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1 © Hajime Mizuyama1
ColPMan: A Serious Game for Practicing
Collaborative Production Management
Hajime Mizuyama, Tomomi No...
2 © Hajime Mizuyama2
• A large-scale MTO company is composed of several sites,
and planning and control of their operation...
3 © Hajime Mizuyama3
• The inter-related sub-problems should be repeatedly solved
reflecting the changing environment.
• N...
4 © Hajime Mizuyama4
• Such dynamic decision-making skills are not easy to be
trained in lectures alone.
• Experiential le...
5 © Hajime Mizuyama5
• Research background and objective
• Game design
• Game implementation
• Application case
• Conclusi...
6 © Hajime Mizuyama6
Hierarchical
The relation between a site, e.g. HQ, deciding an abstract plan
and the other, e.g. a fa...
7 © Hajime Mizuyama7
Downstream
factory
(DSF)
Downstream
factory
(DSF)
Parallel
Headquarters
(HQ)
Downstream
factory
(DSF)...
8 © Hajime Mizuyama8
Order assignment
Upstream
factory
(USF)
Make-to-stock
Make-to-order
Custo-
mers
Materials
inventory
M...
9 © Hajime Mizuyama9
Upstream
factory
(USF)
Make-to-stock
Make-to-order
Custo-
mers
Materials
inventory
Materials
inventor...
10 © Hajime Mizuyama10
66
55
44
33
22
11
0
• Customer’s location
• Customer’s importance
• Material type
• Product size
• ...
11 © Hajime Mizuyama11
Order assignment
Upstream
factory
(USF)
Make-to-stock
Make-to-order
Custo-
mers
Materials
inventory...
12 © Hajime Mizuyama12
This term Next term
Term after
the next
DSF1
DSF2
DSF3
Decisions made by HQ player
List of
orders
L...
13 © Hajime Mizuyama13
Order assignment
Upstream
factory
(USF)
Make-to-stock
Make-to-order
Custo-
mers
Materials
inventory...
14 © Hajime Mizuyama14
Production schedule
• Each DSF is modeled as a single machine with sequence-
dependent setup times ...
15 © Hajime Mizuyama15
Order assignment
Upstream
factory
(USF)
Make-to-stock
Make-to-order
Custo-
mers
Materials
inventory...
16 © Hajime Mizuyama16
Production schedule
• USF is modeled as a single machine of fixed-size lot
production with sequence...
17 © Hajime Mizuyama17
Discrete event simulation representing SC operations
according to given plans under uncertainties
G...
18 © Hajime Mizuyama18
Environmental disturbances incorporated into the game
– Orders and their arrival times
– Production...
19 © Hajime Mizuyama19
Terms and periods
Time
Term 1 Term 2 Term 3 ...
Period 1-5 Period 1-5 Period 1-5 ...
20 © Hajime Mizuyama20
P mode
Time
Term 1 Term 2 Term 3 ...
Period 1-5 Period 1-5 Period 1-5 ...
A team of playersA team o...
21 © Hajime Mizuyama21
PDCA mode
Time
Term 1 Term 2 Term 3 ...
Period 1-5 Period 1-5 Period 1-5 ...
A team of playersA tea...
22 © Hajime Mizuyama22
Game score
Profit = Revenue - Costs
Revenue
∝ The number of products delivered to customers
Costs
–...
23 © Hajime Mizuyama23
• Research background and objective
• Game design
• Game implementation
• Application case
• Conclu...
24 © Hajime Mizuyama24
• The computer simulation part and its graphical interfaces with
human players are implemented with...
25 © Hajime Mizuyama25
A short demoA short demo
Resultant game system
26 © Hajime Mizuyama26
• Research background and objective
• Game design
• Game implementation
• Application case
• Conclu...
27 © Hajime Mizuyama27
• Participants are 107 junior students in the dept. of industrial
and systems engineering, Aoyama G...
28 © Hajime Mizuyama28
1st time slot (90 min.) 2nd time slot (90 min.)
1st week Introduction to ColPMan Game play #1
2nd w...
29 © Hajime Mizuyama29
• 107 students are randomly grouped into 12 teams; each is
composed of nine or eight students.
• On...
30 © Hajime Mizuyama30
• All the reports submitted by the students are read through
and individual items describing a key ...
31 © Hajime Mizuyama31
Number of principles learned
0123456
1st report
2nd report
3rd report
Overall HQ
-related
USF
-rela...
32 © Hajime Mizuyama32
Q1: Did you enjoy playing ColPMan?
Q2: Did your tactics change as you repeat playing ColPMan?
Q3: W...
33 © Hajime Mizuyama33
Yes
(Lecture)
Slightly
yes
Neutral
Slightly
no
No
(Game)
Q1 47 42 11 2 0
Q2 45 48 8 1 0
Q3 32 57 5 ...
34 © Hajime Mizuyama34
Q8: Did ColPMan facilitate communication among the team
members?
Q9: Did ColPMan deepen your unders...
35 © Hajime Mizuyama35
• Research background and objective
• Game design
• Game implementation
• Application case
• Conclu...
36 © Hajime Mizuyama36
• A serious game called ColPMan is developed as a medium for
experiential learning of dynamic decis...
37
Thank you for your kind attention!
Questions and comments are welcome.
Thank you for your kind attention!
Questions and...
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ColPMan: A Serious Game for Practicing Collaborative Production Management

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ColPMan: A Serious Game for Practicing Collaborative Production Management

  1. 1. 1 © Hajime Mizuyama1 ColPMan: A Serious Game for Practicing Collaborative Production Management Hajime Mizuyama, Tomomi Nonaka, Yuko Yoshikawa, and Kentaro Miki Aoyama Gakuin University mizuyama@ise.aoyama.ac.jp ISAGA 2015 @ Kyoto 18/July/2015
  2. 2. 2 © Hajime Mizuyama2 • A large-scale MTO company is composed of several sites, and planning and control of their operations is a huge problem. • Production and delivery operations in those sites are affected by stationary and non-stationary disturbances. • The information on the changing environment is dispersed among the sites, and it is difficult to collect all the relevant information in one place in a timely manner. • Operational planning and control in the in-house supply chain of such a company is divided into several sub-problems and handled by multiple decision makers in those sites. In-house SC of a large-scale MTO company
  3. 3. 3 © Hajime Mizuyama3 • The inter-related sub-problems should be repeatedly solved reflecting the changing environment. • None of the decision makers hold the entire picture of the environment. • It is important for the decision makers – not only to appropriately solve the respective sub-problems – but also to effectively communicate and coordinate with one another in the dynamic environment. In-house SC of a large-scale MTO company
  4. 4. 4 © Hajime Mizuyama4 • Such dynamic decision-making skills are not easy to be trained in lectures alone. • Experiential learning is potentially effective supplemental approach and serious games are a suitable medium for it. • The objective of this research is – to develop an original serious game suitable for training the dynamic organizational decision-making skills, and – to test how the developed game named ColPMan works. Research Objective
  5. 5. 5 © Hajime Mizuyama5 • Research background and objective • Game design • Game implementation • Application case • Conclusions Agenda
  6. 6. 6 © Hajime Mizuyama6 Hierarchical The relation between a site, e.g. HQ, deciding an abstract plan and the other, e.g. a factory, deciding a detailed schedule under the constraint of the abstract plan. Serial The relations between a pair of factories, where one’s output is used as the input of the other. Parallel The relations between a pair of factories, which are in charge of a same production function and are substitutable to each other. Typical relations among sites
  7. 7. 7 © Hajime Mizuyama7 Downstream factory (DSF) Downstream factory (DSF) Parallel Headquarters (HQ) Downstream factory (DSF) Overall topology of in-house SC Hierarchical Upstream factory (USF) Serial DSF1 player DSF2 player DSF3 player USF player HQ player
  8. 8. 8 © Hajime Mizuyama8 Order assignment Upstream factory (USF) Make-to-stock Make-to-order Custo- mers Materials inventory Materials inventory Orders Products inventory Delivery Information Material Downstream factory 1 (DSF1) Headquarters (HQ) Downstream factory 2 (DSF2) Downstream factory 3 (DSF3) Overall topology of in-house SC Five material types × Five product sizes Five material types × Five product sizes
  9. 9. 9 © Hajime Mizuyama9 Upstream factory (USF) Make-to-stock Make-to-order Custo- mers Materials inventory Materials inventory Orders Products inventory Delivery Information Material Downstream factory 1 (DSF1) Headquarters (HQ) Downstream factory 2 (DSF2) Downstream factory 3 (DSF3) How SC is operated Order assignment Five material types × Five product sizes Five material types × Five product sizes
  10. 10. 10 © Hajime Mizuyama10 66 55 44 33 22 11 0 • Customer’s location • Customer’s importance • Material type • Product size • Number of products • Remaining time to due date 0 • Customer’s location • Customer’s importance • Material type • Product size • Number of products • Remaining time to due date Order arrivals from customers Random arrival
  11. 11. 11 © Hajime Mizuyama11 Order assignment Upstream factory (USF) Make-to-stock Make-to-order Custo- mers Materials inventory Materials inventory Products inventory Delivery Information Material Downstream factory 1 (DSF1) Headquarters (HQ) Downstream factory 2 (DSF2) Downstream factory 3 (DSF3) How SC is operated Orders Five material types × Five product sizes Five material types × Five product sizes
  12. 12. 12 © Hajime Mizuyama12 This term Next term Term after the next DSF1 DSF2 DSF3 Decisions made by HQ player List of orders List of orders
  13. 13. 13 © Hajime Mizuyama13 Order assignment Upstream factory (USF) Make-to-stock Make-to-order Custo- mers Materials inventory Materials inventory Orders Products inventory Delivery Information Material Downstream factory 1 (DSF1) Headquarters (HQ) Downstream factory 2 (DSF2) Downstream factory 3 (DSF3) How SC is operated Five material types × Five product sizes Five material types × Five product sizes
  14. 14. 14 © Hajime Mizuyama14 Production schedule • Each DSF is modeled as a single machine with sequence- dependent setup times (and costs). • Which orders among those assigned to the factory are to be processed in this term, and their sequence should be determined. Materials order • The materials inventory in each DSF is controlled by the respective DSF player. • How many materials of each type are ordered should be determined. Decisions made by DSF players
  15. 15. 15 © Hajime Mizuyama15 Order assignment Upstream factory (USF) Make-to-stock Make-to-order Custo- mers Materials inventory Materials inventory Orders Products inventory Delivery Information Material Downstream factory 1 (DSF1) Headquarters (HQ) Downstream factory 2 (DSF2) Downstream factory 3 (DSF3) How SC is operated Five material types × Five product sizes Five material types × Five product sizes
  16. 16. 16 © Hajime Mizuyama16 Production schedule • USF is modeled as a single machine of fixed-size lot production with sequence-dependent setup times (and costs). • The materials inventory in USF is controlled by the USF player. • How many lots of each type are to be produced in this term, and their sequence should be determined. Decisions made by USF player
  17. 17. 17 © Hajime Mizuyama17 Discrete event simulation representing SC operations according to given plans under uncertainties Game flow Table discussionTable discussion DSF1 player DSF2 player DSF3 player USF player HQ player USF DSF3DSF1 DSF2 HQ Planning information Progress information
  18. 18. 18 © Hajime Mizuyama18 Environmental disturbances incorporated into the game – Orders and their arrival times – Production lead-time in DSF – Defectives and machine failures in DSF – Material delivery lead-time – Production lead-time in USF – Defectives and machine failures in USF Uncertainties in simulation
  19. 19. 19 © Hajime Mizuyama19 Terms and periods Time Term 1 Term 2 Term 3 ... Period 1-5 Period 1-5 Period 1-5 ...
  20. 20. 20 © Hajime Mizuyama20 P mode Time Term 1 Term 2 Term 3 ... Period 1-5 Period 1-5 Period 1-5 ... A team of playersA team of players SimulationSimulation SimulationSimulation SimulationSimulation SimulationSimulation Planning information Progress information
  21. 21. 21 © Hajime Mizuyama21 PDCA mode Time Term 1 Term 2 Term 3 ... Period 1-5 Period 1-5 Period 1-5 ... A team of playersA team of players
  22. 22. 22 © Hajime Mizuyama22 Game score Profit = Revenue - Costs Revenue ∝ The number of products delivered to customers Costs – Materials inventory cost at both USF and DSF – Setup cost in both USF and DSF – Material delivery cost – Product inventory cost – Product delivery cost – Late delivery penalty cost Game score
  23. 23. 23 © Hajime Mizuyama23 • Research background and objective • Game design • Game implementation • Application case • Conclusions Agenda
  24. 24. 24 © Hajime Mizuyama24 • The computer simulation part and its graphical interfaces with human players are implemented with Processing, a Java- based programming language suitable for interactive graphics. • A screen is provided to each site and basic information on the progress directly observable from the site is visually displayed on it. • More detailed progress information is given in CSV files. • The simulator incorporates the decisions made by the players also from CSV files. Implementation outline
  25. 25. 25 © Hajime Mizuyama25 A short demoA short demo Resultant game system
  26. 26. 26 © Hajime Mizuyama26 • Research background and objective • Game design • Game implementation • Application case • Conclusions Agenda
  27. 27. 27 © Hajime Mizuyama27 • Participants are 107 junior students in the dept. of industrial and systems engineering, Aoyama Gakuin University, Japan. • The class is open every Thursday and is composed of two 90- minute time slots with 15-minute break in between. • The whole class lasts 15 weeks, but only five weeks are instructed by the authors. • The objective of the class is (1) to understand how optimization techniques work in practical situation, and (2) to brush up programming skills by related exercises. • Thus, two weeks are devoted to programming exercises, and only three time slots are given to playing ColPMan. Class outline
  28. 28. 28 © Hajime Mizuyama28 1st time slot (90 min.) 2nd time slot (90 min.) 1st week Introduction to ColPMan Game play #1 2nd week Lecture on production management techniques Game play #2 3rd week Introduction to programming exercises Programming #1 4th week Programming #2 Programming #3 5th week Game play #3 Presentation Class schedule
  29. 29. 29 © Hajime Mizuyama29 • 107 students are randomly grouped into 12 teams; each is composed of nine or eight students. • One of them is assigned to a role called facilitator, who operates the simulation software. • The others are assigned to one of the five sites. This means that some sites are controlled by a sub-team of two players. • The role assignments are determined by the students themselves. • After each game play session, all the students are requested to hand in a report discussing how to get high score. Team formation and role assignment
  30. 30. 30 © Hajime Mizuyama30 • All the reports submitted by the students are read through and individual items describing a key point are carefully picked up. • The obtained items are classified into different principles. • They are also categorized into overall, HQ-related, USF- related, and DSF-related principles. • It results in nine overall, seven HQ-related, eight USF- related, 17 DSF-related principles. Indirect evaluation of learning effects
  31. 31. 31 © Hajime Mizuyama31 Number of principles learned 0123456 1st report 2nd report 3rd report Overall HQ -related USF -related DSF -related Facilitator players 0123456 1st report 2nd report 3rd report Overall HQ -related USF -related DSF -related Upstream factory players 0123456 1st report 2nd report 3rd report Overall HQ -related USF -related DSF -related Downstream factory players 0123456 1st report 2nd report 3rd report Overall HQ -related USF -related DSF -related Headquarters players
  32. 32. 32 © Hajime Mizuyama32 Q1: Did you enjoy playing ColPMan? Q2: Did your tactics change as you repeat playing ColPMan? Q3: Was it possible to apply your strategy prepared beforehand? Q4: Was your motivation encouraged by the game score? Q5: If you have a chance, do you want to play ColPMan again? Q6: Was it difficult for you to play ColPMan? Q7: Is the ColPMan software easy to operate? Subjective evaluation questions #1
  33. 33. 33 © Hajime Mizuyama33 Yes (Lecture) Slightly yes Neutral Slightly no No (Game) Q1 47 42 11 2 0 Q2 45 48 8 1 0 Q3 32 57 5 6 2 Q4 55 33 10 4 0 Q5 36 40 16 7 3 Q6 22 55 21 4 1 Q7 15 34 13 33 7 Q8 72 26 2 1 1 Q9 35 58 6 2 1 Q10 7 10 10 27 48 Q11 54 37 9 1 1 Subjective evaluation results
  34. 34. 34 © Hajime Mizuyama34 Q8: Did ColPMan facilitate communication among the team members? Q9: Did ColPMan deepen your understanding on production management? Q10: Which do you think more helpful for deepen your understanding lectures or games like ColPMan? Q11: Do you want to use a simulation game like ColPMan for other purposes? Subjective evaluation questions #2
  35. 35. 35 © Hajime Mizuyama35 • Research background and objective • Game design • Game implementation • Application case • Conclusions Agenda
  36. 36. 36 © Hajime Mizuyama36 • A serious game called ColPMan is developed as a medium for experiential learning of dynamic decision-making skills for collaborative production management. • The developed game is actually tested as an undergraduate classroom exercise. • The learning effects provided by ColPMan game are indirectly observed, and the game obtained positive response from the students. • The future directions include simplification of the game structure so as to level the workload of different roles. Conclusions
  37. 37. 37 Thank you for your kind attention! Questions and comments are welcome. Thank you for your kind attention! Questions and comments are welcome.

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