Dr Ron Lembke Operations Management Maximum Throughput of a Process What is the capacity of the system Should we add any capacity How should we run the system Where should we keep inventory ID: 642147
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Slide1
Strategic Capacity Management
Dr. Ron Lembke
Operations ManagementSlide2
Maximum Throughput of a Process
What is the capacity of the system?
Should we add any capacity?
How should we run the system?Where should we keep inventory?
50/hr
20/hr
10/hr
40/hrSlide3
Maximum Throughput of a Process
What is the capacity of the system?
Convert to units / hr
6 min
5 min
4 min
5 min
10/hr
12/hr
15/hr
12/hrSlide4
Productivity measurementsSlide5
Productivity
Productivity = Outputs / Inputs
Partial: Output/Labor or Output/Capital
Multifactor:Output / (Labor + Capital + Energy )Total Measure:Output / InputsSlide6
Automotive Productivity
Book Data:
Jaguar: 14 cars/employee
Volvo: 29 cars/employeeMini: 39 cars/employeeSlide7
US Productivity Growth
Source: Bureau of Labor Statistics Slide8
Total Factor Productivity
Increases
Take labor and capital into account
“percentage increase in output that is not accounted for by changes in the volume of inputs of capital and labour.”
Source: Economist, 2009Slide9
Growth of Service Economy
% of Labor ForceSlide10
U.S. Productivity Gains
Services harder to make more productive
Product Development team structure (
Eg: Chrysler Prowler, Boeing 787)Facilities improvements (less WIP, better quality, flexibility)Keiretsu-like supplier cooperation -- tight cooperationSlide11
U. S. Productivity Gains
Increased 1.37% per year 1990-95
Increased 2.37% per year 1995-98
Potential sources of productivity gains:Capital investment (1.13%)
Labor Quality (0.25%)Technological progress (0.99%)Computers really are making us more productive.Source: WSJ, 8/1/00, “Further Gains in Productivity are Predicted,” A2Slide12
Improving Productivity
Develop productivity measurements– you can’t improve what you can’t measure
Identify and Improve bottleneck operations first
Establish goals, document and publicize improvementsSlide13
Hours workedSlide14
Hours Worked by Country
Source: OECD, 2012
AverageSlide15
Hours Worked and Productivity
Source
:
Eurofund
, European Working Conditions Observatory, 2012Slide16
What Would Henry Say?
Ford introduced the $5 (per day) wage in 1914
He introduced the 40 hour work week
“so people would have more time to buy”It also meant more output: 3*8 > 2*10
“Now we know from our experience in changing from six to five days and back again that we can get at least as great production in five days as we can in six, and we shall probably get a greater, for the pressure will bring better methods. Crowther, World’s Work, 1926Slide17
Forty Hour Week
Ernst Abbe, Karl Zeiss optics
1896: as much done in 9 as in 8.Slide18
Marginal Output of Time
Value of working
n
hrs is OndaAs you work more hours, your productivity per hour goes down
Eventually, it goes negative.Better to work b instead of e hrs
S.J. Chapman
,
1909, “Hours of
Labour
,” The Economic Journal 19(75) 353-373Slide19
“Crunch Mode”
Ea_spouse: 12/04
“Pre-crunch”
SO was working 7 * 13: 91 per week!Maybe time off at 6pm Saturday$5k signing bonus, couldn’t quit
Class action: April ‘06 $14.9mIgda.org “Why Crunch Mode Doesn’t Work: 6 Lessons”Slide20
Learning Curves
time/unit goes down consistently
Down by 10% as output doubles
We can use Logarithms to approximate thisWhat will our cost per unit be when we’ve made 10,000 units?If you ever need this, email me, and we can talk as much as you want
Also, see Appendix BSlide21
Example 1
Paul’s 1 2 3 4 5
Bottles 60 100 150 200 250
Bags 100 200 300 400 500
Newman’s
Bottles 75 85 95 97 98
Bags 200 400 600 650 680
Demand for each product,
by year.Slide22
Example 1
Totals 1 2 3 4 5
Bottles 135 185 245 297 348
Bags 300 600 900 1,050 1,180
bottle machines 150k/yr
Three currently = 150 * 3 = 450kbag machines 250k/yr
Five currently = 250 * 5 = 1,250kSlide23
Example 1
Bottles 135 185 245 297 348
Machines 1 2 2 2 3
Mach. usage 0.9 1.23 1.63 1.98 2.32
Workers 1.8 2.46 3.27 3.96 4.64
(2 workers per machine)
Bags 300 600 900 1,050 1,180
Machines 2 3 4 5 5Mach Usage 1.2 2.4 3.6 4.2 4.7
Workers 3.6 7.2 10.8 12.6 14.1
(3 workers per machine)Slide24
Capacity Tradeoffs
Can we make combinations in between?
150,000
Two-door cars
120,000
4-door
carsSlide25
How much do we have?
We can only sustain so much effort.
“Best Operating Level”
Output level process designed forLowest cost per unitCapacity utilization = capacity used best operating level
Hard to run > 1.0 for long Slide26
Time Horizons
Long-Range: over a year – acquiring, disposing of production resources
Intermediate Range: Monthly or quarterly plans, hiring, firing, layoffs
Short Range – less than a month, daily or weekly scheduling process, overtime, worker scheduling, etc.Slide27
Service Differences
Arrival Rate very variable
Can’t store the products - yesterday’s flight?
Service times variableServe me “Right Now!”
Rates change quicklySchedule capacity in 10 minute intervals, not monthsHow much capacity do we need?Slide28
Capacity Levels in Service
Zone of non-service
<
Zone of service
Critical Zone
Mean service rate,
Mean
arrival
rate,
=100%
=70%
150
100
100
50Slide29
Adding Capacity
Expensive to add capacity
A few large expansions are cheaper (per unit) than many small additions
Large expansions allow of “clean sheet of paper” thinking, re-design of processesCarry unused overhead for a long timeMay never be neededSlide30
Reengineering
“Business Process Reengineering” (Hammer and Champy)
Companies grow over time, adding plants, lines, facilities, etc.
Growth may not end in optimal formRe-design processes from ground upSlide31
Capacity Planning
How much capacity should we add?
Conservative Optimistic
Forecast possible demand scenarios (Chapter 11)
Determine capacity needed for likely levels
Determine “capacity cushion” desiredSlide32
Toyota Capacity
1997: Cars
and
vans?
That’s crazy talkFirst time in North America292,000 Camrys89,000
Siennas89,000 AvalonsSlide33
Capacity Sources
In addition to expanding facilities:
Two or three shifts
Outsourcing non-core activitiesTraining or acquisition of faster equipmentSlide34
Decision Trees
Consider different possible decisions, and different possible outcomes
Compute expected profits of each decision
Choose decision with highest expected profits, work your way back up the tree.Slide35
Summary
Having enough capacity is crucial
Measured productivity (single and multi-factor)
Increasing productivity key to economic growth and profitsComputed number of machines and employees neededMaking employees more productive is often cheaper than adding machines