Exam 2: Ch 5 & 6 Flashcards
Productivity
A measure of process performance
Productivity = Outputs / Inputs
Single-factor productivity
Measures output levels relative to single input
Batteries produced / Direct Labor hours
Multi-factor productivity
measures output levels relative to more than one input
Batteries produced / (machine hours + Direct labor hours)
Total productivity
measures output levels relative to all the inputs
Total nightly Sales / Total nightly costs
Productivity Growth
100% [ (Current productivity - Previous productivity) / Previous Productivity ]
Labor productivity on the ABC line was 40units/hr in 2018. In 2019, labor productivity is 42units/hr. What is the productivity growth from 2018 to 2019?
Productivity Growth = 100%{ (42 - 40) / 40 ]
Efficiency
a measure of process performance; the ratio of actual outputs to standard outputs.
E = 100% [ (actual outputs / std. outputs) ]
or
E = 100% [ std. time / actual time) ] for one unit
Standard output
an estimate of what should be produced, given a certain level of resources.
Cycle Time
the total elapsed time needed to complete a business process
Percent Value-added time
the percentage of total cycle time that is spent on activities that actually provide value
%ValueAddedTime = 100% (value-added time) / (total cycle time)
Capacity
the capability of a worker, a machine, a workcenter, a plant, or an organization to produce output in a time period.
Capacity Decisions
- How much capacity is needed? how is it measure?
- When do we need capacity?
- What form of capacity is needed?
Theoretical capacity
the maximum output capability, allowing for no adjustments for preventive maintenance, unplanned downtime, or the like.
Rated capacity
the long term expected output capability of a resource or system.
Actual output
rate of output actually achieved
Measuring System Effectiveness
Theoretical: 50 Trucks/day
Rated: 40 trucks/day
Actual output: 36 trucks/day
Efficiency = Actual output / rated capacity
36 / 40 = 90%
Utilization = actual output / theoretical capacity
36 / 50 = 72%
*measured as percentages
Examples of capacity
Law firm: billable hours vs number of lawyers
Textiles factory: spinning hours vs number of machines
car wash: cars per hour: amount of water, reliability, chemicals
Controllable factors
of shifts, Number of machines, # of employees, # of facilities, Training level
Uncontrollable factors
supplier problems, time of delivery
Lead capacity strategy
capacity is added in anticipation of demand
lag capacity strategy
capacity is added only after demand has materialized
match capacity strategy
balances between lead and lag by avoiding periods of high under or over utilization
Fixed costs
expenses an organization incurs regardless of the level of business activity
variable costs
expenses directly tied to the level of business activity
Total cost formula
TC = FixedCost + VariableCost * X
x = amount of business activity
Indifference point
the output level at which the two alternatives generate equal costs
** The low-cost alternative changes at the indifference point
Expected value
a calculation that summarizes the expected costs, revenues, or profits, of a capacity alternative, given several demand levels with different probabilities.
Break-even analysis
the volume level for a business at which total revenues cover total costs
BEP = FixedCost / (Reveue - VariableCost)
Service Capacity Planning
Present a number of challenges related to:
- the need to be near customers
- the need to match the timing of demand
- the inability to match the timing of demand
- the inability to store services
- the degree of demand volatility
Theory of constraints
an approach to visualizing and managing capacity which recognizes that nearly all products and services are created through a series of linked processes, and in every case there is at leas one process step that milits throughput for the entire chain.
Steps to theory of constraints
- Identify the constraint
- exploit the constraint
- subordinate everything to the constraint
- elevate the constraint (try to increase its capacity)
- find the new constraint
Littles Law
a law that holds true for any system that has reached a steady state. the steady state is the point where inventory has had time to build up in the system and the average number of arrivals per period of time equals the average number of departures
Inventory = Rate x Time
