Research and Teaching Plan

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RESEARCH AND
TEACHING PLAN
Presentation to:
Department of Information and
Decision Sciences
College of Business Administration
University of Texas at El Paso
1
PRESENTATION OUTLINE
• Describe an “interesting” research
project
• Present an overview of current research
and teaching interests/projects
• Discuss my vision for the future
2
“Interesting” Research Project:
KABOM
knowledge/activity based operations modeling
With
Carey McCleskey, Edgar Zapata, Russ Rhodes
Advanced Projects, NASA
Kennedy Space Center, FL
3
Outline for this section
• Introduction
• Previous work
• KABOM
• Project Extensions
• Project Status
4
Introduction
do you know?
• The cost per space shuttle flight?
• During the design of shuttle, the
designers expected/planned the time
between flights to be:
a) < 1 week
b) < 1 month
c) 1 - 2 months
d) 3 - 4 months
e) > 5 months
• From the above, what is the current average time
between flights?
• What is the shuttle’s design reliability?
5
Introduction
the design to operations gap
• A view of operations
by the designers
• Operations at the
Orbiter Processing
Facility (OPF) today.
6
Introduction
the causes
• Space vehicles are complex systems
• Operations was not a primary concern of designers
– Design process focused on the rocket equation
– Primary operations concern: how do we use existing facilities
– Once the vehicle worked - up to Kennedy to make it work.
• Minimizing cost was an objective (NASA’s budget
has had its ups and downs), BUT it was a “myopic”
view, minimize development cost or minimize
manufacturing cost, seldom a total cost view.
7
Introduction
things are changing
• NASA is changing.
– Moving from a service provider to a support and
monitoring entity
• Space business environment is changing
– Commercial launch capabilities have increased.
• Facilities in old USSR, Guyana, Brazil, China, and even sea
launches
– Need for launches has increased, exceeding capacity
– Interest in other commercial uses of space
• Hilton Space Hotels?- spacehotels
– The X Prize
8
Outline for this section
• Introduction
• Previous work
• KABOM
• Project Extensions
• Project Status
9
Previous work
vision spaceport
• Team approach > ground operations modeling
– Includes NASA KSC and Ames, Lockheed Martin, Boeing,
SIAC, and other related government, university, and private
organizations.
– My role: NASA fellow for the summers of 1998 and 1999.
• Objectives:
– Develop models to asses new designs: spaceport operations
- life cycle costs
– Educate vehicle designers on spaceport operations
– Connect model to design/development models and
manufacturing models
10
Previous work
vision spaceport
• First approach
– Knowledge based utility functions
– Mapped vehicle inputs to spaceport functions.
• Functions provided sense of direction: was the design an
improvement over the baseline for a function. Cost and times
derived from the deviation
• Developed a tool in Excel/VB: AATe.
– NASA Copyright.
– Used in several studies at Marshal and Langley.
– Modeling approach was applied in a second tool application developed by CCT.
11
Previous work
vision spaceport
Umax
$ or CT
Umin
0
1
F(Mc)=Si1.I, j1..Ji (Xij*SiMc/(Sy =1..ISyMc))
I
Ji
Xij
SiM
F(Mc)
# of design/assessment questions
# of options for design question i
Value of option j for design question i (0 - 1)
Strength of relation, design/assessment question i to Mc
Score for spaceport function M and characteristic c
12
Outline for this section
• Introduction
• Previous work
• KABOM
• Project Extensions
• Project Status
13
Knowledge/Activity based
Operations Modeling (KABOM)
• Objective:
– To asses the operational requirements of a vehicle
design. Determine:
• Cost per flight (cost per pound) and Cycle time
• Processes and Resources required
– Present to vehicle designers the processes required
for operation
– Address limitations of the utility function approach
• Dissipate effect an expert will have captures
• Difficult to calibrate as inputs increase
• Limited representation of reliability effect
14
KABOM Basics
Origins
• Related to ABC models - used in manufacturing and
SCM
• Similar to the approach used by Christenson and Komar
(1998) to model/ analyze reusable rocket engine
operability
• Primarily for online functions (landing, turnaround,..)
• Model is a component of total spaceport analysis model
which should capture the other spaceport modules (not
in flow).
– This is a subset of an LCC model that includes development,
manufacturing, and operations
15
KABOM Basics
The RLV design
• The model characterizes a RLV
architecture/concept by I design variables
– I represents a particular option of the vehicle, for
example ceramic times, ultra high density
ceramics, SOFI.
– The binary variable di is used to represent the
inclusion of a design option; di = 1 if the design
option is included in the design and di = 0 if not.
16
KABOM Basics
The RLV design
• This model characterizes a RLV
architecture/concept by J vehicle
characteristics/ operational drivers.
– The vehicle characteristics J represents measures
that will drive operational cost or time, for
example the number of fuel cells or the area
covered by a type of thermal protection.
– The variable qj is used to represent the quantify
of an operational driver, qj > 0 if that
operational driver exists in the design and qj = 0
if not.
17
KABOM Basics
The Activities
• There are A spaceport activities.
– Activities relate to one or more design variables.
– The binary variable sa represents the inclusion of that
activity in the activity set for that design; sa = 1 if that
activity is part of the activity set and sa = 0 if it is not.
– The determination of the activity set is determined by
knowledge based equations. I.E.:
s3 =
s7 =
1 , if d1 + d12 = 2
0, otherwise
1 , if d11 = 0 and d123 = 1 or if q56 > 100
0, otherwise
18
KABOM Basics
Activity Characterization
• Three characteristics for each activity: activity
time, activity cost, and need percentage.
– The process time for an activity a; pa, is determined
by a knowledge based equation.
• p1 = UNIF (35, 100) x q13 hours
• p5 = EXPO (3 x q38 ) minutes
• p42 = 50 x q38 minutes
– The cost per activity a; ca, will be characterized in a
similar fashion.
• c1 = p1 x $14,000
• c81 = $10,000 + $120 x q39
• c22 = $75,000
19
KABOM Basics
Activity Characterization
• Continued:
– The need percentage for an activity a; na, is
determined by a knowledge based equation.
• n19
• n7
=
=
10% , if e45 = 1
30% , if e46 = 1
100%, otherwise
50% , if q92 < 2,000
100%, otherwise
– From these values, we can determine the expected
average time for an activity, E’(pa):
E’(pa) = na x E(pa)
20
KABOM Basics
Process Modeling
• Spaceport process model
– All A activities are integrated into a spaceport
process model.
– The process model captures precedence constraints
and possible alternative routes.
LAUNCH
TURNAROUND
TRAFFIC CONTROL
TERMINAL
LANDING
ASSEMBLY/
INTEGRATION
EXPENDABLE
ELEMENTS
21
KABOM Basics
Resources
• The spaceport has R resources
– Each resource r has a set r of assigned activities.
– Each resource r has a per unit of capacity fixed
operational cost, fcr and one time acquisition cost, acr.
– The capacity for a resource r, xr, is estimated by:
xr. = Round up(F x S for all a  r [E’(pa)] / T)
F = Round up(D/VC)
where
T = Time of spaceport operation
D = Annual demand (lbs.)
F = Number of flights per year
VC = Vehicle per flight capacity
22
KABOM Basics
Fleet Size
• The system requires a fleet of Vn vehicles to
satisfy annual demand
– The process network and average expected activity
times are used to determine the set of activities in the
critical path .
Vct = S for all a   [E’(pa)]
Vfr = T / (Vct + Vot )
Vn = Roundup (F / Vfr)
where
Vct = Vehicle ground cycle time Vot = Vehicle orbit time
23
KABOM Basics
Architecture
User
Activity
Generator
Activity Library
User Interface
Critical Path/ Resource
Capacity Generator
(Process Model)
Report Generator
Process Model/Simulation
Cost Generator
Improvement Agent
24
KABOM Basics
Simulation Model
• Why the use of simulation:
– Better representation of a dynamic environment.
– Estimate bottlenecks, resource utilization, queues, ...,
costs (VS Team objective 1).
– Provide designers a graphical (animation)
representation of their system at work.. (Team
objective 2)
– Allows the evaluation of scenarios.
• For example, a version of the model could be developed
where two types of vehicles can be modeled (I.e. Shuttle
and Venture Star).
25
KABOM Basics
Improvement Agent and Cost
Calculations
• Improvement Agent
– Heuristic to improve total performance.
• The heuristics will recommend changes to resource capacity
and/or fleet size parameters. Several iterations are conducted
(simulation repeated) until cost improvements are not obtained.
• Cost calculations
– Activity costs tracked during the simulation run.
– Total costs include activity costs and resource related
costs
– Vehicle acquisition costs are included as an input
from the designers.
26
Outline for this section
• Introduction
• Previous work
• KABOM
• Project Extensions
• Project Status
27
Project Extensions
• Approach used to develop design analysis tools
for manufactured products (an advanced ABC
analysis)
– Help product designers estimate costs/processes
– Evaluate what if scenarios in a design (mfg processes)
– A “real time” version of the model could estimate the
effect of a new product on current system load.
•
•
•
•
Order for “customized product” arrives
Tool determines activities, costs, ..
Order is added to current production schedule
Decision on taking the order or how to schedule it
28
Outline for this section
• Introduction
• Previous work
• KABOM
• Project Extensions
• Project Status
29
Project Status
• A prototype was developed last summer
while at KSC
• Student project on a web based version of
the AATe
• Grant proposal - excellent evaluations,
waiting for funding.
30
PRESENTATION OUTLINE
• Describe an “interesting” research
project
• Present an overview of current
research and teaching
interests/projects
• Discuss my vision for the future
31
Overview Of Research/ Teaching
Interests And Projects
• Research
–
–
–
–
Production Planning
Supply Chain Management
IS/OM/Simulation Interaction
Space operations
• Teaching
– Games
– Excel applications
– Advanced POM courses/ APICS/ ERP (Future)
32
Production Planning Research
• Cellular manufacturing systems
– Development of tools and models to plan/schedule on
systems where production resources are organized as cells and
products into common families.
– Work with Jeet Gupta from Ball State University
– Paper in progress
• Parallel Machine Scheduling with Multiple Criteria
– Development of heuristics for difficult multi-criteria problems
in the parallel machine setting.
– Work with Jeet Gupta and Kazou Nakatani (FGCU)
– Two papers accepted for publication, several in progress.
33
Supply Chain Management
Research
• Supplier Decision Making
– Evaluation of the role transportation plays on supplier
decision making.
– Work with John Tyworth from Penn State University
– One paper accepted for publication
• Supply Chain Simulation
– Development of simulation models for supply chain
environments in order to evaluate transportation and
scheduling priorities..
– Work with John Tyworth
34
Interaction of IS, OM, and
simulation
• Supply Chain Management
– Development of architecture to support “real time” DM..
– Utilizes simulation to investigate “what if ” scenarios.
– Work with J. Tyworth and K. Nakatani.
• Project Management
– Development of architecture to support Web based project
management.
– Utilizes simulation to evaluate the CP and effect of “what if ”
scenarios.
– Prototype developed and tested at NASA.
– Work with K. Nakatani.
35
OM Games/Exercises
• Development/application of class games to
enhance student learning
– Beer game from Jacobs web page
– In-class exercises after “lecture”.
• QFD - development of a QFD diagram for a business class
• SPC - process simulation
– JIT game with Lego/remote controlled cars
(Rokenbok)
36
Excel Applications
• Use of Excel for operations analysis
–
–
–
–
Data analysis/ “real time” behavior graphs
Queue models
Forecasting
Capacity Analysis
• Use of Excel for quantitative methods
course
– Math Programming
– VB front end
– “Real world” application development
37
PRESENTATION OUTLINE
• Describe an “interesting” research
project
• Present an overview of current research
and teaching interests/projects
• Discuss my vision for the future
38
My vision of the future
research
• Continue research on all four areas
– SS: applications of KABOM to manufacturing, IS/Simulation,
Production Planning, SCM
– Publication in leading journals,
– Long term - editor of leading journal
• Develop relationships with manufacturers in El Paso
and Juarez.
• Manufacturing-Logistics Center? - outreach program.
– Foster knowledge creation in the ML field - faculty and student
projects, grants, ....
– Foster business2business partnerships/creation of new businesses
– Continuing education programs?
39
My vision of the future
teaching
• Teaching/POM
– Continue development of teaching games
• Program/curricula development
– Graduate program in Manufacturing Logistics?
– Integration of APICS certification into some
undergraduate and graduate courses?
– Revision of POM undergraduate program?
– ERP integration to the POM program?
• Link undergraduate POM students to faculty
research projects
40
•Thanks for your
time
•Questions?
41
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