Capacity Planning, Aggregate Scheduling, Master Schedule, and Short-Term Scheduling

1
Capacity Planning, Aggregate Scheduling, Master
Schedule, and Short-Term Scheduling
Capacity Planning 1. Facility size 2.
Equipment procurement
Long-term
Aggregate Scheduling 1. Facility utilization
2. Personnel needs 3. Subcontracting
Intermediate-term
Master Schedule 1. MRP 2. Dis-aggregation
of master plan
Intermediate-term
Short-term
Short-term Scheduling 1. Work center loading
2. Job sequencing
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Scheduling Low-Volume Systems

• Loading - assignment of jobs to process centers
• Sequencing - determining the order in which jobs
  will be processed
• Job-shop scheduling
• Scheduling for low-volume systems with many
  variations in requirements

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Loading Jobs in Work Centers

• Assigning jobs to work centers
• Considerations
• Job priority (e.g., due date)
• Capacity
• Work center hours available
• Hours needed for job
• Approaches
• Gantt charts (load scheduling) - capacity
• Assignment method - job to specific work center

4
Loading

• Two Approaches to loading
• - Finite Loading limit the amount of work that
  is released to a given work center on the basis
  of capacity consideration.
• Input/output control is a method for keeping
  track of assigned resource (input) and the work
  completed by a resources (output). This helps
  identify a backlog (input rate in greater that
  output rate). The remove a backlog to slow down
  the input.

5
Loading

• - Infinite loading assign job to center
  regardless of available capacity. This requires
  that proper planning has been done to make sure
  enough capacity is available to take care of all
  work to be done.

6
Scheduling

• Definition Determination of when something is to
  be done and the tasks and activities required to
  do it. Establishing the timing of the use of
  equipment, facilities and human activities in an
  organization
• Scheduling aids in on-time completion
• Direct link to value perceived by customers
• Scheduling improves the utilization of the firms
  resources
• Direct link to productivity

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Strategic Implications of Short-Term Scheduling

• By scheduling effectively, companies use assets
  more effectively and create greater capacity per
  dollar invested, which, in turn, lowers cost
• This added capacity and related flexibility
  provides faster delivery and therefore better
  customer service
• Good scheduling is a competitive advantage which
  contributes to dependable delivery

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The Goals of Short-Term Scheduling

• Minimize completion time
• Maximize utilization (make effective use of
  personnel and equipment)
• Minimize WIP inventory (keep inventory levels
  low)
• Minimize customer wait time

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Scheduling Services Considerations

• Scheduling services different from manufacturing
• Inability to store or inventory services
• Random nature of customer requests for service
• Point of customer contact
• Back-office operations
• Front-office operations

10
Choosing a Scheduling Method

• Qualitative factors
• Number and variety of jobs
• Complexity of jobs
• Nature of operations
• Quantitative criteria
• Average completion time
• Utilization ( of time facility is used)
• WIP inventory (average jobs in system)
• Customer waiting time (average lateness)

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Forward and Backward Scheduling

• Forward scheduling begins the schedule as soon
  as the requirements are known
• jobs performed to customer order
• schedule can be accomplished even if due date is
  missed
• often causes buildup of WIP
• Backward scheduling begins with the due date of
  the final operation schedules jobs in reverse
  order
• used in many manufacturing environments,
  catering, scheduling surgery

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Scheduling Difficulties

• Variability in
• Setup times
• Processing times
• Interruptions
• Changes in the set of jobs
• No method for identifying optimal schedule
• Scheduling is not an exact science
• Ongoing task for a manager

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Minimizing Scheduling Difficulties

• Set realistic due dates
• Focus on bottleneck operations
• Consider lot splitting of large jobs

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Sequencing

• Sequencing Determine the order in which jobs at
  a work center will be processed.
• Priority rules Simple heuristics used to select
  the order in which jobs will be processed.
• Job time Time needed for setup and processing
  of a job.

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Priority Rules for Dispatching Jobs

• First come, first served
• The first job to arrive at a work center is
  processed first
• Earliest due date
• The job with the earliest due date is processed
  first
• Shortest processing time
• The job with the shortest processing time is
  processed first
• Longest processing time
• The job with the longest processing time is
  processed first
• Critical ratio
• The ratio of time remaining to required work time
  remaining is calculated, and jobs are scheduled
  in order of increasing ratio.

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Assumptions of Priority Rules

• The setup of jobs is known
• Setup time is independent of processing sequence
• Setup time is deterministic
• There will be no interruptions in processing such
  as
• Machine breakdowns
• Accidents
• Worker illness

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First Come, First Served Rule

• Process first job to arrive at a work center
  first
• Average performance on most scheduling criteria
• Appears fair reasonable to customers
• Important for service organizations
• Example Restaurants

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SPT and LPT Rule

• SPT Schedule a job with shortest
  processing time first
• LPT Schedule a job with longest processing
  time first

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Earliest Due Date Rule

• Process job with earliest due date first
• Widely used by many companies
• If due dates important
• If MRP used
• Due dates updated by each MRP run
• Performs poorly on many scheduling criteria

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Advantages of the Critical RatioScheduling Rule

• Use of the critical ratio can help to
• determine the status of a specific job
• establish a relative priority among jobs on a
  common basis
• relate both stock and make-to-order jobs on a
  common basis
• adjust priorities and revise schedules
  automatically for changes in both demand and job
  progress
• dynamically track job progress and location

21
Two Work Center Sequencing

• Johnsons Rule technique for minimizing
  completion time for a group of jobs to be
  processed on two machines or at two work centers.
• Minimizes total idle time
• Several conditions must be satisfied

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Johnsons Rule Conditions

• Job time must be known and constant
• Job times must be independent of sequence
• Jobs must follow same two-step sequence
• Job priorities cannot be used
• All units must be completed at the first work
  center before moving to second

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Johnson's Rule - Scheduling N Jobs on Two Machines

• 1. List all jobs and their processing times each
  machine.
• 2. Select first the job with the shortest
  processing time. If the shortest processing time
  lies with the first machine, the job is scheduled
  first if with the second machine, the job is
  scheduled last.
• 3. Once a job is scheduled, eliminate it.
• Apply steps 2-3 to the remaining jobs until all
  jobs are assigned. The process will move toward
  the center of the sequence.

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Limitations of Rule-Based Dispatching Systems

• Scheduling is dynamic therefore, rules need to
  be revised to adjust to changes in process,
  equipment, product mix, etc.
• Rules do not look upstream or downstream idle
  resources and bottleneck resources in other
  departments may not be recognized
• Rules do not look beyond due dates

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Number of Servers
Single Server
Multiple Servers
Examples
Multiple Single Servers
Examples
26
Queue Discipline
First come -- first served (FCFS)
Multiple Priorities
Examples
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Project Management

• A project is a set of activities aimed at meeting
  a goal, with a defined beginning and end.

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Project Management with Certain Time Estimates

• Summary of steps
• Determine activities that need to be accomplished
• Determine precedence relationships and completion
  times
• Construct network diagram
• Determine the critical path
• Determine early start and late start schedules

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Project Scheduling When the Times of Activities
are Uncertain

• Summary of steps
• Determine the activities that need to be
  accomplished
• Determine the precedence relationships and
  completion times
• Construct the network diagram
• Determine the critical path
• Determine the early start and late start
  schedules
• Calculate the variances for the activity times
• Calculate the probability of completing by the
  desired due date

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Project Scheduling with Time Uncertainty

• The Heuristic approach to dealing with timing
  uncertainty
• Based on understanding of individual activities
  as conforming to a beta distribution
• Take three time estimates
• Optimistic - What is the (realistic) fastest we
  can get an activity done?
• Pessimistic - What is the (realistic) worst case
  scenario for delay?
• Most likely - What is our most likely estimate?

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Earliest Due Date Rule

• Process job with earliest due date first
• Widely used by many companies
• If due dates important
• If MRP used
• Due dates updated by each MRP run
• Performs poorly on many scheduling criteria

32
Best Methods among Priority Rule

• SPT and EDD are superior in all measure. SPT is
  generally the best for minimizing flow and
  average number of jobs.

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Critical Ratio (CR)

• Ratio of time remaining to work time remaining

Time remaining

CR
Work days
remaining
Due date
-
Today'
s date

Work (lead
) time remaining

• Process job with smallest CR first
• Performs well on average lateness

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Advantages of the Critical RatioScheduling Rule

• Use of the critical ratio can help to
• determine the status of a specific job
• establish a relative priority among jobs on a
  common basis
• relate both stock and make-to-order jobs on a
  common basis
• adjust priorities and revise schedules
  automatically for changes in both demand and job
  progress
• dynamically track job progress and location

35
Two Work Center Sequencing

• Johnsons Rule technique for minimizing
  completion time for a group of jobs to be
  processed on two machines or at two work centers.
• Minimizes total idle time
• Several conditions must be satisfied

36
Johnsons Rule Conditions

• Job time must be known and constant
• Job times must be independent of sequence
• Jobs must follow same two-step sequence
• Job priorities cannot be used
• All units must be completed at the first work
  center before moving to second

37
Limitations of Rule-Based Dispatching Systems

• Scheduling is dynamic therefore, rules need to
  be revised to adjust to changes in process,
  equipment, product mix, etc.
• Rules do not look upstream or downstream idle
  resources and bottleneck resources in other
  departments may not be recognized
• Rules do not look beyond due dates

38
Queuing Theory

• Where is waiting?
• Service facility
• Fast-food restaurants
• post office
• grocery store
• bank

Manufacturing Equipment awaiting repair Phone
or computer network Product orders
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Measures of System Performance

• Average number of customers waiting
• Average time customers wait
• System utilization

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Application of Queuing Theory

• We can use the results from queuing theory to
  make the following types of decisions
• How many servers to employ
• Whether to use a single fast server or a number
  of slower servers
• Whether to have general purpose or faster
  specific servers

Goal Minimize total cost cost of servers
cost of waiting
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System Characteristics

• Number of servers
• Arrival and service pattern
• Infinite Population The arrival is not
  affected by waiting line (public places, e.g.
  gas station)
• Finite Population The arrival is affect by
  waiting line.
• Queue discipline

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Number of Servers
Single Server
Multiple Servers Single line
Examples
Multiple Single Servers
Examples
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Customer Arrival rate variable follow a Poisson
Distribution
A Poisson distribution is usually assumed
This also is referred to as having random
arrivals.
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Service Time
Either an exponential distribution is assumed
Examples
OR any distribution (only single-server model is
easily solved)
Examples
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The Queue Arrival Process Determining the
Probability of x arrivals in a time period

• Queue arrivals follow a Poisson distribution.
• P(x) the probability of x arrivals in a time
  period
• x the number of arrivals per unit time
• ? the average arrival rate in a certain time
  increment
• e 2.7283 (the base of the natural logarithms)

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Managing Queue Arrivals

• A Call center receives 36 calls per hour, Poisson
  distributed. What is the probability of
  receiving 41 calls?
• ? 36
• x 41
• e 2.7283 (the base of the natural logarithms)

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