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Capacity PlanningCapacity PlanningCapacity PlanningCapacity PlanningCapacity PlanningCapacity PlanningCapacity PlanningCapacity Planning
Dr. Mohammad Abdul Mukhyi, SE., MM
Capacity
Capacity: Definition
Capacity Types
Capacity of the Supply Chain
Calculating Capacity
Introduction to Facility
Planning
HOW MUCH long range capacity will be
needed?needed?
WHEN will the additional capacity be
required?
WHERE should the facility be located?
WHAT should the layout and
characteristics of the facility be?
Strategic Capacity Planning
CapacityThe amount of resource inputs available
relative to output requirements at a
particular time
How does productivity relate to capacity?
Defining Capacity
the rate of output from an OM system per unit of timethe rate at which the firm withdraws work from the systemJumlah masukan sumberdaya-sumberdaya yang Jumlah masukan sumberdaya-sumberdaya yang tersedia relatif untuk kebutuhan keluaran pada waktutertentu.
unit keluaranwaktu
Defining Capacity
In general, production capacity is the maximum production rate of an organization (or maximum conversion rate of a production system) in any given period.system) in any given period.
Sustainable practical capacity is the greatest level of output that a plant can maintain:
within the framework of a realistic work schedule
taking account of normal downtime
assuming sufficient availability of inputs to operate the machinery and equipment in place
Berbagai Definisi:
1. Design Capacity : tingkat keluaran per satuan untuk mana pabrikdirancang.
2. Rated Capacity ; tingkat keluaran per satuan waktu yang menunjukkan bahwa fasilitas secara teoritik mempunyai kemampuanmemproduksi.
3. Standard capacity : tingkat keluaran per satuan waktu yang ditetapkan3. Standard capacity : tingkat keluaran per satuan waktu yang ditetapkansebagai sasaran pengoperasian bagi manajemen, supervisi dan paraoperator mesin, dapat digunakan sebagai dasar bagi penyusunananggaran.
4. Actual dan atau operating capacity : tingkat keluaran rata-rata per satuan waktu selama periode waktu yang telah lewat = kapasitasstandar ± cadangan-cadangan, penundaan, tingkat sisa nyata.
5. Peak capacity : jumlah keluaran per satuan waktu yang dapat dicapaimelalui maksimisasi keluaran dengan kerja lembur, menambah tenagakerja, mengurangi jam istirahat dan sebagainya
Steps in the Capacity Planning
Process
Estimate the capacity of the present
facilities.
Forecast the long-range future capacity Forecast the long-range future capacity
needs.
Identify and analyze sources of capacity
to meet these needs.
Select from among the alternative sources
of capacity.
Measures of Capacity
Output rate capacity – Suitable for a single product or a few homogeneous products
Design capacity - The maximum capacity that Design capacity - The maximum capacity that can be achieved under ideal conditions
Effective capacity utilization - The percent of design capacity actually achieved
Aggregate capacity – Suitable when a common unit of output is used
. . . more
Measures of Capacity
Rated capacity – Maximum usable
capacity of a particular facility
Input rate capacity – Suitable for service Input rate capacity – Suitable for service
operations
Percentage utilization of capacity -
Relates output measures to inputs
available
Capacity Utilization
Capacity used
level operatingBest
usedCapacity nUtilizatio =
Capacity used
Rate of output actually achieved
Best operating level
Capacity for which the process was designed
Capacity Utilization--Example
Best operating level = 120 units/week
Actual output = 83 units/weekActual output = 83 units/week
Utilization = ?Utilization = ?Utilization = ?Utilization = ?
.692units/wk 120
units/wk 83=
level operatingBest
usedCapacity nUtilizatio ==
Capacity Cushion
A capacity cushion is an additional amount of
capacity added onto the expected demand to
allow for:allow for:
greater than expected demand
demand during peak demand seasons
lower production costs
product and volume flexibility
improved quality of products and services
Supply Chain Capacity
Tactical perspective
output driven
units of output, hours workedunits of output, hours worked
strategic perspective
capability
what you can and cannot do
match capabilities with marketing needs
Ratedcapacity
=JumahMesin
Jam KerjaMesin
Persentasepenggunaan
EfisiensiSistem
X X X
Contoh:Contoh:Suatu pusat kerja beroperasi 6 hari per minggudengan basis dua sift (8 jam per sift), ada empatmesin dengan kemampuan sama. Bila mesindigunakan 75% dari waktu pada tingkat efisiensisistem sebesar 90%
Jawab :
Rated Capacity = (4) (8x6x2) (0,75) (0,90)
= 259 jam kerja standar/minggu= 259 jam kerja standar/minggu
Types of Capacity
Maximum
Effective
DemonstratedDemonstrated
Planning Effects of Capacity Types
Types of Capacity:
Maximum Capacity (aka Design)
Defined: The highest rate of output that a process can achieve
Calculation involves the following assumptions:Calculation involves the following assumptions:
equally skilled workers
no time loss due to changeovers or product differences
no loss of capacity due to PM or planned downtime
no OT work or heroic employee efforts
Are these assumptions realistic?
Types of Capacity:
Effective Capacity
Defined: the output rate that managers
expect for a given process
Why would you operate below maximum?Why would you operate below maximum?
Types of Capacity:
Demonstrated Capacity
Defined: the actual level of output for a
process over a period of time, i.e., the process over a period of time, i.e., the
average of output over time
Why might this number be different than
maximum or effective capacity?
Types of Capacity:
Demonstrated Capacity
Demonstrated capacity
what we actually observewhat we actually observe
can be affected by numerous factors
problems with input
problems internally
nature of the product
new vs standard
Capacity within the Supply
Chain
Must deal with the issue of bottlenecks and
system constraints.
Capacity defined by:Capacity defined by:
information systems
infrastructure
physical capacity
logistics capacity
supplier capacity
relationship management
Bottlenecks
Must look for bottleneck
constraining resource
how identifiedhow identified
too much or too little inventory
overtime
why important
limits output
determines lead time
determines ability of system to make money
Bottlenecks - Con’t
Types of bottlenecks
output based
time-basedtime-based
These bottlenecks may the same or they may be
different
Keys to success
keep the bottlenecks busy
inventories/signals
invest in bottlenecks
Capacity - calculating
Level of output of a plant or system is
dependent on how it is organized
capacity in sequencecapacity in sequence
linear operations
capacity in parallel
multiple alternative operations
any machine can be used
Capacity - Sequential
Capacity of a system or process is based
on the operation with the lowest amount
of capacityof capacity
Keys
convert into the same units of measurement
ensure that we are talking about the same
dimensions
effective vs design vs demonstrated
capacity taken over the same time
Capacity - Sequential
We have a process that makes cans
Operation 1 - punches out tops and bottoms
2 lids for every can2 lids for every can
produces 250 lids per minute
Operation 2 - body
1 body for every can
produces 175 bodies per minute
Operation 3 - mating
makes the can
produces 7500 cans per hour
Capacity - Parallel
Capacity of the system or operation is based on
the sum of the capacities of the various
machines that make up the operation.
Operation 3 has 4 machines
machine 1 - 90 pieces per minute
machine 2 - 110 pieces per minute
machine 3 -120 pieces per minute
machine 4 - 80 pieces per minute
Total capacity for operation 3 = 400 pieces/min
Capacity Management Tools:
Calculating Capacity
1. Describe the general flow of activities within the process
2. Establish the time period
3. Establish a common unit3. Establish a common unit
4. Identify the Maximum capacity for the overall process
5. Identify the Effective capacity for the overall process
6. Determine the Demonstrated capacity
7. Compare the Demonstrated, Effective and Maximum Capacities and take appropriate actions
Capacity - Example
Mondavi Plant
Draw a diagram
What is its capacity
Why is it hard to calculate
Other Factors to Consider
Setups
reduce the capacity of the facility
capacity is finite wrt timecapacity is finite wrt time
Relevant vs irrelevant
relevant also depends on the options
considered
also depends on the level of capacity
utilization
Relevant Analysis
Consider the following
for a machine, what is the impact of one for a machine, what is the impact of one
additional hour of setup if the machine is
50% utilized?
What is the impact of one additional hour
of setup if the machine is 85% utilized?
Importance of Setup Reduction
Setup reduction (SMED) can reduce setup times
by 30 to 50% without significant investments.
When teams work to reduce process variation or
to improve safety, handling, preventive
maintenance or housekeeping, they also tend to
reduce setup times.
When setup times decrease, setup labor and
startup problems decrease.
Setup Reductions
When setup times decrease, it is economical to
run smaller lots, which tend to reduce
inventories, scrap, and rework.inventories, scrap, and rework.
The habit of continuous improvement must not
be discouraged (even if your equipment is not
the bottleneck).
As conditions change, a non-bottleneck can
easily become a bottleneck.
Capacity Management Tools:
Input/Output Control
A tool that manages work flows to
match the demonstrated capacity of
processprocess
Prevent problems by using “plan your
work, work your plan” rule
Economies of Scale
Best operating level - least average unit cost
Economies of scale - average cost per unit
decreases as the volume increasesdecreases as the volume increases
Diseconomies of scale - average cost per unit
increases as the volume increases
Other considerations
Subcontractor and supplier networks
Focused production
Economies of scope
Economies and Diseconomies
of ScaleAverage Unit
Cost of Output ($)
Economies DiseconomiesDiseconomies
Annual Volume (units)Annual Volume (units)
Best Operating Level
Economiesof Scale
DiseconomiesDiseconomiesof Scaleof Scale
Economies and Diseconomies
of Scale
Average UnitCost of Output ($)
100100100100----unitunitunitunitplantplantplantplant
Optimum Plant Size
Annual Volume (units)
200200200200----unitunitunitunitplantplantplantplant
300300300300----unitunitunitunitplantplantplantplant
400400400400----unitunitunitunitplantplantplantplant
The Learning Curve Effect
60
70
80
90
100
Co
st/
Tim
e p
er
rep
eti
tio
n
Cost
10
20
30
40
50
60
0 20 40 60 80 100
Number of repetitions (Volume)
Co
st/
Tim
e p
er
rep
eti
tio
n
The Learning Curve Effect
Observe, that the per unit cost (or price) of
the product (or service) declines the product (or service) declines
exponentially as the number of
repetitions increases
Capacity Focus
Should manufacturers attempt to excel on all production objectives?on all production objectives?
Plants within plants (Skinner)Extend focus concept to operating level
Capacity Flexibility
Flexible plantsFlexible processesFlexible processesFlexible workers
Capacity Planning
Units
per
Stage 1 Stage 2 Stage 3
6,000 7,000 4,500
What will happen to WIP inventory?
Issue: How to maintain system balance?
per
month
6,000 7,000 4,500
Analyzing Capacity-Planning
Decisions
Break-even Analysis
Present-Value AnalysisPresent-Value Analysis
Decision Tree Analysis
Computer Simulation
Waiting Line Analysis
Linear Programming
Determining Capacity
Requirements
Forecast sales within each individual product lineproduct lineCalculate equipment and labor requirements to meet the forecastsProject equipment and labor availability over the planning horizon
Example: Capacity
Requirements
A manufacturer produces two lines of ketchup, FancyFineand a generic line. Each is sold in small and family-size plastic bottles. plastic bottles. The following table shows forecast demand for the next four years.
Y ear: 1 2 3 4
F a ncyF ine
S mall (0 0 0 s) 5 0 6 0 8 0 1 0 0
F amily (0 0 0 s) 3 5 5 0 7 0 9 0
G eneric
S mall (0 0 0 s) 1 0 0 1 1 0 1 2 0 1 4 0
F amily (0 0 0 s) 8 0 9 0 1 0 0 1 1 0
Example: Capacity
Requirements
The Product from a Capacity Viewpoint
Are we really producing two different types of ketchup from the standpoint of capacity ketchup from the standpoint of capacity requirements?
Example: Capacity RequirementsEquipment and Labor Requirements
Year: 1 2 3 4
Small (000s) 150 170 200 240
Family (000s) 115 140 170 200
Three 100,000-units-per-year machines are available for small-bottle production. Two operators required per machine.
Two 120,000-units-per-year machines are available for family-sized-bottle production. Three operators required per machine.
Example: Capacity RequirementsEquipment and Labor Requirements
• Total machine capacity available for small-bottle production: 3*100,000=300,000 units/year
• Total machine capacity available for family-sized-bottle • Total machine capacity available for family-sized-bottle production: 2*120,000=240,000 units/year
• Total labor capacity required for small-bottle production: 3*2=6 operators
• Total labor capacity required for family-sized-bottle production: 2*3=6 operators
Example: Capacity
Requirements
Y ear: 1 2 3 4
S mall (000s) 150 170 200 240
F amily (000s) 115 140 170 200
S m all M ach. C ap . 300 ,000 Labor 6S m all M ach. C ap . 300 ,000 Labor 6
F am ily-size M ach. C ap . 240 ,000 Labor 6
S m all
P ercen t capacity used 50 .00% 56.67% 66.67% 80.00%
M achine requ irement 1 .50 1 .70 2 .00 2 .40
Labor requ irement 3 .00 3 .40 4 .00 4 .80
F am ily-size
P ercen t capacity used 47 .92% 58.33% 70.83% 83.33%
M achine requ irement 0 .96 1 .17 1 .42 1 .67
Labor requ irement 2 .88 3 .50 4 .25 5 .00
The Decision-Making Process
Problem Decision
Quantitative AnalysisLogicHistorical DataMarketing ResearchScientific AnalysisProblem
?Decision
!Scientific AnalysisModeling
Qualitative AnalysisEmotionsIntuitionPersonal Experience& MotivationRumors
Six Steps of the Decision
Process
1 Defining the problem and the factors that influence it
2 Establishing decision criteria and goals
3 Formulating a model or relationship between goals and variables3 Formulating a model or relationship between goals and variables
4 Identifying and evaluating alternatives
5 Selecting the best alternative
6 Implementing the decision
Fundamentals of Decision
Theory
The three types of decision models:
1 Decision making under certainty
2 Decision making under risk
3 Decision making under uncertainty
Terms:
Alternative: course of action or choice
State of nature: an occurrence over which the decision maker has no control
Decision Making Under
Uncertainty
Maximax
find the alternative that maximizes the maximum outcome for every alternative.outcome for every alternative.
Maximin
find the alternative that maximizes the minimum outcome for every alternative.
Equally likely
find the alternative with the highest average outcome
Decision Tree Analysis
Structures complex, multiphase decisions
Allows objective evaluation of Allows objective evaluation of
alternatives
Incorporates uncertainty
Develops expected values
Decision Tree Analysis
Symbols used in decision tree:Symbols used in decision tree:Symbols used in decision tree:Symbols used in decision tree:
A decision node from which one of several A decision node from which one of several
alternatives may be selected.
A state of nature node out of which one
state of nature will occur.
Decision Tree Analysis
1 Define the problem
2 Structure or draw the decision tree
3 Assign probabilities to the states-of-nature
4 Estimate the payoffs for each possible combination of alternative and state-of-nature
5 Solve the problem by computing expected monetary values (EMV) for each state-of-nature node
Example 1: Decision Tree
Analysis
Good Eats Café is about to build a new restaurant. An architect has developed three building designs, each with a different seating capacity. Good Eats estimates that with a different seating capacity. Good Eats estimates that the average number of customers per hour will be 80, 100, or 120 with respective probabilities of 0.4, 0.2, and 0.4. The payoff table showing the profits for the three designs is on the next slide.
Example 1: Decision Tree
Analysis
Payoff TablePayoff TablePayoff TablePayoff Table
Average Number of Customers Per Hour
c1 = 80 c2 = 100 c3 = 120
Design A $10,000 $15,000 $14,000
Design B $ 8,000 $18,000 $12,000
Design C $ 6,000 $16,000 $21,000
� Expected Value ApproachExpected Value ApproachExpected Value ApproachExpected Value Approach
Calculate the expected value for each decision. The
Example 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree Analysis
Calculate the expected value for each decision. The decision tree on the next slide can assist in this calculation. Here d1, d2, d3 represent the decision alternatives of designs A, B, C, and c1, c2, c3 represent the different average customer volumes (80, 100, and 120) that might occur.
� Decision Tree
.2.2
.4.4
.4.4
.4.4
dd11
cc11
cc
cc22
cc33
PayoffsPayoffs
10,00010,000
15,00015,000
14,00014,000
22
Example 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree Analysis
11
.4.4
.2.2
.4.4
.4.4
.2.2
.4.4
dd22
dd33
cc11
cc11
cc22
cc22
cc33
cc33
8,0008,000
18,00018,000
12,00012,000
6,0006,000
16,00016,000
21,00021,000
33
44
�� Expected Value For Each DecisionExpected Value For Each DecisionExpected Value For Each DecisionExpected Value For Each DecisionExpected Value For Each DecisionExpected Value For Each DecisionExpected Value For Each DecisionExpected Value For Each Decision
dd11
EV = .4(10,000) + .2(15,000) + .4(14,000)EV = .4(10,000) + .2(15,000) + .4(14,000)= $12,600= $12,600
Design ADesign A22
Example 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree AnalysisExample 1: Decision Tree Analysis
hoosehoose the design with largest EV the design with largest EV ---- Design C.Design C.
33
44
dd22
dd33
EV = .4(8,000) + .2(18,000) + .4(12,000)EV = .4(8,000) + .2(18,000) + .4(12,000)= $11,600= $11,600
EV = .4(6,000) + .2(16,000) + .4(21,000)EV = .4(6,000) + .2(16,000) + .4(21,000)
= = $14,000$14,000
Design BDesign B
Design CDesign C
1 1
A Sequence of Decisions
National DecisionNational Decision
Political, social, economic stability;
Currency exchange rates; . . . . .
Climate; Customer concentrations;
Regional DecisionRegional Decision
Community DecisionCommunity Decision
Site DecisionSite Decision
Climate; Customer concentrations;
Degree of unionization; . . . . .
Transportation system availability;
Preference of management; . . . . .
Site size/cost; Environmental impact;
Zoning restrictions; . . . . .
Region Location Decision
Corporate desires
Attractiveness of region (culture, taxes, climate, etc.)
Labor availability, costs, attitudes toward unionLabor availability, costs, attitudes toward union
Cost and availability of utilities
Environmental regulations of state and town
Government incentives
Proximity to raw materials & customers
Land/construction costs
Site Location Decisions
Site size and cost
Air, rail, highway, waterway systemsAir, rail, highway, waterway systems
Zoning restrictions
Nearness of services/supplies needed
Environmental impact issues
Factors Affecting the
Location Decision
Economic
Site acquisition, preparation and construction Site acquisition, preparation and construction
costs
Labor costs, skills and availability
Utilities costs and availability
Transportation costs
Taxes
. . . more
Factors Affecting the
Location Decision
Non-economic
Labor attitudes and traditionsLabor attitudes and traditions
Training and employment services
Community’s attitude
Schools and churches
Recreation and cultural attractions
Amount and type of housing available
Facility Types and Their
Dominant Locational Factors
Mining, Quarrying, and Heavy Manufacturing
Near their raw material sources
Abundant supply of utilities
Land and construction costs are inexpensiveLand and construction costs are inexpensive
Light Manufacturing
Availability and cost of labor
Warehousing
Proximity to transportation facilities
Incoming and outgoing transportation costs
. . . more
Facility Types and Their
Dominant Locational Factors
R&D and High-Tech Manufacturing
Ability to recruit/retain scientists, engineers, etc.
Near companies with similar technology interests
Retailing and For-Profit Services
Near concentrations of target customers
Government and Health/Emergency Services
Near concentrations of constituents
Some Reasons the
Facility Location Decision
Arises
Changes in the market
Expansion
ContractionContraction
Geographic shift
Changes in inputs
Labor skills and/or costs
Materials costs and/or availability
Utility costs
. . . more
Some Reasons the
Facility Location Decision
Arises
Changes in the environment
Regulations and lawsRegulations and laws
Attitude of the community
Changes in technology
Analyzing Location Decisions
Quantitative Approaches
Qualitative ApproachesQualitative Approaches
Integrating Qualitative and Quantitative
Data
Analyzing Location Decisions
Quantitative Approaches
Decision trees
Center of Gravity Method
Finds best distribution center locationFinds best distribution center location
Location Breakeven Methods
Special case of breakeven analysis
Transportation Method
Special case of LP method
NPV analysis
Computer Simulation
Analyzing Location Decisions
Mixed Approaches
Weighted Methods which:
Assigns weights and points to various factors
Determines tangible costsDetermines tangible costs
Investigates intangible costs
Examples:
Rating scale approach
Relative-aggregate-scores approach
Example 1: Locational Breakeven
Analysis
200
250
Akron
Bowling Green
Chicago
0
50
100
150
0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200
Akron
Lowest cost Bowling Green
Lowest cost
Chicago
Lowest cost
Penentuan kebutuhan
kapasitas
∑=
++=
x
1iiiiiistd ]NB)ST(O[ H
Hstd = jumlah total jam sumber daya yang dibutuhkan untukstd
memenuhi permintaanOi = jumlah unit keluaran X yang diperlukanTi = waktu pengoperasian standar per unit XSi = waktu persiapan standar peru unit keluaran XBi = waktu standar untuk mempersiapkan sekumpulan XNi = jumlah kumpulan X yang diperlukanX = jumlah jenis produk
mwo
stdact
E P E
H H =
Hact = jumlah sumberdaya nyata yang dibutuhkanHstd = jumlah total jam sumber daya yang dibutuhkan untuk
memenuhi permintaanEo = efisiensi organisasionalPw = produktivitas operatorEm = efisiensi mesin, faktor pemeliharaan, faktor mesin rusak
avl
actr
H
HN =
Nr = jumlah unit sumberdaya yang dibutuhkanH = jumlah jam yang tersedia per unit sumberdaya selama
r
Havl = jumlah jam yang tersedia per unit sumberdaya selamaperiode waktu tertentu
Permintaan produk sebesar 200 unit, ada 22 hari kerja per bulan. Waktu pengoperasian standar per unit sebesar 8 jam, waktupersiapan setengah jam setiap unit. 200 unit akan diproses dalam 10 kumpulan, pada setiap akhir kumpulan, mesin harus diuji dandisesuaikan kembali sebelum kumpulan berikutnya diproses, waktudisesuaikan kembali sebelum kumpulan berikutnya diproses, waktupenyiapan memerlukan 4 jam. Efisiensi organisasional diperkirakan95% dan mesin beroperasi dengan efisiensi 90%. Selama mesindioperasikan dengan kecepatan wajar diperlukan waktu penundaanuntuk pemeliharaan selama 48 menit per hari, mesin-mesindijalankan 8 jam per hari dan para operator mesin bekerja sesuaidengan standar (1,00).
Berapa jumlah mesin yang dibutuhkan untuk memenuhi permintaanbulanan?
nyata jam 2.035,1 90,0)(0,1(95,0
740.1H
standar jam 1.7404(10)0,5)200(8H
act
std
==
=++=
mesin 56,11)8(22
1,035.2N r ==
Learning Curve dan Kapasitas
Y = C XS
Log Y = S log X + Log C
X = jumlah unit produk yang dibuatX = jumlah unit produk yang dibuat
C = jam kerja langsung yang diperlukan oleh produksi
pertama
Y = jumlah jam kerja rata-rata per unit produk
S = slope = (log % -2)/log 2
Untuk kurva 80%S = log 80-2/log 2
= 1,90309 – 2 / 0,30103 = -0,322
Perusahaan menerima kontrak pembuatan produk sejumlah 50 unit. Produk
pertama memerlukan 2.000 jam tenaga kerja langsung, dengan learning curve
yang berlaku sebesar 80% waktu yang diperlukan per unit produk :yang berlaku sebesar 80% waktu yang diperlukan per unit produk :
Log Y = -0,322. log 50 + log 2.000
= -0,322(1,69897) + 3,30103
= 2,75396
Y = 567,491 jam kerja langsung
literatur
T. Hani Handoko, Dasar-dasar manajemen produksi dan
operasi, bPFE, UGM, Yogyakarta.
Sheri Nemeth and Mick Peters, Production and Operating Sheri Nemeth and Mick Peters, Production and Operating
Management.
N. Gaither and Frazier, Production and Operations
Management, 8th Edition, Duxbury Press, NY, NY, 1999.
(Road server) Handouts for most classes are available on
the ROAD server. The handouts can be accessed at: _
HYPERLINK http://road.uww.edu
__http://road.uww.edu_