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. [email protected]
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”