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By Drew Harris
Scope
Time
Quality
Cost
Seminar by: Drew Harris Managing the Critical Constraints 2
Budget
Control
Program Goals
Cutting Edge
Technologies
Fab Schedules
New Developments
Employee Performance
Training & Development
Program Schedules
Component
cost-optimization
Fabrication
techniques
Productivity
 Clearly define what is in Scope and out of
scope, as scope creep impacts the budget
allocations.
 Ensure that new developments receive
budget prior to being included in scope.
Seminar by: Drew Harris Managing the Critical Constraints 3
 To control costs you must efficiently
manage the cost drivers
 Resources
 Machinery and Technology
 Materials
 Quality
 Consultants, Contractors, and specialty shops
 Delivery and expediting costs
 Schedule slips and changes.
Seminar by: Drew Harris Managing the Critical Constraints 4
 It is imperative that processes be measured to determine
performance, productivity, quality and repeatability.
 Equipment capabilities must be known and maintained
through scheduled maintenance.
 Materials must meet specifications and adhere to tight
delivery schedules.
 CAD/CAE/CAM technology should follow QA standards and
adhere to thorough documentation and file storage.
 Inventory turns and supply stocks must be fine tuned.
 Inputs and Outputs must be agreed upon between upstream
and downstream customers. A high satisfaction level should
be achieved and maintained.
Seminar by: Drew Harris Managing the Critical Constraints 5
 Develop an all encompassing Quality
Assurance plan that covers;
 Design and Engineering
 In-house Fabrication
 Technical services
 Ensure that all suppliers follow the QA plan
▪ Outside fabrication
▪ Assembly
▪ Materials
▪ Post processing
Seminar by: Drew Harris Managing the Critical Constraints 6
Seminar by: Drew Harris Managing the Critical Constraints 7
TIME SCOPE COST
CONSTRAINT
(Non-Flexible)
ENHANCE
(Somewhat
Flexible)
ACCEPT
(Flexible)
The Critical Constraints are anchored together and set, based on the
objective of the program. In this example, Scope is basically fixed and
non-flexible. This scope anchor allows for a somewhat flexible cost
constraint and a flexible time constraint (scheduling).
So let us now proceed to look at the Time Constraint of Scheduling for
the remainder of this talk.
 Scheduling has been defined as "the art of assigning
resources to tasks in order to insure the termination of
these tasks in a reasonable amount of time" (1).
According to French (2), the general problem is to find a
sequence, in which the jobs (e.g., a basic task) pass
between the resources (e.g., machines), which is a
feasible schedule, and optimal with respect to some
performance criterion.
References
1. M. Dempster, J. Lenstra, and R. Kan, Deterministic and stochastic scheduling:
introduction. Proceedings of the NATO Advanced Study and Research Institute on
Theoretical Approaches to Scheduling Problems, D. Reidel Publishing Company: 3-14,
1981.
2. S. French, Sequencing and Scheduling. New York: Halsted Press, 1982.
Seminar by: Drew Harris Managing the Critical Constraints 8
 Underestimating planned tasks
 Creative designs requiring additional learning curve
time.
 Capacity imbalances
 Unavailable critical resources, technology or
equipment
 Unusually low resource or equipment utilization
 “Hot” Tasks interjected into the plan.
 Conflicting priorities
 Lack of an integrated schedule
 Delays
 Absenteeism
 Rework
Seminar by: Drew Harris Managing the Critical Constraints 9
 Form a team to get to the root
cause of each impact. Go down 5
levels w/Why?
 Verify the root causes with data
 Complete the countermeasure
table with specific actions.
 For each root cause, identify up
to 3 broad countermeasures
(what to do).
 Rank the effectiveness of each
countermeasure.
 Identify the specific
implementation actions (how?)for
each countermeasure.
 Rank the feasibility (time, cost) of
each specific action and decide
which to implement.
Seminar by: Drew Harris Managing the Critical Constraints 10
Seminar by: Drew Harris Managing the Critical Constraints 11
Worse Case Scenario Std. Use of time (Mins)
Delays & Interferences 120 20
2-15 min Breaks 30 30
Daily Meetings 110 60
Focused Time 220 370
220
370
110
60
30
30
120
20
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Daily Utilization
Comparison for an 8 hr (480 Mins.) day
Focused Time Daily Meetings 2-15 min Breaks Delays & Interferences
46%
77%
As we push the
upper limit of
technology in our
development, work
centers, and
processes …we
must dig deeper
and utilize advance
scheduling theories
and optimization to
accurately plan
these events.
Seminar by: Drew Harris Managing the Critical Constraints 12
 Develop an Integrated schedule showing material
shipments and processing flowing into the schedule for
design, engineering, machining and assembly. It is
imperative to include the people, equipment, and material
that are used to complete tasks .
 Manage the critical path The series of tasks that must be
completed on schedule for a project to finish on schedule.
 Understand the network logic associated with each
schedule.
 Improve the duration estimates and reduce variation.
 Status and update the schedule frequently.
 Document the key learning of each schedule
performance.
Seminar by: Drew Harris Managing the Critical Constraints 13
MEASURE AND TRACK ESTIMATING
ACCURACY TO IMPROVE ESTIMATES
INDIVIDUAL
EST.
TEAM
ESTIMATE
ACTUAL
DURATION
ACCURACY
(INDIV)
ACCURACY
(TEAM)
TASK 1
6.0 7.6 8.0 75% 95%
TASK 2
2.7 3.1 2.8 98% 113%
TASK 3
1.75 2.3 1.8 97% 128%
TASK 4
10.2 13.0 12.6 81% 104%
EXPECTED TOLERANCE OF +/- 5%
Seminar by: Drew Harris Managing the Critical Constraints 14
 Use and integrated schedule and manage the critical path
Seminar by: Drew Harris Managing the Critical Constraints
15
 Develop Key metrics to assess deliveries and productivity.
 Determine and eliminate the delays that affect utilization
 Plan in “Critical and Hot” tasks and priorities
 Utilize PERT and mathematical algorithms to improve shop
loading.
 Deploy a rigorous scheduling process and include backward
and forward scheduling techniques
 Perform capacity analysis on resources, work centers,
equipment and technology.
 Improve team dynamics to gain synergy to function at a
higher level
 Optimize the integrated schedule through an advanced
scheduling and simulation modeling.
Seminar by: Drew Harris Managing the Critical Constraints 16
Seminar by: Drew Harris Managing the Critical Constraints
17
Metrics to aid in Scheduling accuracy!
Do the following Results Metrics exist?
On Time Delivery (OTD)
Order-Fulfillment Lead Time (OFLT)
Dock to Dock (DTD)
First Time Through quality (FTT)
Health and Safety metrics
Days lost due to accidents
Absenteeism
Employee Turnover
Do the following Productivity Metrics exist?
Build to Schedule (BTS)
Overall Equipment effectiveness (OEE)
Value added to Non-value added ratio (VA/NVA)
 Since scheduling problems fall into the class of NP-
complete problems, they are among the most difficult to
formulate and solve.
 Thus, I have adopted ideas from the paper Job Shop Scheduling
Techniques published by; Albert Jones, PhD National Institute of
Standards and Technology and Luis C. Rabelo, Ph.D., Professor
Industrial and Manufacturing Engineering Dept. California
Polytechnic State University
 It is necessary to adopt additional parameters to
categorize the variance that impacts the job shop
schedule.
 These additional parameters will allow us to;
 Develop algorithms to improve duration estimates through
regression analysis and predictions.
 Develop a knowledgebase of known machining center
processing paths.
 Construct a Discrete Scheduling Model to Optimize solutions
Seminar by: Drew Harris Managing the Critical Constraints 18
 Consider these additional parameters to categorize schedule problems
as proposed by Graves
1. Processing complexity,
2. Scheduling criteria,
3. Parameter variability,
4. Scheduling environment.
 Processing complexity, refers to the number of processing steps and
workstations associated with the production process. This dimension
can be decomposed further as follows:
1. One stage, one processor
2. One stage, multiple processors,
3. Multistage, flow shop,
4. Multistage, job shop.
Seminar by: Drew Harris Managing the Critical Constraints 19
 The second dimension, scheduling criteria,
states the desired objectives to be met. "They are
numerous, complex, and often conflicting”.
Some commonly used scheduling criteria
include the following:
1. Minimize total schedule slippage,
2. Minimize the number of late jobs,
3. Maximize system/resource utilization,
4. Minimize in-process inventory,
5. Balance resource usage,
6. Maximize production rate.
Seminar by: Drew Harris Managing the Critical Constraints 20
 The third dimension, parameters variability, indicates
the degree of uncertainty of the various parameters of
the scheduling problem.
 If the degree of uncertainty is insignificant, the
scheduling problem could be called deterministic.
 The last dimension, scheduling environment, defined
the scheduling problem as static or dynamic.
Scheduling problems in which the number of jobs to
be considered and their ready times are available are
called static. On the other hand, scheduling problems
in which the number of jobs and related
characteristics change over time are called dynamic.
Seminar by: Drew Harris Managing the Critical Constraints 21
 Improve the basic scheduling parameters
Critical Path analysis
Integration
Visibility, Delays and Prioritizations
Learning Curves
Capacity and Utilization
 Build Knowledgebase for processing
paths, estimates and critical parameters
 Use simulation modeling as an inference
engine to manage the variables, build
processing rules, input algorithms and
distributions, all to optimize our schedule.
Seminar by: Drew Harris Managing the Critical Constraints 22
References
1. M. Dempster, J. Lenstra, and R. Kan, Deterministic and stochastic
scheduling: introduction. Proceedings of the NATO Advanced Study
and Research Institute on Theoretical Approaches to Scheduling Problems,
D. Reidel Publishing Company: 3-14, 1981.
2. S. French, Sequencing and Scheduling. New York: Halsted Press,
1982.
3. S. Graves, A Review of Production Scheduling. Operations
Research, 29: 646-675, 1981.
4. S. Gershwin, Hierarchical flow control: a framework for
scheduling and planning discrete events in manufacturing
systems. Proceedings of IEEE Special Issue on Discrete Event Systems,
77: 195-209, 1989.
Seminar by: Drew Harris Managing the Critical Constraints 23
Seminar by: Drew Harris Managing the Critical Constraints
24

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Program Management using the Triple constraints

  • 2. Scope Time Quality Cost Seminar by: Drew Harris Managing the Critical Constraints 2 Budget Control Program Goals Cutting Edge Technologies Fab Schedules New Developments Employee Performance Training & Development Program Schedules Component cost-optimization Fabrication techniques Productivity
  • 3.  Clearly define what is in Scope and out of scope, as scope creep impacts the budget allocations.  Ensure that new developments receive budget prior to being included in scope. Seminar by: Drew Harris Managing the Critical Constraints 3
  • 4.  To control costs you must efficiently manage the cost drivers  Resources  Machinery and Technology  Materials  Quality  Consultants, Contractors, and specialty shops  Delivery and expediting costs  Schedule slips and changes. Seminar by: Drew Harris Managing the Critical Constraints 4
  • 5.  It is imperative that processes be measured to determine performance, productivity, quality and repeatability.  Equipment capabilities must be known and maintained through scheduled maintenance.  Materials must meet specifications and adhere to tight delivery schedules.  CAD/CAE/CAM technology should follow QA standards and adhere to thorough documentation and file storage.  Inventory turns and supply stocks must be fine tuned.  Inputs and Outputs must be agreed upon between upstream and downstream customers. A high satisfaction level should be achieved and maintained. Seminar by: Drew Harris Managing the Critical Constraints 5
  • 6.  Develop an all encompassing Quality Assurance plan that covers;  Design and Engineering  In-house Fabrication  Technical services  Ensure that all suppliers follow the QA plan ▪ Outside fabrication ▪ Assembly ▪ Materials ▪ Post processing Seminar by: Drew Harris Managing the Critical Constraints 6
  • 7. Seminar by: Drew Harris Managing the Critical Constraints 7 TIME SCOPE COST CONSTRAINT (Non-Flexible) ENHANCE (Somewhat Flexible) ACCEPT (Flexible) The Critical Constraints are anchored together and set, based on the objective of the program. In this example, Scope is basically fixed and non-flexible. This scope anchor allows for a somewhat flexible cost constraint and a flexible time constraint (scheduling). So let us now proceed to look at the Time Constraint of Scheduling for the remainder of this talk.
  • 8.  Scheduling has been defined as "the art of assigning resources to tasks in order to insure the termination of these tasks in a reasonable amount of time" (1). According to French (2), the general problem is to find a sequence, in which the jobs (e.g., a basic task) pass between the resources (e.g., machines), which is a feasible schedule, and optimal with respect to some performance criterion. References 1. M. Dempster, J. Lenstra, and R. Kan, Deterministic and stochastic scheduling: introduction. Proceedings of the NATO Advanced Study and Research Institute on Theoretical Approaches to Scheduling Problems, D. Reidel Publishing Company: 3-14, 1981. 2. S. French, Sequencing and Scheduling. New York: Halsted Press, 1982. Seminar by: Drew Harris Managing the Critical Constraints 8
  • 9.  Underestimating planned tasks  Creative designs requiring additional learning curve time.  Capacity imbalances  Unavailable critical resources, technology or equipment  Unusually low resource or equipment utilization  “Hot” Tasks interjected into the plan.  Conflicting priorities  Lack of an integrated schedule  Delays  Absenteeism  Rework Seminar by: Drew Harris Managing the Critical Constraints 9
  • 10.  Form a team to get to the root cause of each impact. Go down 5 levels w/Why?  Verify the root causes with data  Complete the countermeasure table with specific actions.  For each root cause, identify up to 3 broad countermeasures (what to do).  Rank the effectiveness of each countermeasure.  Identify the specific implementation actions (how?)for each countermeasure.  Rank the feasibility (time, cost) of each specific action and decide which to implement. Seminar by: Drew Harris Managing the Critical Constraints 10
  • 11. Seminar by: Drew Harris Managing the Critical Constraints 11 Worse Case Scenario Std. Use of time (Mins) Delays & Interferences 120 20 2-15 min Breaks 30 30 Daily Meetings 110 60 Focused Time 220 370 220 370 110 60 30 30 120 20 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Daily Utilization Comparison for an 8 hr (480 Mins.) day Focused Time Daily Meetings 2-15 min Breaks Delays & Interferences 46% 77%
  • 12. As we push the upper limit of technology in our development, work centers, and processes …we must dig deeper and utilize advance scheduling theories and optimization to accurately plan these events. Seminar by: Drew Harris Managing the Critical Constraints 12
  • 13.  Develop an Integrated schedule showing material shipments and processing flowing into the schedule for design, engineering, machining and assembly. It is imperative to include the people, equipment, and material that are used to complete tasks .  Manage the critical path The series of tasks that must be completed on schedule for a project to finish on schedule.  Understand the network logic associated with each schedule.  Improve the duration estimates and reduce variation.  Status and update the schedule frequently.  Document the key learning of each schedule performance. Seminar by: Drew Harris Managing the Critical Constraints 13
  • 14. MEASURE AND TRACK ESTIMATING ACCURACY TO IMPROVE ESTIMATES INDIVIDUAL EST. TEAM ESTIMATE ACTUAL DURATION ACCURACY (INDIV) ACCURACY (TEAM) TASK 1 6.0 7.6 8.0 75% 95% TASK 2 2.7 3.1 2.8 98% 113% TASK 3 1.75 2.3 1.8 97% 128% TASK 4 10.2 13.0 12.6 81% 104% EXPECTED TOLERANCE OF +/- 5% Seminar by: Drew Harris Managing the Critical Constraints 14
  • 15.  Use and integrated schedule and manage the critical path Seminar by: Drew Harris Managing the Critical Constraints 15
  • 16.  Develop Key metrics to assess deliveries and productivity.  Determine and eliminate the delays that affect utilization  Plan in “Critical and Hot” tasks and priorities  Utilize PERT and mathematical algorithms to improve shop loading.  Deploy a rigorous scheduling process and include backward and forward scheduling techniques  Perform capacity analysis on resources, work centers, equipment and technology.  Improve team dynamics to gain synergy to function at a higher level  Optimize the integrated schedule through an advanced scheduling and simulation modeling. Seminar by: Drew Harris Managing the Critical Constraints 16
  • 17. Seminar by: Drew Harris Managing the Critical Constraints 17 Metrics to aid in Scheduling accuracy! Do the following Results Metrics exist? On Time Delivery (OTD) Order-Fulfillment Lead Time (OFLT) Dock to Dock (DTD) First Time Through quality (FTT) Health and Safety metrics Days lost due to accidents Absenteeism Employee Turnover Do the following Productivity Metrics exist? Build to Schedule (BTS) Overall Equipment effectiveness (OEE) Value added to Non-value added ratio (VA/NVA)
  • 18.  Since scheduling problems fall into the class of NP- complete problems, they are among the most difficult to formulate and solve.  Thus, I have adopted ideas from the paper Job Shop Scheduling Techniques published by; Albert Jones, PhD National Institute of Standards and Technology and Luis C. Rabelo, Ph.D., Professor Industrial and Manufacturing Engineering Dept. California Polytechnic State University  It is necessary to adopt additional parameters to categorize the variance that impacts the job shop schedule.  These additional parameters will allow us to;  Develop algorithms to improve duration estimates through regression analysis and predictions.  Develop a knowledgebase of known machining center processing paths.  Construct a Discrete Scheduling Model to Optimize solutions Seminar by: Drew Harris Managing the Critical Constraints 18
  • 19.  Consider these additional parameters to categorize schedule problems as proposed by Graves 1. Processing complexity, 2. Scheduling criteria, 3. Parameter variability, 4. Scheduling environment.  Processing complexity, refers to the number of processing steps and workstations associated with the production process. This dimension can be decomposed further as follows: 1. One stage, one processor 2. One stage, multiple processors, 3. Multistage, flow shop, 4. Multistage, job shop. Seminar by: Drew Harris Managing the Critical Constraints 19
  • 20.  The second dimension, scheduling criteria, states the desired objectives to be met. "They are numerous, complex, and often conflicting”. Some commonly used scheduling criteria include the following: 1. Minimize total schedule slippage, 2. Minimize the number of late jobs, 3. Maximize system/resource utilization, 4. Minimize in-process inventory, 5. Balance resource usage, 6. Maximize production rate. Seminar by: Drew Harris Managing the Critical Constraints 20
  • 21.  The third dimension, parameters variability, indicates the degree of uncertainty of the various parameters of the scheduling problem.  If the degree of uncertainty is insignificant, the scheduling problem could be called deterministic.  The last dimension, scheduling environment, defined the scheduling problem as static or dynamic. Scheduling problems in which the number of jobs to be considered and their ready times are available are called static. On the other hand, scheduling problems in which the number of jobs and related characteristics change over time are called dynamic. Seminar by: Drew Harris Managing the Critical Constraints 21
  • 22.  Improve the basic scheduling parameters Critical Path analysis Integration Visibility, Delays and Prioritizations Learning Curves Capacity and Utilization  Build Knowledgebase for processing paths, estimates and critical parameters  Use simulation modeling as an inference engine to manage the variables, build processing rules, input algorithms and distributions, all to optimize our schedule. Seminar by: Drew Harris Managing the Critical Constraints 22
  • 23. References 1. M. Dempster, J. Lenstra, and R. Kan, Deterministic and stochastic scheduling: introduction. Proceedings of the NATO Advanced Study and Research Institute on Theoretical Approaches to Scheduling Problems, D. Reidel Publishing Company: 3-14, 1981. 2. S. French, Sequencing and Scheduling. New York: Halsted Press, 1982. 3. S. Graves, A Review of Production Scheduling. Operations Research, 29: 646-675, 1981. 4. S. Gershwin, Hierarchical flow control: a framework for scheduling and planning discrete events in manufacturing systems. Proceedings of IEEE Special Issue on Discrete Event Systems, 77: 195-209, 1989. Seminar by: Drew Harris Managing the Critical Constraints 23
  • 24. Seminar by: Drew Harris Managing the Critical Constraints 24