Perfor mance an nd Profit Optimiza ation
Transcription
Perfor mance an nd Profit Optimiza ation
TUESDAY,, 02 AUGUST 2011 16:51 Performance an nd Profit Optimizaation By Alan R. Bessen and Sam Sawant This is thee second of a three‐part seeries on crushiing measurem ment and anaalysis. – Ed. Performance Optimiza ation: Pursuitt of the point in your operaation that yieelds the higheest percentagge of quality in‐‐demand product at the lo owest cost with the least aamount of waaste. It appears throughout the aggregate es industry that manageme ent priority has shifted tow ward regulato ory and corpo orate compliaance; often resu ulting in a reaactive approach to managing performannce, too often n with objecttives limited tto simply keeping the plant running. There is n no debate that compliance e with environ nmental, safeety, permitting, budgeting and personnel managem ment prioritiess are all necesssary. Howevver, it is clear that the econ nomic viabilitty of an aggreegates plant and its continued d operation d depend on pro ofitability. Meerely keepingg the plant running regardless of effectiven ness or profitaability is simp ply not an accceptable perfoormance objeective. Managingg performance, maximizingg saleable ton ns and minim mizing surplus inventory red duces cost an nd increases profit. Operaating perform mance directlyy relates to opperating cost;; operating co ost and produ uction yield direcctly relate to profitability. As an aggreggates manageer your job certainly includes regulatoryy and corporate e compliance but must nott neglect man naging the pe rformance off your process. more Accurate evaluation off the present state of yourr process is neecessary to efffectively manage it. The m hood intendeed results will be achieved.. By analyzingg data accurate aand timely daata is, the higher the likelih from with hin the production processs you pursue o optimization by minimizin ng production n losses and b balancing productio on, sales, inve entory and op perating cost tto achieve opptimal profitaability. Identify a and Minimize System Limitations Developin ng and validatting your process model provides prod uct yield and capacity dataa for various operatingg configurations or modes. Most aggreggate operatio ns will definee at least threee standard operating modes ge enerally intended to maxim mize yield of ccoarse aggreggate sizes, meedium aggreggate sizes or fine aggregate e sizes. It shou uld be expectted that, at m minimum, betw ween three aand 10 operatting modes co ould be defined in n most aggreggate plants de epending on d diversity of d esign and on market requ uirements. Some large plan nts will have m more than 10 common mo odes; a few pllants, limited by deposit, m market or dessign will operate in n a single mode. It is not uncommon to find that tho ose processes that have noot been modeeled or have n not properly validated their model o operate in wh hat can be de escribed as a ““Universal Seetup” or modee. This is ofteen by default be ecause they h have no practical modelingg capability too establish wh hat they shou uld be produccing and no practiccal measurem ment to establish what they are produciing. This geneerally results in reactive scheduling of overtime e to compenssate for materrial shortagess, repeated in nventory corrrections, exceessive on of by‐product and highe er than necessary unit pro duction costss. productio mon in develo opment of the e flow model to establish tthe Design Raate or maximu um in‐feed raate for It is comm each mod de. However, it is critical to o avoid confusing Design R Rate with Aveerage Rate. Th he Design Ratte as establishe ed by the flow w model defin nes the maxim mum theoretiical tph rate o of any given m mode. The Avverage Rate is the e expected avverage tph du uring the time e the plant is actually operrating. Individuall product rate es for each mode divided b by the in‐feedd rate for the same mode provides a percentagge yield for eaach product. Product percentage rates for each mod de multiplied by the projected average in n‐feed rate de efine the average ton per operated houur for each prroduct. Agg gregates Perf formance Man nagement: “I Identify Whatt You Need” “If You A Always Do Whatt You Have Alwa ays Done ...You A Always Get Wha at You Always G Got” The next sstep in defining process caapability is to establish a d aily operatingg schedule in ncluding numb ber of shifts, sch heduled hourss per shift and d actual operrated hours d uring scheduled productio on. Applying fforecast operatingg hours to yielld rates estab blished for sellected modess defines the expected pro oduction capaability of the crushing and scree ening process. The final sstep is to ensure that pit capacity can b be scheduled to supply maaterial at an appropriate raate for each operrating mode. If not, then yyour system iss limited by ppit capacity an nd evaluation n of improvem ment potential should occurr in that area. If so, then eaach mode shoould be evalu uated for poteential improveement. ment plans are e developed aand impleme ented incremeentally, resultts are verified d and a new rrate and Improvem yield capaability is estab blished for eaach mode. Pursuing Market Demand projections off expected saales are criticaal to effectiveely manage bo oth cost and profit. Sales cannot Monthly p occur if ad dequate inventory is not aavailable to m meet custome r requiremen nts for volumee and timing. Without aa reasonably aaccurate sales forecast the ere is no clea r target for production to pursue and therefore no short‐term ability to ju udge the effect of current operating peerformance on future saless and cost expectations. Fig#1: Unbalaanced Producttion vs. Sales product yield with It can be sseen in Fig#1 that pursuingg projected sales tons withhout attemptt to balance p sales mix generates an n inventory increase of 477 7,440 tons to achieve the 11 million tonss of forecast ssales. us production n on operatinng cost and on n margin. Fig#2 shows the effectt of this surplu Agg gregates Perf formance Man nagement: “I Identify Whatt You Need” “If You A Always Do Whatt You Have Alwa ays Done ...You A Always Get Wha at You Always G Got” “Unbalanced d” Sales es-Production-Invento ory ExcessInventory Adds dsCost–ReducesMarg gin ction “Balanced d” Sales-Production-Invventory NoSurplusInventtory NoWaste–MaxMa Margin cction Inven ntory Fig# #2: Unbalanced Sales vs. Producction Cost Example Fig#3: Balanceed Sales vs. Prod duction Cost Exaample Fig#3 shows an idealize ed balance w with an operatting cost reduuction and inccreased marggin of almost $ $4 million; de emonstratingg the significaant value lost by operatingg blindly, driveen to achievee sales tons w without consideraation of the co ost/profit imp pact of the un nmanaged ba lance betweeen sales mix aand product yyield. It is intere esting to note e that much o of the cost impact resultingg from an outt of balance p process often gets lost within n accounting systems thatt allocate prod duction crediit. The result is a short‐term positive accountin ng profit while e consuming massive amo ounts of work ing capital; att least until ru ules change aand inventoryy caps are imp posed to force e accurate refflection of prroduction costs and profit.. operation that yields the highest By compaaring Figure 2 and Figure 3 it becomes cclear that the point in an o percentagge of in‐demaand product aat the lowest cost with thee least amoun nt of waste is the point wh hich provides tthe optimal b balance betwe een product yyield and salees mix. Achievingg this in an agggregates operation requires: 1. Devellopment of a valid processs model accurrately reflecti ng the impacct of changes in setup on the yield and capacity of the e production system. mic sales forecasting drivin ng monthly prroduction, invventory, cost and profit. 2. Current and dynam 3. Timely measureme ent and manaagement of cu urrent perforrmance. egic marketing and sourcin ng with consid deration for ddeposit, proceess and cost iissues. 4. Strate The job off an enlighten ned operation ns manager iss to maximizee profit by maanaging perfo ormance, costt and the sales production m mix; it is not ju ust to make to ons. Minimizin ng Waste and d By Product The chart shown as Figg#4 demonstrrates how varriation in equ ipment configuration and flow can affeect demand p product (3/8‐in.) yield as w well as the yie eld of waste aand by‐producct (Scr). It is clear from the dataa that minimu um by‐product yield occurrs when coarsse products aare allowed to o flow to stockpile. Re‐crushing creates a draamatic increasse in by‐prod uct yield while the re‐crusshed 3/4‐in. aand 5/8‐ in. producct yields drop p to 5 percentt or less. It can also o be seen in FFig#4 that 3/8 8‐in. product yyield increasees from 13 peercent to nearly 25 percent by re‐ crushing vvarious comb binations of no on‐demand p products. How wever, with sccreenings yieeld increasing from 16 percent to o 23 percent, in approximaate correlatio on to the yieldd of 3/8‐in. product, it willl ultimately become necessaryy to recognize e, address or aaccept added d cost associa ted with re‐sstockpiling, reeprocessing or wasting by‐product ton ns created wh hile optimizin ng demand prroduct yield. Agg gregates Perf formance Man nagement: “I Identify Whatt You Need” “If You A Always Do Whatt You Have Alwa ays Done ...You A Always Get Wha at You Always G Got” Fig#4: Yieeld Managemennt Care in mode selection n and accuraccy in yield evaaluation is crittical to managing both dem mand producct and by‐producct yield. Equip pment selectiion, operatingg condition a nd plant desiign must also be considereed in any effortt to minimize waste and byy‐product botth in existing plants and in n the design o of new processsing systems. Managingg Inventory Surplus and Sh hortage Accurately establishingg process cap pabilities in ap ppropriate co nfigurations enables dailyy production tto be scheduled d with reason nable expectation of what will be produuced. Fig#5 an nd Fig#6 provvide exampless of basic dataa sheets used for calculatin ng expected p production byy operating m mode. In Fig#5, m max tph‐opr iis determined d by field meaasurement orr from the flow model and d represents tthe maximum m or design caapacity for eacch mode. The e tph factor iss applied to th he design factor to represent the expected average tph ffor each hourr that a plant actually operrates. Percen nt yield factorrs are also obttained or field measu urement. from the fflow model o In Fig#6, sscheduled hours of operattion are reducced by the peercent uptimee factor to callculate the exxpected hours of aactual producction. Neither sccheduled nor operated pro oduction hou urs should be confused witth scheduled labor hours w which includes p pre‐shift inspe ection, scheduled breaks, end of shift cclean out, etc. Scheduled labor hours m must always be e greater than n production hours. Agg gregates Perf formance Man nagement: “I Identify Whatt You Need” “If You A Always Do Whatt You Have Alwa ays Done ...You A Always Get Wha at You Always G Got” Fiig#5: Product Yie eld & Avg. TPH C Calc by Mode Fig##6: Operating SSchedule & Prod duction Rate by Mode Pursuing tthe combinattion of modess and operating schedules that yield thee highest perrcentage of in n‐ demand p product with the least amo ount of waste e and by‐prodduct invariable results in th he lowest uniit cost per ton. However, it is also invaariable that normal operattions require the plant to rrun out of balance to meeet sales commitments. It shoulld be expecte ed, that sales will generatee adequate reevenue to offsset costs and d profit margiin. maintain tthe projected When the ey don’t, it is u usually a resu ult of inadequ uate communnication betw een sales and d operation regardingg process capaacity, yield lim mits and markketing commiitments. Without aacceptable sales and proce ess forecasts the plant is ddriven blindly by short‐term m sales demaand without re ealistic regard d for managin ng production n cost. Approopriately foreccasting produ uction and salles makes it p possible to efffectively projject inventoryy shortages a nd surplus months ahead enabling adju ustment to both saales sourcing and to produ uction schedu ules. performance ccomes from m measuring an nd managing yyour processiing equipmen nt and flow Optimal p configuration. Optimall profit comess from balanccing plant perrformance an nd capacity with sales dem mand. mind that even n a butcher knows before he starts thatt there is a lim mited quantitty of filet miggnon Keep in m available in his processs. He knows that there will be a lot morre hamburgerr along with vvarious roastss and steaks. He e also knows that there is a significant aamount of hooof, hide and miscellaneou us waste. Thee butcher le earns to price e and plan acccordingly. Without aan effective m means of forecasting there e is no practic al means of ccreating a com mmon undersstanding of capabillities and limits among sale es and operattions manageers and therefore no hopee of optimizingg profit. The spreaadsheet show wn as Fig#7 is a simplified e example of thhe basic details included in n modeling an nd balancingg sales, production, invento ory and cost. Key sales, prooduction and d inventory deetails are projjected months ahead. n target of Results arre used to adjjust schedules, modes, sales sourcing aand pricing wiith a common optimizingg profit. Agg gregates Perf formance Man nagement: “I Identify Whatt You Need” “If You A Always Do Whatt You Have Alwa ays Done ...You A Always Get Wha at You Always G Got” ation and perfformance opttimization con nsultant with more Alan R. Beessen, P.E., is a process‐design, automa than 35 yeears of experience in the a aggregates an nd mining inddustries. abeessen@quarryyengineers.co om . ant has more than 30 yearrs of experience developingg new and innnovative prod ducts for the Sam Sawa aggregatee and mining industries. He holds two m masters degreees in Mechannical Engineeering, and worked with Nord dberg Inc. beffore starting IInnotech Solutions in Januaary of 2000. H He has extenssive experiencce analyzing mining and a aggregate cirrcuits, proposing substantiial improvemeents and impllementing thee changes tthat have mett or exceeded d customers’ eexpectations. ssawant@ttheinnotechso olutions.com Agg gregates Perf formance Man nagement: “I Identify Whatt You Need” “If You A Always Do Whatt You Have Alwa ays Done ...You A Always Get Wha at You Always G Got”