ColPMan: A Serious Game for Practicing Collaborative Production Management

1 © Hajime Mizuyama 1

ColPMan: A Serious Game for Practicing

Collaborative Production Management

Hajime Mizuyama, Tomomi Nonaka,

Yuko Yoshikawa, and Kentaro Miki

Aoyama Gakuin University

[email protected]

ISAGA 2015 @ Kyoto 18/July/2015


• 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


• 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


• 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


• Research background and objective

• Game design

• Game implementation

• Application case

• Conclusions

Agenda


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


Downstream factory (DSF)


Parallel

Headquarters (HQ)


Overall topology of in-house SC

Hierarchical

Upstream factory (USF)

Serial

DSF1 player

DSF2 player

DSF3 player

USF player

HQ player


Order assignment


Make-to-stock

Make-to-order

Custo-mers

Materials inventory

Materials inventory

Orders

Products inventory

Delivery

Information

Material

Downstream factory 1 (DSF1)

Headquarters (HQ)



Overall topology of in-house SC

Five material types ×

Five product sizes


Five product sizes



Make-to-stock

Make-to-order

Custo-mers

Materials inventory

Materials inventory

Orders

Products inventory

Delivery

Information

Material


Headquarters (HQ)



How SC is operated

Order assignment


Five product sizes


Five product sizes


6 6

5 5

4 4

3 3

2 2

1 1

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


Order assignment


Make-to-stock

Make-to-order

Custo-mers

Materials inventory

Materials inventory

Products inventory

Delivery

Information

Material


Headquarters (HQ)



How SC is operated

Orders


Five product sizes


Five product sizes


This term Next term Term after the next

DSF1

DSF2

DSF3

Decisions made by HQ player

List of orders List of orders


Order assignment


Make-to-stock

Make-to-order

Custo-mers

Materials inventory

Materials inventory

Orders

Products inventory

Delivery

Information

Material


Headquarters (HQ)



How SC is operated


Five product sizes


Five product sizes


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


Order assignment


Make-to-stock

Make-to-order

Custo-mers

Materials inventory

Materials inventory

Orders

Products inventory

Delivery

Information

Material


Headquarters (HQ)



How SC is operated


Five product sizes


Five product sizes


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


Discrete event simulation representing SC operations according to given plans under uncertainties

Game flow

Table discussion Table discussion

DSF1 player

DSF2 player

DSF3 player

USF player

HQ player

USF

DSF3 DSF1 DSF2

HQ

Planning information Progress information


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


Terms and periods

Time

Term 1 Term 2 Term 3 ...

Period 1-5 Period 1-5 Period 1-5 ...


P mode

Time



A team of players A team of players

Simulation Simulation Simulation Simulation Simulation Simulation Simulation Simulation

Planning information

Progress information


PDCA mode

Time



A team of players A team of players


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



• Game design



• Conclusions

Agenda


• 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


A short demo A short demo

Resultant game system



• Game design



• Conclusions

Agenda


• 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


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


• 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


• 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


Number of principles learned

01

23

45

6

1st report2nd report3rd report

Overall HQ-related

USF-related

DSF-related

Facilitator players

01

23

45

6


Overall HQ-related

USF-related

DSF-related

Upstream factory players

01

23

45

6


Overall HQ-related

USF-related

DSF-related

Downstream factory players

01

23

45

6


Overall HQ-related

USF-related

DSF-related

Headquarters players


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


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


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



• Game design



• Conclusions

Agenda


• 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

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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ColPMan: A Serious Game for Practicing Collaborative Production Management