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System dynamics study of the Japanese automotive industry closed loop supply chain

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Purpose A major challenge the car industry currently faces worldwide is how to implement an effective reverse (also called closed loop) supply chain design while manufacturing environmental friendly cars from limited available resources. The purpose of this paper is to examine relationships between reduce, reuse and disposal in the Japanese car market with base scenario analysis using the car consumption data and forecast. Design/methodology/approach The system dynamics (SD) modeling analyzes the closed loop supply chain design for the Japanese car industry. Relationships between reduce, reuse, recycle and disposal are explored with base scenario analysis using the car consumption data and forecast. The SD model is subjected to extreme conditions test for structural validity. Dynamic analysis of different market scenarios for the Japanese car industry's reverse supply chain is conducted. Findings Japanese ELV regulation will trigger the growth of used car export rate to emerging countries. Without additional tax on used car export, manufacturers in Japan tend to export used cars. Imposing tax on used car export will place some control on such export and improve economic opportunities for remanufacturers, recyclers, government, manufacturers and consumers in Japan. Practical implications The used car export option in Japanese reverse supply chain may cause the emerging countries (importing used cars) not able to sustain this activity. The Japanese government and manufacturers should take initiative to create or support the reverse logistics facilities in export countries. Issues pertaining to how product components can be recycled, reused, or remanufactured should be factored in the product design phase to reduce the cost of products and raw materials. Originality/value The dynamic model of the Japanese car market provides an experimental simulation tool, which can be used to forecast the relationship between reduce, reuse, recycle, disposal and how various logistics elements will be impacted by government regulations on a long‐term basis.
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System dynamics study of the
Japanese automotive industry
closed loop supply chain
Sameer Kumar and Teruyuki Yamaoka
College of Business, University of St Thomas, Minneapolis, Minnesota, USA
Abstract
Purpose – A major challenge the car industry currently faces worldwide is how to implement an
effective reverse (also called closed loop) supply chain design while manufacturing environmental
friendly cars from limited available resources. The purpose of this paper is to examine relationships
between reduce, reuse and disposal in the Japanese car market with base scenario analysis using the
car consumption data and forecast.
Design/methodology/approach – The system dynamics (SD) modeling analyzes the closed loop
supply chain design for the Japanese car industry. Relationships between reduce, reuse, recycle and
disposal are explored with base scenario analysis using the car consumption data and forecast. The SD
model is subjected to extreme conditions test for structural validity. Dynamic analysis of different
market scenarios for the Japanese car industry’s reverse supply chain is conducted.
Findings – Japanese ELV regulation will trigger the growth of used car export rate to emerging
countries. Without additional tax on used car export, manufacturers in Japan tend to export used cars.
Imposing tax on used car export will place some control on such export and improve economic
opportunities for remanufacturers, recyclers, government, manufacturers and consumers in Japan.
Practical implications – The used car export option in Japanese reverse supply chain may cause
the emerging countries (importing used cars) not able to sustain this activity. The Japanese
government and manufacturers should take initiative to create or support the reverse logistics
facilities in export countries. Issues pertaining to how product components can be recycled, reused, or
remanufactured should be factored in the product design phase to reduce the cost of products and raw
materials.
Originality/value The dynamic model of the Japanese car market provides an experimental
simulation tool, which can be used to forecast the relationship between reduce, reuse, recycle, disposal
and how various logistics elements will be impacted by government regulations on a long-term basis.
Keywords Supply chain management, Recycling, Cars, Automotive industry, Japan
Paper type Research paper
Introduction
Modern life has been greatly influenced by cars. The Organization for Economic
Cooperation and Development (OECD, 2004), estimates that the number of motor
vehicles will increase by 74 percent all over the world from 1997 to 2020. Currently
about 80 percent of cars originate from companies in the USA, Europe, and Japan. The
consumer trends in these major markets are more and more concerned about green
environments. The European Union, for example, requires manufacturers to recycle
auto bodies built since 2002. This is called the end of life vehicle program (ELV)
(Kumar and Fullenkamp, 2004). Such government regulation has a significant impact
on the reverse supply chain in related industries. One major challenge currently faced
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1741-038X.htm
Japanese
automotive
industry
115
Received April 2005
Revised November 2005
Accepted January 2006
Journal of Manufacturing Technology
Management
Vol. 18 No. 2, 2007
pp. 115-138
qEmerald Group Publishing Limited
1741-038X
DOI 10.1108/17410380710722854
by the car industry is how to implement a viable design for a closed loop supply chain
that allows manufacturing of environmentally oriented cars from limited resources.
Early in the twentieth century Henry Ford introduced his Fordism theory. This
theory has to do with the perfection of the assembly line method of manufacturing.
Fordism, therefore, worked towards the formulation of a mass-consumption and
mass-scrap society. This phenomenon has triggered consumers’ concerns for the
environment and has required greater responsibility on the part of the producers. To
respond to this customer expectation, the study of reverse logistics began in the early
nineties principally with the Council of Logistics Management and has been recognized
by both business and society (Stock, 1992). Since, then, a lot of research on this topic
has been done and reverse logistics is still a growing academic field. Most issues in
reverse logistics are also found in the forward logistics literature (Krikke and Ie Balanc,
2004). Thus, it is important to consider not only forward logistics system but also
reverse logistics as well. This concept is termed a closed loop supply chain and a
number of studies have been conducted in Europe on this topic (Seitz and Peattie, 2004;
Rand, 2005; Georgiadis and Vlachos, 2004).
An ideal closed loop supply chain disposal to the landfill should not to be an option
and all materials used in products reaching end of life should be reused in the forward
supply chain. Realizing the significance of a closed loop supply chain, many scholars
have continued to write on recovery options from a management perspective (Thiery,
1995). Furthermore, many organizations or governments are using the three R’s of
reduce, reuse, and recycle to encourage end-customers to recycle or reuse the products
and reduce disposal to landfills. Various macro economic elements of a closed loop
supply chain include: direct reuse, repair, refurbishing, remanufacturing, and
cannibalization. These elements are all defined as “reuse”.
There are many business entities and organizations involved in this loop, such as
the government and export dealers. All stakeholders should be actively included in this
loop. For example, after the Japanese “Home appliance recycling law” (Ueno, 2003) was
implemented, there were abandoned goods found on the road, or they were exported or
discarded outside of Japan because the law ignored end customers’ financial burden
and the capabilities of reverse remanufacturers and recyclers (Yamayoshi, 2004).
Rest of the paper is organized as follows. It begins with a brief overview of system
dynamics (SD) modeling methodology. Next, an overview of Japanese car industry is
presented that includes: macro economic view of car industry; state of car recycling in
Japan and Japanese car recycle law. Qualitative and quantitative analyses (that are part
of SD modeling methodology) enable process understanding of Japanese cars closed
loop supply chain. Model testing for extreme conditions support structural validity of
SD model developed for the reverse supply chain. Car consumption forecast for the
period 2004-2024 for Japan is determined that serve as the primary input to the SD
model. The study also explores how Japan is engaged in disposing cars that reach end
of life phase and export of used cars to emerging countries (such as, Poland, Czech
Republic) including potential threats to car manufacturers in these economies. Base
scenario analysis for Japanese reverse supply chain using SD model is carried out.
Dynamic analysis that includes different market scenarios for Japanese car reverse
supply chain is also conducted. Finally, based on what we have learnt from the SD
modeling approach, conclusions and recommendations are made to highlight potential
opportunities for improvements.
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System dynamics approach
The behavior of the system is analyzed through a dynamic simulation model based on
the principles of SD methodology. The SD methodology was introduced in the early
1960s by Jay Forrester as a simulation methodology for analysis and a long-term
decision making tool to solve complex industrial management problems (Sterman, 2000).
The Logistics Systems Dynamic Group at Cardiff University has developed a
methodology for a structured approach that can be used in the dynamic analysis of
supply-chains and their re-engineering process (Naim and Towill, 1994). This concept
was adapted by Tibben-Lembke (1998). It is called Cardiff methodology which is
shown in Figure 1 and discussed below.
In Cardiff methodology, there are mainly two stages of analyses. The first stage
involves qualitative analysis. In this stage, both the objective of the study and the key
drivers are identified. Then, the relationships among key drivers are shown in terms of
either positive, or negative relationship. Once, the relationships have been established,
qualitative factors (behaviors) are usually included in this flow. The second stage is the
quantitative analysis. In this stage, the relationships described in the first stage are
shown in terms of algebraic equations. After that, a simulation is conducted using SD
computer software to represent the dynamic model.
There are many examples of forward supply chains modeling. A recent study by
Georgiadis and Vlachos (2004) developed a closed supply chain to show how ecological
awareness impacts product recovery. Although closed loop supply chains that
incorporate environmental concerns have already been developed, the value chain
needs to be further studied in order to analyze the relationship between recycle and
reuse and also the impact of government regulations.
It may be pointed that there is a lack of SD research in studying closed loop supply
chains from macro economic view. The model presented includes a major macro
economical view of new, discarded, re-used and recycling products and the flows in a
reverse supply chain. The consideration of major economical views in our model is an
important difference from Tibben-Lembke (1998), Georgiadis and Vlachos (2004) and
Towill and Naim (2004) approaches of studying manufacturing/remanufacturing
system using control theory/simulation (Figure 1). All relationships in the model are
analyzed based on cause and effect analyses and also through various mathematical
formulae. The dynamic model provides an experimental simulation tool, which can be
used to forecast the relationship between re-use, recycle and how various logistics
elements will be impacted by government regulations on a long-term basis.
Japan’s car industry
In order to have a deeper understanding of the car recycling law in Japan, it is essential
to review the background. In this section, first a macro economic analysis is conducted
to identify the issues and problems. Next, the research explores how the car parts are
recycled to have greater understanding of the automotive reverse supply chain.
Finally, the state of car recycling in Japan and the car recycle law are reviewed.
Macro economic analysis
According to “The Society of Motor Manufacturers and Traders Limited” (SMMT,
2003) in 2002, the total number of motor vehicles in use worldwide was 814.89 million
units. The USA is listed with 225.45 million motor vehicles in use, accounting for
Japanese
automotive
industry
117
28 percent of the world total, followed by Japan with 73.99 million, Germany with
48.22 million, Italy with 37.68 million, and France with 35.14 million motor vehicles in
use. In recent years, many emerging countries have started importing cars from
developed nations. According to Peugeot-Citron (2003) Company’s Report, the Chinese
Figure 1.
Cardiff methodology for
supply chain design
Qualitative Analysis
Quantitative Analysis
Sensitivity
Analysis
Dynamic
Analysis
Verification/
validation
Statistical
techniques
Objectives
Control theory
techniques
Flow diagram
construction
Systems
input-output
analysis
Reverse Logistics
System for
Remanufacturing
Conceptual
modal
(Influence diagram)
Computer
simulation
techniques
Source: Naim and Towill (1994) and Tibben- Lembke (1998)
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car market is expanding significantly. Their statistics show 2.3 million units were sold
in China in 2002 which represents a 68.5 percent annual growth rate from the previous
year. There is clearly a greater potential market in China and it is projected 3.2 percent
of the population will own car vehicles by 2010 (Energy Data and Modeling Center,
2004). Furthermore, according to Ahmed (2004), the number of adolescents, aged 10-19,
is at an all-time high of 1.2 billion. So, it can be estimated that more cars will have to be
produced in the near future to respond to this demand.
At present, every two people own a car in the USA. If the people in the rest of the
world were to attain the same level of ownership as in America, an additional 2.5 billion
cars would be needed. In other words, manufacturers would have to produce five times
as many as the existing number of cars produced in 2003.
Car recyclable part categories
The problem of how to recycle cars cannot be solved without knowing various parts of
reverse supply chain and how they are linked. In this section, the Japanese car
recycling system is examined to serve as an example. Related problems and issues are
also investigated.
To make a passenger car, about 3,000 modular parts are needed. Figure 2 shows a
typical car with various major modules labeled in figure. These modular parts are
grouped into 20 categories from a recycling perspective. These categories and
associated recyclable material are listed in Table I. These are the items that are
recycled by Toyota Company.
The state of car recycling in Japan
Cars are recycled differently in each country because of different government regulations,
social structures, political systems and also the level of economic development. In this
Figure 2.
Twenty recyclable
categories of
Toyota car parts
12
3
4
7
17
5
8
11
10
6
9
19
12
20
18
13 14 15 16
Japanese
automotive
industry
119
section, the Japanese car market will be used as an example of existing reverse supply
chain (Figure 3). Car recycling in Japan is a four-step process:
(1) The oil, engine, tires, and seats are removed and recycled.
(2) The remaining auto body is compressed and shipped to appropriate facilities.
(3) In the facilities, the compressed body is shredded and divided into steel,
non-steel and other material.
(4) The other material, called automobile shredder residue (ASR) is dumped into
the sea to create artificial islands.
Car parts Recycled parts categories
1. Window Tile
2. Seats Soundproofing for cars
3. Body Car parts or steel products
4. Trunk Car parts or steel products
5. Wires (copper) Copper products
6. Hood Car parts or steel products
7. Bumper Bumper or interior parts for cars
8. Radiator Aluminum
9. Coolant Combustion aid oil for boiler
10 Engine oil Combustion aid oil for boiler
11 Engine Engine or aluminum
12 Batteries Batteries
13 Transmission Car parts or steel products
14 Gear oil Combustion aid oil for boiler
15 Converter Converter
16 Door Car parts or steel products
17 Tire Cement
18 Suspension Steel products or aluminum products
19 Bumper Bumper, interior parts for cars, or tool kit
20 Wheel Steel products or aluminum products
Table I.
Relationship between
Toyota’s car parts and
recycled parts categories
Figure 3.
Flow diagram of current
recycling of car vehicles in
Japan
4 million
cars per
year
5 million
cars per
year
1 million
cars per
year
Disassemblers
Used Car Export
ASR(17–19%)
Recycle as steel,
non-steel material
(4060%)
Oil, engine, tire, seat,
etc. are removed
(2045%)
Dealer
Used Car Shop
Repair Shops
End User
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Currently by car weight, 81-83 percent of cars are recycled. Therefore, the key to
success in the future is how the car industry in Japan will recycle the other 19 percent of
ASR. Japan currently produces 0.7 million tons of ASR per year and half of it is
dumped into the sea to create artificial islands.
Japanese Car Recycle Law
Availability of fewer landfill sites for waste disposal and the increasing cost of raw
materials have forced both the government and companies to implement a new
recycling system. In Japan, a Car Recycle Law was implemented in the beginning
of 2005. This regulation stipulates that manufacturers are required to
make arrangements for recycle and reuse of three categories of used car items the
chlorofluorocarbon (CFC), air bags and ASR. The objective of these laws is to decrease
the recycling of the shredder dust in Japan. Japanese government monitors any
recycling or reuse process. The information is exchanged by an electronic database of
consumers, government, and car companies. The goal of the new Japanese recycling
law is to increase the recycling rate by over 95 percent by 2015. A recycle fee is
collected when the consumer purchases a car. This fee is different for each car brand.
When consumers sell the cars to dealers, used car shops, or repair shops; the fees paid
with the registration of new or used car are reimbursed to them.
Qualitative analysis of Japanese car market
In order to measure the impact of the Japanese car recycling law, the material flow
diagram of the existing car industry in Japan is analyzed (Figure 4). Both forward and
Figure 4.
Stock flow diagram of the
closed loop supply chain
for Japanese car market
22
20
Demand
for Raw
Material
Case 2: Raw Material
Inventory not Sufficient
to meet Production
Requirement
Case 1: Reuse Material
Inventory Sufficient to
meet Production
Requirement
Case B: Raw
Material Inventory
not Sufficient to
meet Production
Requiment
Check for
Sufficient
Reuse Material
Inventory
Demand
for Raw
Material in
Case 2
Demand for
Import of
Raw
Material
Recycled
Raw
Material
Recycle rate
Dispose
rate
Number of
Cars
Disposed
Number of Cars
Recycled
Collected Used
cars
Average Consumption
[11 year]
Used car Export
Number
of Cars
Reused
Test and
Disassembly Cars
Number of
Cars
Recycled
Numbers of
Cars
Recycled
23
24 26
28
15
13
12
8
10
25
18
19
17
16
21
11
34
67
9
5
2
1
14
27
29
Raw Material
and Reuse
Material Needed
for Production
Use of Reuse
Material in case2
Remanufacturers
Inventory
Car
Production Car Stock
Car
Distributuion
and Sales
Car
Consumption
Demand
Actual
Consumption
Data 1993-2003
and Forecast for
2004-2024 [Car]
Number of
Cars
Reused
Used car
export rate
Reuse
Rate
Number of Cars
Reused
Raw Material
Inventory
Deficit Raw Material
Needed for
Production
Deficit Reuse
Material Needed
for Production
Case A: Raw
Material Inventory
Sufficient to
Meet Production
Requirement
Check for
Sufficient Raw
Material
Inventory
Use Raw
Material
Inventory in
case B
+
+
+
+
+
+
+
+
+
+
+
Japanese
automotive
industry
121
reverse logistics are affected by consumption. Commodity flow in the forward supply
chain is driven by customers whereas material flow in the reverse supply chain is also
driven by customers who are pushing used products back to manufacturers, recyclers
and remanufacturers (Towill and Naim, 2004). Manufacturers in the reuse process try
to consume “reuse material” first, because it is already available in their inventories. If
new raw material for production is needed, then car manufacturers have to purchase it
from domestic or foreign suppliers. The current Japanese car industry closed loop
supply chain is not a usual closed supply chain because it also includes the export of
used cars. The import of new raw material mainly comes into manufacturers’
inventories. Cars are exported as new, used, or scrapped. Disposal of ASR is typically
done by dumping it into the sea to create artificial islands. A Japanese car’s useful life
is estimated to be an average of 11 years which is shorter than in the USA because of
different criteria based on the government motor vehicle inspection style and culture
(Anonymous, 2004).
In the schematic stock flow diagram (Figure 4), six pictorial blocks are used to
represent flows, delays, converters, stocks, jumping link, and link catcher. Flow is a
circle block which stands for activities affected by various variables in the system.
Converters (or auxiliary variables) are shown as diamond blocks to represent rates
which are not affected by various activities in the system. Delay blocks (shown
as curved rectangles appended with an arrow) introduce pipeline time delay. Stock
blocks (shown as cylinders) shows accumulation of inventory. The jumping link
(shown as a pentagon heading up) forwards the flow data to jumping catcher (a
pentagon heading down).
Various flows, delays, stocks and converters annotated with a numbering system in
Figure 4, are listed in Table II.
Quantitative analysis of Japanese car market
In this section, various relationships between major business entities are shown by
algebraic equations used in SD simulation with computer software titled “The
Simulation Tool and Knowledge Network (SimTakn) (Ikeda, 2003) and Excel”. The
selection of SimTakn for this study was simply based on the fact that it is an
inexpensive tool available for SD analysis.
Mathematical formulation
We illustrate below the algebraic equations used to calculate used car export,
re-manufacturers’ inventories and raw material inventories. The units of the variables
used in the SD model equations are in terms of cars except rate variables are in
percents.
The algebraic equation (1) below for used car export (correspond to flow activity 9
in Figure 4) in the SD model is given by:
Used car export ¼Collected used cars £Used car export rate
þðTest and disassemble cars 2Number of cars reused
2Number of cars recycled 2Number of cars reused
2Number of cars disposedÞ
ð1Þ
where
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Collected used cars ¼DELAYðcar consumption demand;
average delay time in Japan ð11 yearsÞ;0Þð2Þ
Test and disassemble cars ¼Collected used cars
£ð12Used car export rateÞð3Þ
Number of cars reused ¼Test and disassemble cars £Reuse rate ð4Þ
Number of cars recycled ¼Test and disassemble cars £Recycle rate ð5Þ
Number of cars disposed ¼Test and disassemble cars £Dispose rate ð6Þ
The flow activities described by equations (2)-(6) above correspond to annotated labels
7, 8, 10, 13, and 12 in the stock flow diagram shown in Figure 4. Noting the fact that
cars in Japan retire in 11 years; the delay variables “Average Consumption” in stock
and flow diagrams of Figures 3 and 4 are treated as pipeline delay. The assumption in
our SD model is that the outflow of the pipeline delay is zero until, at a time equal to the
average delay, the entire pulse input flows out of the delay chain into the “Collected
Used Cars” for that year.
As mentioned before, manufacturers try to use the “reuse material” first. In this
section, two cases delineate the use of “reuse material” in the SD model. The first case,
case 1 is based on the adequate availability of “reuse material” in the inventory to
Forward logistics Forward logistics
1. Actual consumption data (1993-2003)
and forecast (2004-2024)
16. Raw material and reused material needed for
production
2. Car consumption demand 17. Case 1: reuse material inventory sufficient to
meet product requirement
3. Car production
18. Deficit reuse material needed for production
4. Car stock
19. Check for sufficient reuse material inventory
5. Car distribution and sales
20. Case 2: reuse material inventory not sufficient
to meet production requirement
Reverse logistics
21. Use of reuse material in case 2
6. Average consumption
22. Demand for raw material
7. Collected used cars
23. Demand for raw material in case 2
8. Test and disassembly cars
24. Case A: raw material inventory sufficient to
meet production requirement
9. Used car export
25. Deficit raw material needed for production
10. Number of cars reused
26. Check for sufficient raw material inventory
11. Remanufacturers’ inventory
27. Case B: raw material inventory not sufficient
to meet production requirement
12. Number of cars disposed
28. Use of reuse material in case B
13. Number of cars recycled
29. Demand for import of raw material
14. Recycled raw material
15. Raw material inventory
Note: Numbered in the sequence of occurrence in Figure 4
Table II.
List of flows, delays,
stocks and converters
Japanese
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satisfy the raw material required to support demand requirement for cars. The second
case, case 2 is based on lack of sufficient reuse material availability in inventory to
meet demand requirements for cars.
The algebraic equation (7) for the remanufacturers’ inventory over time tis given by:
Remanufacturers’ inventoryðtÞðcorrespond to flow activity 11Þ
¼Zt
0
½Number of car reused 2{ðCase 1 :reuse material inventory
sufficient to meet production requirementÞor ðCase 2 :reuse
material inventory not sufficient to meet production requirementÞ}dt
þRemanufactures’ inventory ð0Þ
ð7Þ
Beside reflecting the remanufacturers’ behaviors in the SD model by case 1 and case 2,
the two other cases, case A and case B, should also be considered for the use of raw
material. The first case, case A is based on the adequate availability of domestic raw
material inventory to satisfy the total raw material requirement to support demand for
cars. The second case, case B is based on lack of domestic raw material inventory
availability to meet demand requirements for cars. Therefore, in case B, manufacturers’
import raw material to satisfy the consumers’ car demand.
The algebraic equation for raw material inventory (8) over time tis given by:
Raw material inventoryðtÞðcorrespond to flow activity 15Þ
¼Zt
0
½Recycled raw material 2{ðCase A :raw material inventory
sufficient to meet production requirementÞor
ðCase B :raw material inventory not sufficient to meet
production requirementÞ}dtþRaw material inventory ð0Þ
ð8Þ
The other equations (9) through (27) used in the simulation model, developed from the
stock flow diagram for the Japanese closed loop supply chain (Figures 4) are described
below. Raw material inventory (0) and remanufacturers’ inventory (0) are both set to 0
in this study.
Raw material and reuse material needed for production
ðcorrespond to flow activity 16Þ¼Car production ðin car unitsÞð9Þ
Car consumption demand ðcorrespond to flow activity 2Þ
¼Actual consumption data 1993 22003 and forecast for 2004 22024 ð10Þ
Car production ðcorrespond to flow activity 3Þ
¼Car consumption demand ð11Þ
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Car stock ðtÞðcorrespond to stock activity 4Þ
¼Car stock ðt2dtÞþðCar production 2car distribution and salesÞdt
þCar stock ð0Þ
ð12Þ
Car distribution and sales ðcorrespond to flow activity 5Þ
¼Car production ð13Þ
Recycled raw material ðcorrespond to flow activity 14Þ
¼Number of cars recycled ð14Þ
Demand for raw material ðcorrespond to flow activity 22Þ
¼Raw material and reuse material needed for production ð15Þ
Deficit reuse material needed for production ðcorrespond to flow
activity 18Þ¼Number of cars reused 2Raw material and
reuse material needed for production
ð16Þ
Check for sufficient reuse material inventory ðcorrespond to
flow activity 19Þ¼{1;If deficit reuse material needed
for production .0;0;otherwise:}
ð17Þ
Case 1 :Reuse material inventory sufficient to meet product
requirement ðcorrespond to flow activity 17Þ¼jCheck for sufficient
reuse material inventory ðYes ¼1Þ21j;
ð18Þ
where jjrepresents absolute value.
Case 2 :Reuse material inventory not sufficient to meet production
requirement ðcorrespond to flow activity 20Þ¼jCheck for sufficient
reuse material inventory ðNo ¼0Þ21j
ð19Þ
Use of reuse material in case 2 ðcorrespond to flow activity 21Þ
¼Case 2 :reuse material inventory not sufficient to meet product
requirement £Number of cars reused
ð20Þ
Demand for raw material in case 2 ðcorrespond to flow activity 23Þ
¼Case 2 :reuse material inventory not sufficient to meet product
requirement £ðDemand for raw material 2Number of cars reusedÞ
ð21Þ
Deficit raw material needed for production ðcorrespond to flow activity
18Þ¼Recycled raw material 2Demand for raw material in case 2 ð22Þ
Check for sufficient raw material inventory ðcorrespond to flow activity
26Þ¼{1;If deficit raw material needed for production .0;0;otherwise:}ð23Þ
Japanese
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Case A :raw material inventory sufficient to meet production
requirement ðcorrespond to flow activity 24Þ¼jCheck for sufficient
raw material inventory ðYes ¼1Þ21j
ð24Þ
Case B :raw material inventory not sufficient to meet production
requirement ðcorrespond to flow activity 27Þ¼jCheck for sufficient
raw material inventory ðNo ¼0Þ21j
ð25Þ
Use raw material inventory in case B ðcorrespond to flow activity 28Þ
¼Case B :raw material inventory not sufficient to meet production
requirement £Recycled raw material
ð26Þ
Demand for import of raw material ðcorrespond to flow activity 29Þ
¼Case B :raw material inventory not sufficient to meet production
requirement £ðDemand for raw material in case
22Recycled raw materialÞ
ð27Þ
Model testing
Many modelers have developed specific tests to validate SD model conditions
(Forrester, 1961; Forrester and Senge, 1980). These tests enable discovering
weaknesses (or flaws) in the SD model. The extreme condition (also called
structure validation) test and behavior sensitivity test are often used for the SD model
validation.
During the behavior sensitivity test, modelers change the parameters and observe
which parameters are highly sensitive and then compare whether this behavior
matches the real system (Barlas, 1996). Therefore, in order to compare whether model
behavior matches real system or not, historical performance data is required. In our
case, compatible long-term historical data were not available for reverse supply chain
and impact of government ELV regulations. Thus, only the extreme condition test is
conducted in this study.
The extreme condition test involves assigning extreme values for selected model
parameters and comparing the model generated behavior to the observed behavior of
the real system under the same extreme conditions (Barlas, 1996). During the structure
validity phase in the extreme condition test, modelers check out whether each flow and
stock equation makes sense even when their inputs take on extreme values and the
model responds plausibly when subjected to extreme policies, shocks and parameter
changes (Sterman, 2000). In this section, two extreme conditions are illustrated as an
example by using car consumption demand. By subjecting these extreme conditions,
the anticipated behavior of the model can be observed.
In the first test, the maximum car consumption demand is examined to observe the
behavior. For example, economic boom resulted in increased car consumption. The
anticipated behavior is increasing raw material demand to meet domestic car
consumption demand. Figure 5 shows the resulting behavior under the condition in
which sales increased 500 percent in 2004 and increased 5 percent each year thereafter.
JMTM
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126
The anticipated behavior is increased raw material demand for Japan covered through
import when cars have reached the end of useful life after 2004. In the case of the US,
since the average useful life of a car is 14 years counting from the base year 1993, the
increased raw material demand covered through domestic sources or import will occur
from 2007 onwards. The downward blip in raw material demand in the year after 2013
in both graphs in Figure 5 is the result of increased recycled raw material availability
in that year.
In the second test, the minimum car consumption demand (sales ¼zero) is used for
the extreme condition test after 2004. For instance, company develops something
which is a substitute for the car, etc. The anticipated behavior is raw material demand
reduced to zero, shown in Figure 6.
Observing these extreme conditions, the model tests suggest that the models are
reliable and can be used to explore closed loop supply chains for both Japan and the USA.
Japanese car consumption forecast
Car consumption and recycle data are used for the period 1983-2024. The simulation
model uses data for the real car vehicle consumption during 1983-2003 in Japan
Figure 5.
Result of the behavior
(demand for raw material)
under the maximum
extreme condition
0
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
70,000,000
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
Year
Cars
Car Consumption
Forecast
Demand for Import
of Raw Material
Figure 6.
Result of the behavior
(demand for the raw
material) under the
minimum extreme
condition
0
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
70,000,000
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
Year
Cars
Car Consumption
Forecast
Demand for Import of
Raw Material
Japanese
automotive
industry
127
(JAMA, 2004). From 2004 to 2024 consumption is estimated using Holt’s (exponential
smoothing forecast with trend approach) for the Japanese model.
Forecasting time series that exhibit linear trend
In the Japanese market, we believe the trend of the car vehicle consumption can be
observed as a linear trend with a small growth rate which needs to be validated.
The model to forecast a time series that exhibits a linear trend is:
Yt¼B0þB1tþ[t
In this model, B
0
represents the y intercept and B
1
the slope of the time series. [
t
is
the random error at time t. Linear regression can be used to test for trend. If pvalue is
small (less than (
a
) we can conclude that a linear trend model is appropriate.
Regression approach (Table III) determined that a linear trend in Japanese car sales
as p-value for B
1
coefficient was less than 0.05. The next step is to select a forecasting
method. One technique is to use the regression equation based on the historical time
series data to forecast future time series values. Although theoretically the regression
equation should only be used within the range of observed value of t(from 1 to n), as
long as the period we wish to forecast is not too far into the future, using the regression
equation should give a reasonable forecast. The forecast for a time period t is obtained
by substituting value of tinto the regression equation.
Suppose there are nvalues of the time series and we wish to forecast values for
periods nþ1, nþ2, nþ3, and so on. One potential draw back of the regression
approach is that the formulae used to determine the vales for the y intercept (B
0
) and
slope (B
1
) of the regression line treat all time series points equally. Consequently,
earlier observations of the time series from periods 1 and 2 have as much influence on
these estimates as later values from periods n21 and n.
Holt’s linear exponential smoothing is one of the effective forecasting tools for time
series that exhibit a linear trend. Time series data to which this technique is
appropriate has a level that is smooth or slowly changing and non-seasonal; and trend
that is smooth, slowly changing rate of change of level. This technique is based on the
assumption that the trend tends to flatten towards end of data. The new forecast is the
sum of smoothed level and smoothed trend; each described by the following
relationships given in equations (28) and (29).
Smoothed level ¼
a
£ðLast period’s actual salesÞþð12
a
Þ
£Last period’s forecast ð28Þ
Smoothed trend ¼
g
£ðThis period smoothed level 2Last period
smoothed levelÞð12
g
Þ£Smoothed trend for last period ð29Þ
where
a
is the smoothing factor for level, and
g
is the smoothing factor for trend.
Higher values for a smoothing constant
a
for the level and smoothing constant
g
for
the trend place more weight on the recent values. On the other hand, if the time series
level and trend change slowly, lower values are assigned to smoothing constants.
Number of (
a
,
g
) combinations were tried to forecast Japanese car sales. We choose
a
¼0.1 and
g
¼0.2 for Japanese car sales projections as this combination generated
JMTM
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128
Summary
output
Regression
statistics
Multiple R0.874803579
R
2
0.765281302
Adjusted R
2
0.757709731
Standard error 414,142.6592
Observations 33
ANOVA
Df SS MS F Significance F
Regression 1 1.73354 £10
þ13
1.73354 £10
þ13
101.0729891 2.82087 £10
þ11
Residual 31 5.31694 £10
þ12
1.71514 £10
þ11
Total 32 2.26524 £10
þ13
Coefficients Standard error t-stat p-value
Lower 95
percent
Upper 95
percent
Lower 95.0
percent
Upper 95.0
percent
Intercept 2,300,664.152 147,526.6253 15.59490802 3.18551 £10
þ16
1,999,781.448 2,601,546.855 1,999,781.448 2,601,546.855
Xvariable 1 76,117.8877 7,571.277659 10.05350631 2.82087 £10
þ11
60,676.1565 91,559.6189 60,676.1565 91,559.6189
Residual
output
Probability
output
Observation Predicted Y Residuals Percentile Y
1 2,376,782.039 25,974.96078 1.515151515 2,286,795
2 2,452,899.927 174,187.0731 4.545454545 2,402,757
3 2,529,017.815 424,008.1854 7.575757576 2,449,429
4 2,605,135.702 2318,340.7023 10.60606061 2,500,095
5 2,681,253.59 56,387.40998 13.63636364 2,627,087
6 2,757,371.478 2307,942.4777 16.66666667 2,737,641
7 2,833,489.365 2333,394.3654 19.6969697 2,854,176
8 2,909,607.253 252,897.25312 22.72727273 2,856,710
9 2,985,725.141 51,147.85918 25.75757576 2,866,695
10 3,061,843.029 2207,667.0285 28.78787879 2,953,026
(continued)
Table III.
Linear regression table
showing estimated
coefficient of the
regression line for
Japanese car
consumption
Japanese
automotive
industry
129
11 3,137,960.916 2271,265.9162 31.81818182 3,036,873
12 3,214,078.804 2175,806.8039 34.84848485 3,038,272
13 3,290,196.692 2154,585.6916 37.87878788 3,095,554
14 3,366,314.579 2270,760.5793 40.90909091 3,104,083
15 3,442,432.467 2338,349.467 43.93939394 3,135,611
16 3,518,550.355 2372,527.3547 46.96969697 3,146,023
17 3,594,668.242 2319,868.2424 50 3,274,800
18 3,670,786.13 46,572.86988 53.03030303 3,717,359
19 3,746,904.018 656,844.9822 56.06060606 4,093,148
20 3,823,021.906 1,279,637.094 59.09090909 4,154,084
21 3,899,139.793 969,093.2068 62.12121212 4,199,451
22 3,975,257.681 478,754.3191 65.15151515 4,210,168
23 4,051,375.569 148,075.4314 68.18181818 4,259,872
24 4,127,493.456 82,674.54367 71.21212121 4,289,683
25 4,203,611.344 240,293.656 74.24242424 4,403,749
26 4,279,729.232 388,998.7683 77.27272727 4,441,354
27 4,355,847.119 136,158.8806 80.3030303 4,443,905
28 4,431,965.007 2338,817.0071 83.33333333 4,454,012
29 4,508,082.895 2353,998.8948 86.36363636 4,460,014
30 4,584,200.783 2324,328.7825 89.39393939 4,492,006
31 4,660,318.67 2370,635.6702 92.42424242 4,668,728
32 4,736,436.558 2295,082.5579 95.45454545 4,868,233
33 4,812,554.446 2352,540.4456 98.48484848 5,102,659
Table III.
JMTM
18,2
130
smallest forecast errors for Japanese car sales projection. The resulting vehicle
consumption graphs using actual and forecast data are shown in Figures 7 and 8.
Japanese end of life vehicle recovery rates
In the base scenario analysis for Japan, actual percents are used for dispose, reuse and
recycle of cars that reached their end of lives and export rates (in 2003) of used cars
Figure 7.
Japanese motor vehicle
consumption from
1971 to 2003
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
Year
Cars
Figure 8.
Japanese motor vehicle
consumption forecast for
the period 2004-2024
4,400,000
4,500,000
4,600,000
4,700,000
4,800,000
4,900,000
5,000,000
5,100,000
5,200,000
5,300,000
5,400,000
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
Year
Cars
Japanese
automotive
industry
131
from Japanese government statistics is shown in Table IV (Ministry of Economy,
Trade and Industry, 2004).
The simulation model uses Japanese government goals to achieve 95 percent
recycle rate and also to reduce disposal rate from 17.5 percent in 2003 to 5 percent in
2015. The 12.5 percent reduction in disposal rate by 2015 is equally distributed to
2003 reuse and recycle rates, each of them increase by 6.25 percent, respectively.
Further, the dispose rate used in this study will be 0 percent by 2023. A breakdown of
dispose, reuse and recycle rates for vehicles reaching their end of lives is shown in
Table V.
Japanese used car export rate
It is also necessary to have a clearer understanding of the impact of used car
export on emerging countries. For example, the EU has already implemented the
ELV since the start of 2002. Both recycling and political systems are slightly
different between EU and Japan. The research indicates the EU’s ELV has made
significant impact on the used car market in emerging countries. According to the
Czech News Agency (2003), Czech Republic’s import of used cars doubled in 2002
compared to 2001. About ninety percent of used cars in 2002 came from
Germany, France, Italy and Belgium. Nearly, 67 percent of the imported cars in
the Czech Republic were from Germany (Table VI). Furthermore, in Poland used
Dispose rate 80 percent 17.5 percent
Reuse rate 32.5 percent
Recycle rate 50 percent
Used car export rate 20 percent
Source: Ministry of Economy, Trade and Industry (2004)
Table IV.
Japanese end of life
vehicle recovery rates
and used car export
rate – 2003
2003 (percent) 2015 (percent)
Dispose rate 17.5 5
Reuse rate 32.5 38.75
Recycle rate 50 56.25
Table V.
Japanese end of life
vehicle recovery rates
summary 2003 and
2015
Case in Czech Republic in 2002 Case in Poland in 2003
Used car import has increased about twice in 2002
from 2001
Used car consumption has increased by
257.6 percent in 2003 compared to 2002
90 percent used imported cars came from Germany,
France, Italy and Belgium in 2002
New car sales decline by 32.1 percent in 2003
Table VI.
Used car imports case in
Czech Republic in 2002,
and in Poland in 2003
JMTM
18,2
132
car consumption has increased by 257.6 percent, when comparing 115,257 units for
eight months in 2002 with 400,000 units during the same period in 2003. Also, this
trend has forced the new car sales decline by 32.1 percent. Poland’s number one
retailer Fiat has had their sales decline by 58 percent (Table VI) (Automotive News
Europe, 2004). Thus, the ELV in Europe has greatly impacted not only used car
export, but also sales of new cars.
The SD model assumes an increase in used cars export for Japan of 50 percent from
2003 to 2004, and subsequent annual increase of additional 1 percent during the period
2004-2023. These numbers are based on statistics on the export of used cars to East
European countries (Automotive News Europe, 2004). The used car export rate increase
in subsequent years (starting 2004) is assumed to be a pessimistic number for the
analysis because Japan has different political system and geographical limitations in
exporting to other countries (Anonymous, 2005).
Base scenario analysis
Figure 9 shows the number of cars reaching their end of lives that will be reused,
recycled, and disposed in Japan during the period 2004-2023. These results are
generated from a SD simulation model.
Recycling and reuse fluctuated because both are affected by consumption, however,
recycling will be affected more than reuse. Moreover, the volume of recycling and reuse
are decreasing gradually. The dispose rate is decreasing as well, however, the
volume itself is small. Thus, from a logistical point of view, the dispose rate is more or
less the same.
Japan has no material resources within the country. Thus, manufacturers have to
import raw material to maintain the production. Figure 10 shows Japanese demand for
the import of raw material (2004-2024).
Figure 9.
Japanese used cars
dispose, reuse, and recycle
amounts during 2004-2024
4,000,000
3,500,000
3,000,000
2,500,000
2,000,000
1,500,000
Cars
Year
Number of Cars
Disposed
Number of Cars
Recycled
Number of Cars
Reused
1,000,000
500,000
0
2004
2006
2008
2010
2024
2022
2020
2018
2016
2014
2012
Japanese
automotive
industry
133
Final finding pertain to increase in used car export as shown in Figure 11. Since, the
Japanese manufacturer does not need to pay the recycling, reuse, and disposing fees
and due to strong demand from emerging countries for used cars, manufacturers will
export more used cars. Greater demands to export used cars affect the significantly
declining volume of reuse and recycle material.
Dynamic analysis
Although, the base scenario analysis is important, another set of scenario analyses is
conducted by changing the parameters in the SD model. In investigating different
Figure 10.
Japanese demand for
import of raw material
4,000,000
3,500,000
3,000,000
2,500,000
2,000,000
1,500,000
Cars
Year
1,000,000
500,000
0
2004
2006
2008
2010
2024
2022
2020
2018
2016
2014
2012
Figure 11.
Japanese yearly used car
export
4,000,000
3,500,000
3,000,000
2,500,000
2,000,000
1,500,000
Cars
Year
1,000,000
500,000
0
2004
2006
2008
2010
2024
2022
2020
2018
2016
2014
2012
JMTM
18,2
134
scenarios for the Japanese model, the baseline case, where the used car export rate
(increased 50 percent from 2003 to 2004) provides useful insight. The four scenarios
studied included used car export rate decrease/increase of 250, 0, 100 and 150 percent,
respectively, from 2003 to 2004. Figure 12 shows the impact of the used car export rate
decrease/increase (for different scenarios used relative to the base scenario) on the
amount of yearly raw material import for Japan.
Investigating the scenarios selected for Japanese car markets, clearly the SD model
results show the predictable behavior. Figure 12 shows Japan’s car industry will
import higher or lower amounts of raw material depending upon Japanese used car
export rate is larger or smaller than baseline case.
Conclusions and recommendations
In this study, we have examined relationships between reduce, reuse, recycle and
disposal in the Japanese car market with base scenario analysis using the car
consumption data and forecast. The SD model was also subjected to an extreme
conditions test for structural validity. Dynamic analysis of different market scenarios
for the Japanese car industry’s reverse supply chain was also conducted that showed
the predictable behavior.
Japanese ELV regulation will enhance used car export rate. Since, the Japanese
Government did not impose additional tax on used car export, manufacturers tend
to export more used cars. If the government wants to create an efficient closed loop
supply chain within Japan, it is essential to impose some recycle tax to control the
used car exports. Doing so will improve economic opportunities for
remanufacturers, recyclers, government, manufacturers and consumers.
Furthermore, by providing a used car export option in Japanese reverse supply
chain, we should not lose sight of whether the emerging countries are able to
support an efficient reverse supply chain system or not. If they are not, the Japanese
government and manufacturers should take initiative to create or support the
reverse logistics facilities in export countries as part of their social responsibility. In
2003, 55 percent of the total Japanese used car export was directed to New Zealand
(23 percent), UAE (13 percent), England (10 percent), and Russia (9 percent)
(JUMVA, 2003). These countries will be the key for creating an efficient new
Figure 12.
Impact of Japanese used
car export rate decrease
and increase by 250, 0, 50,
100, and 150 percent in
2003-2004 and subsequent
additional annual increase
of 1 percent on yearly raw
material import amounts
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
2004
2007
2010
2013
2016
2019
2022
Year
Cars
Used Car Export
Rate = –50%
Used Car Export
Rate = 0%
Used Car Export
Rate = 50% (Base)
Used Car Export
Rate = 100%
Used Car Export
Rate = 150%
Japanese
automotive
industry
135
Japanese closed loop supply chain. This concept will be a win-win situation because
Japan can export used cars to these countries to meet their demand. This will also
prevent mass disposal and emission problems in these countries. The quality of
used cars is surely taken into consideration by the Japanese manufacturers in their
export.
It will be very difficult for any country to create self-sustainable closed loop supply
chains. Both the exporting and importing country should consider creating a
cooperative relationship to realize an ideal closed loop supply chain. Japan has a
geographical advantage being close to the countries which use right-handed vehicles
and these countries have a potential demand for the used cars. Thus, these countries
should be included in developing partnerships with the Japanese closed loop supply
chain.
Companies are often looking at forward supply chains for their products to realize
gains in their cash flows and they are ignoring the importance of reverse logistics.
However, in the long run, it is important that they look at the reverse supply chain as
an essential factor for increasing cash flows because it will reduce raw material cost. If
a company wants to minimize possibilities of negative cash flows in a reverse supply
chain, it is essential for the company to have a closed loop supply chain perspective
when developing new products. Issues pertaining to how product components can be
recycled, reused, or remanufactured should be considered during the product design
phase. Doing so will surely reduce the cost of parts, raw materials, and also be
environmentally friendly.
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recycle/Nagoya
About the authors
Sameer Kumar is a Professor of Decision Sciences and Qwest Endowed Chair in Global
Communications and Technology Management in the College of Business, University of
Japanese
automotive
industry
137
St Thomas, Minneapolis, Minnesota. Major areas of research interests include optimization
concepts applied to various aspects of global supply chain management, information systems,
technology management, product and process innovation, and capital investment
justifications. Sameer Kumar is the corresponding author and can be contacted at:
skumar@stthomas.edu
Teruyuki Yamaoka has an MBA from the University of St Thomas, Minneapolis and BS in
Economics from Konan University in Kobe, Japan. Teruyuki had worked as an intern at Kiku
enterprises Inc. during 2002-2003. He has also worked as a Japanese business, travel and tour
consultant.
JMTM
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138
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... PVAL materials are also widely produced and consumed in Japan and the United States. Kuraray (Japan) is the world's biggest single producer of PVAL, accounting for 16% of total global capacity and supplying over 50 distinct grades [8], [9]. ...
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In Japan, the Law for Recycling of Specified Kinds of Consumer Electric Goods has been enforced in full from April 2001. Japanese laws related to the environment and recycling are leading the world and are called "Japan models". As a result the accomplishments of these laws are attracting attention throughout the world. Nationwide implementation of the Home Appliances Recycling Law, including deployment of home electric appliance recycling plants and their technical issues in Japan, are summarized.
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Reverse logistics can have a significant impact on the cost of owning an item, and is an important factor to consider in calculating the total cost of ownership (TCO), when making a purchasing decision. Frameworks for calculating TCO are presented from the literature. Then, the impact of reverse logistics on each of these costs is discussed. The importance of including disposal and end-of-life costs in any total cost of ownership calculation is also discussed.Total cost of ownership (TCO) is a structured approach for determining the total costs associated with the acquisition and subsequent use of a given item or service from a given supplier (Carr and Ittner, 1992). An important area for consideration in TCO is the cost associated with product returns (LaLonde and pohlen, 1996). Reverse logistics (RL) is the process of moving products the “wrong way,” from the customer back to the supplier. Many of these costs are affected by the presence of a reverse logistics system, and this should be taken into account in the calculation of total costs of ownership.
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While companies spend much effort on the design, analysis, and management of their forward supply chains, they need to pay the same attention to their reverse supply chain. Pioneering firms have learned that making product returns profitable relies on good design of the reverse chains' business processes, including integration with the forward chain. Product modularity offers new possibilities for supply chain design. Optimal closed-loop supply chain management requires three things. First, the type of return needs to be matched with the appropriate closed-loop supply chain. Second, through modular reuse, optimal value can be regained in closed-loop applications. Third, the value of reuse information may in some cases be higher than the value of the returns themselves.
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The key issue facing local Japanese government is improving the planning capability of local government staff; municipal governments in particular want to do more but lack the geo-political power. For example the city of Tatebayashi, as well as the towns of Itakura and Meiwa located in the Gunma prefecture are not well known to many Japanese people. Those areas are located in the Nikko city suburbs, a beautiful area known for the famous Toshogu shrine and Kinugawa ravine, in addition to popular hot springs. Developing the tourist industry may trigger further development of other industries and boost the economy in those cities and towns. These areas also have quality resources for promoting tourism including rare regional wild flowers, beautiful flower gardens, and Japanese festivals. Unfortunately, these areas have long been ignored and without any serious political representation mainly due to their geo-political location, which is outside the famous tourist sites. Under such conditions, improving the planning capability of those municipal governments is required to further develop the local economy using the present resources of the tourist industry. Another key subject facing local governments are environmental issues such as solid waste management, which requires extensive preparation capabilities by staff, specifically efficient in arranging and executing plans. However, there are very few useful tools to assist in effectively formulating plans, projection of quantitative effects to acquire the necessary budget, or successfully incorporating the participation of local citizens.
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This article examines strategic production and operations management issues in product recovery management (PRM). PRM encompasses the management of all used and discarded products, components, and materials for which a manufacturing company is legally, contractually, or otherwise responsible. The objective of PRM is to recover as much of the economic (and ecological) value of used and discarded products, components, and materials as reasonably possible, thereby reducing the ultimate quantities of waste to a minimum. This article also discusses the relevance of PRM to durable products manufacturers. It contains a categorization of PRM decisions. A case study based on the PRM system of a multinational copier manufacturer is presented to illustrate a set of specific production and operations management issues. The experiences of two other pro-active manufacturers (BMW and IBM) are also discussed.
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The “Law of Industrial Dynamics” is a well-known phenomenon which leads to significant swings in demand as orders are passed down along a supply chain. Large fluctuations in demand result for the manufacturer leading to policies which counteract the objectives of materials logistics management which are to reduce inventories while maintaining strategic stocks, improve product quality, minimize the total cost of operations and procurement, ensure service levels to customers and minimize variance in material flow. A number of strategies have been advocated and applied which may be summarized as integrating the supply chain and adopting lean manufacturing techniques. Such strategies encompass three main factors, classified as technological (which may include adopting electronic data interchange), organizational (such as moving towards focused plants) and attitudinal (such as the adoption of Partnership Sourcing as a strategy). This paper provides a framework in which systems dynamics modeling, analysis and simulation aids in the decision making process to establish how best to achieve the materials logistics management objectives. Firstly, during the modeling and analysis phase, the supply chain champion is provided with insight as to the effectiveness of the current supply chain design to damp down order fluctuations. Secondly, on the basis of continuous improvement, simulation then allows him to re-engineer the supply chain by asking “what if?” questions and assessing the relative benefits of various strategies against the financial and attitudinal costs of implementation.
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Model validation constitutes a very important step in system dynamics methodology. Yet, both published and informal evidence indicates that there has been little effort in system dynamics community explicitly devoted to model validity and validation. Validation is a prolonged and complicated pro-cess, involving both formal/quantitative tools and informal/ qualitative ones. This paper focuses on the formal aspects of validation and presents a taxonomy of various aspects and steps of formal model validation. First, there is a very brief discussion of the philosophical issues involved in model validation, followed by a flowchart that describes the logical sequence in which various validation activities must be carried out. The crucial nature of structure validity in system dynamics (causal-descriptive) models is emphasized. Then examples are given of specific validity tests used in each of the three major stages of model validation: Structural tests.
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Wittenberg notes some differences between models of theories and models of real systems and then concludes that validation of these two types of models must be fundamentally different: Behavior validation, which is important in validating models of real systems, loses its meaning in validating models of theories, where emphasis must shift to structural validity. My first disagreement with this argument is its implication that for models of real systems emphasis is normally on behavior validity. In fact, since system dynamics models are causal ones, structural validity must always be crucial, whether one deals with models of theories or models of real systems. Without structural validity, behavior validity is meaningless for any system dynamics model, by definition. (This is not true for noncausal, statistical models.) I therefore find superfluous, even misleading, Wittenberg's suggestion that emphasis be shifted to evaluating the structural validity of models of theories. My other objection to Wittenberg's conclusion is its suggestion that behavior validity is spurious for all models of theories, by their nature. This is a false generalization. It is often possible (sometimes necessary) to carry out tests of behavior validity on models of theories. In fact, the boundary adequacy test that Wittenberg himself performs on Sterman's model is an important counterexample. Since a major stated purpose of Sterman's model is to test the dynamic consistency of Kuhn's theory, behavior validity becomes crucial! If we argue as Wittenberg suggests, that behavior validity of Sterman's model is spurious by definition (because we have no "objective" access to the alleged behavior), then this means that the model makes a major claim tbat is impossible to test, which is tantamount to declaring tbe model void. The only way to evaluate the dynamic consistency of any theory is to compare its alleged behavior with its deduced behavior. Since Wittenberg states that the purpose of models of theories is in general "to probe an argument's internal consistency," bis conclusions about behavior validity would render all models of theories void, in principle. My disagreement with Wittenberg's distinction between validating models of real systems and validating models of theories should not imply that I am against any such distinction. One could come up with a number of practical differences