balance of the season and the 50,000 ton production / sales loss was avoided.  Estimated value of the avoided loss was $80,000.

 

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The Bott= om Line

Incorporating new technology = into your maintenance program will not magically improve plant performance.  Monitoring and recording equipment cond= ition does not make it run better.  The k= ey to any successful maintenance program is to focus employees on taking actions and adopting pract= ices that will improve equipment reliability.  In this setting vibration analysis and infrared thermography are properly defined as useful tools not solutions themselves. 

 

Predictive Maintenance methods have proven effective in other industries, as we learn to properly apply th= em in the aggregates industry we will be able to redefine expectations for reliability, improving productivity and increasing profitability.

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