2. 2 ACKNOWLEDGEMENT
I would like to express my deep gratitude to
all my professors for their patient guidance,
expert guidance, advice in presenting
seminar and enthusiastic encouragement.
Also I would like to thank the authors of the
journals that I referred would also like to
extend my thanks to my classmates for their
full support.
3. 3 CONTENTS
• What is Agile manufacturing ?
• Why do we need to be Agile ?
• Keys to agility and flexibility
• Concept of agility
• Comparison of lean and agile supply chain
• Case studies
1.Design of agile supply chain assessment model in an Indian
automotive components manufacturing organizations.
2. Selection of appropriate machine tools and equipment
selection for doing plane milling by axiomatic design.
• Conclusion
• References
4. 4 INTRODUCTION
Not long ago, manufacturers had greater control over the supply
chain because they controlled the pace at which products were
manufactured and thus when they entered the supply chain
Companies that have learned how to improve management of their
production systems to meet demand, and changes in demand, have
developed a competitive advantage and work hard to maintain that
advantage (Uribe, Cochran, & Shunk , 2003)
Lean focuses on eliminating or reducing any activity or expenditure
that does not add value to a company's operations (Pham &
Thomas, 2005).
5. What is Agile Manufacturing?
Agility in manufacturing helps to reduce material costs,
maximize expenditures for human resources, minimize idle
inventory, and improve facility or machine utilization
(Anuziene & Bargelis)
Roots of agile in America defence industry
Ability to thrive in constant , Unpredictable change
Agile is boundary focused.
5
6. Why do we need to be agile?
Global Competition is intensifying
Mass markets are fragmenting into niche markets.
Cooperation among companies is becoming necessary,
including companies who are in direct competition with
each other
Very short product life-cycles, development time, and
production lead times are required.
6
7. Why do we need to be agile?
(cont )
Customers are expecting:
1. Low volume products
2. High quality products
3. Custom products
Customers want to treated as individuals
7
8. Keys to agility and flexibility
To determine customer needs quickly and continuously
reposition the company against it’s competitors.
To design things quickly based on those individual
needs.
To put them into full scale, quality , production quickly.
To respond to changing volumes and mix quickly.
To respond to a crisis quickly
8
9. 9 The Concept of agility
Fig 1 Agile supply chain
Source: Google(www.emeraldinsight.in)
1.Market sensitive- Supply chain is
capable of reading and responding to real
demand
2.Virtual- Information-based supply chain,
rather than inventory-based
3.Network based- EDI and internet
enable partners in the supply chain to act
upon the real demand
4.Process integration- Collaborative
working between buyers and suppliers,
joint product development, common
systems and shared information
10. Table-1 Comparison of characteristics of lean and agile
supply
Characteristic Lean Agile
Logistics focus Eliminate waste Customers and
markets
Partnerships Long-term , Stable Fluid clusters
Key measure Output measure
such as productivity
and cost
Measure
capabilities, and
focus on customer
satisfaction
Process focus Work
standardization,
conformance to
standards
Focus on operator
self-management to
maximize autonomy
Logistics planning Stable , fixed period Instantaneous
response
10 Source: Google(www.emeraldinsight.in)
11. 11
During the initial phase, the manufacturing processes and the
products manufactured by XYZ were studied.
Then a cross-functional team with seven experts was formed at
XYZ.
Choosing approximate linguistic terms for assessing
performance ratings and importance weights of ASC attributes
Design of agile supply chain
assessment model and its case study in
an Indian automotive components
manufacturing organizations.
12. TABLE-2 : Linguistic terms and fuzzy numbers used.
Source :‘ Design of agile supply chain assessment model and its case study in an Indian automotive
components manufacturing organizations’, Journal of Manufacturing Systems 32 (2013) 620– 631 C
12
13. In order to assess the performance ratings and importance weights
of ASC attributes, the experts were approached with datasheets
TABLE-3 Excerpt of ASC assessment data sheet
Source :‘ Design of agile supply chain assessment model and its case study in an Indian automotive
components manufacturing organizations’, Journal of Manufacturing Systems 32 (2013) 620– 631 C
13
14. During this case study the average fuzzy ratings and average
performance weights were denoted respectively by Rj and Wj
Consolidated fuzzy ratings and fuzzy weights were used to
determine the fuzzy ASC index.
14
15. Source :‘ Design of agile supply chain assessment model and its case study in an Indian
automotive components manufacturing organizations’, Journal of Manufacturing
Systems 32 (2013) 620– 631
TABLE-4 ‘Average fuzzy rating’ and ‘average fuzzy weights’ pertaining to
agile supply chain enabler ‘Virtual Enterprise/Organization’.
15
16. TABLE 5 : Performance rating furnished by experts using linguistic terms
pertaining to agile supply chain enabler ‘Virtual Enterprise/Organization’.
Source :‘ Design of agile supply chain assessment model and its case study in an
Indian automotive components manufacturing organizations’, Journal of
Manufacturing Systems 32 (2013) 620– 631 C
16
17. TABLE-6:Importance weights furnished by experts using linguistic
terms pertaining to agile supply chain enabler ‘Virtual
Enterprise/Organization
Source :‘ Design of agile supply chain assessment model and its case study in an Indian automotive
components manufacturing organizations’, Journal of Manufacturing Systems 32 (2013) 620– 631 C
17
18. Once FACI was obtained, it can be matched with linguistic terms.
During this study, Euclidean distance method was adopted for this
purpose since it is the most intuitive method for humans to use.
In this study, the linguistic terms as(Extremely Agile (EA), Very Agile
(VA), Agile (A), Fairly (F), and Slowly (S)) were chosen for labeling to
determine the ASC Level
The Euclidean distance was calculated using Eq
The Euclidean distance between FASCI and all linguistic terms
used during this case study are shown below.
By matching linguistic label with minimum D, the ASC perfor-
mance level of XYZ was assessed as ‘Very Agile’
18
19. Identification of importance indices of ASC attributes is
calculated Fuzzy Performance Improvement index (FPII) of ASC
attributes
FPII is calculated using the Eq below
19
The mathematical equations and procedure adopted from fuzzy
Logic for calculating FPII and ranking them are presented here
FPII of ASC attributes must be ranked. Here, the ranking of the
fuzzy number is based on centroid method for membership
function (a , b, c) as given in Eq. where a, b and c are the lower,
middle and upper values of triangular fuzzy number
20. 20
The same procedure was followed to calculate the ranking scores of all ASC attributes
Source :‘ Design of agile supply chain assessment model and its case study in an Indian automotive components
manufacturing organizations’, Journal of Manufacturing Systems 32 (2013) 620– 631
-
TABLE 7 Proposals for agile supply chain performance improvement
21. 21
The computation of FAI and Euclidean Distance indicated that the
performance of ASC prevailing at XYZ as ‘Very Agile’
The preliminary study on evaluating ASC index was done using
scoring approach
After determining the ranking scores of ASC attributes, the experts
were requested to fix the management threshold value.
It acts as a minimum value ; attributes have ranking score less than
management threshold will be weaker; otherwise stronger
RESULT
If ranking scores were found to be less than the management
threshold value seven experts were further consulted to suggest
proposals for improving the performance of ASC attributes
22. Application integrating axiomatic
design and agile manufacturing
unit in product evaluation
Selection of appropriate machine tools and equipment
is one of the key techniques in constructing agile
manufacturing units.
This study uses the basis of axiomatic design and customer
requirements, with consideration also given to the factors like
quality, time, and costs, to build a hierarchical decision-making
model for equipment selection in agile manufacturing units.
22
23. Axiomatic design addresses the design requirements , DR,
(what we want) and design solution, DS, (how to achieve the
objects) in the design process and makes effective mapping
and decomposition.
Axiomatic design has two principles for decision making:
1. Independence axiom
2. Information axiom
Information content (I) is defined as follows:
Where, P is the probability of design
requirements being
satisfied
If there are n design requirements, the total information
content Itotal is defined as follows:
23
24. Main contents of axiomatic design
1. Four domains
A “Zig- Zagging” conversion maps from “What” to “How’s”!
Figure 2 Diagram of structural mapping in axiomatic design
Source :Application integrating axiomatic design and agile manufacturing unit
product evaluation, Int J Adv Manuf Technol (2012) 63:181–189
24
25. It is defined by characteristic vectors specifically for design targets
and design solutions
2. Mapping matrix
i) Matrix equation
3. Contents of the axioms
ii) Matrix algebra
Simultaneous equations
25
26. A factory had a shipment of parts to machine and one
of the machining work procedures was plane milling.
Conditions of restriction were set as follows:
C1 for distribution of parts types,
C2 for appropriate machining method,
C3 for appropriate part size, and
C4 for good operational status.
A set of candidate equipment in workshop M: {M1, M2, M3, M4}
was selected, where the four elements represent four milling
machines, respectively.
A manufacturer, whose top goal is to maximize the investment
income ratio.
26
27. Source :Application integrating axiomatic design and agile manufacturing unit
product evaluation, Int J Adv Manuf Technol (2012) 63:181–189
TABLE 9 : Equipment selection indicator based on independence axiom
27
28. Set the basic demand, DR1, as selection of machining
equipment for some work procedure to maximize the income
from investment
The available resources should be utilized as much as
possible so that DS1 is equal to the utilization of machining
equipment available.
The design equation is as follows
Once DS1 is obtained, DR1 can further be divided into DR11,
DR12, and DR13,
The design equation is as follows
28
29. From DS11, we can divide DR11 further. Yet, as different work
procedure requires different indicator of machining accuracy
The design equation is as follows
Machining accuracy affects cutting speed and cutting amount
DR12 can be subdivided based on DS12
DS12 is further divided in to DR121,DR122 and DR123
There are many cost indicators related to the machining
capitalized cost.
Further breakdown of DR13 is made based on DS123
29
30. The design equation is as follows:
The total cost of this step is associated with the machining
time , The design equation is as follows
According to DS133,the energy consumption by the by the
equipment is as follows
30
With the above analytical processes summed up , the
equipment selection indicators built based on independence
axiom and the design matrix
31. Source :Application integrating axiomatic design and agile manufacturing unit
product evaluation, International Journal Advanced Manufacturing Technology
(2012) 63:181–189
RESULT
TABLE 10 : Result of Indicator range of machine tool to process the work
31
32. 32
Equipment evaluation model based on improved information axiom
In equipment evaluation, assuming the equipment with the least
amount of information is the best equipment
Fig.3 Information amount of machining
accuracy for machine tools equipment Fig. 4 Information amount for utilization time
of machine tools
Fig. 5 Information amount for cost spent by
machine tools
Source :Application integrating axiomatic design and agile
manufacturing unit product evaluation, International
Journal Advanced Manufacturing Technology (2012)
63:181–189
33. 33
The forces of globalization and competition that are driving the need for
manufacturing companies to be agile in order to stay competitive
One of the major goals of agile manufacturing is to produce customized
products in a short time at low cost
With Agile Manufacturing we will be able to develop new ways of
interacting with our customers and suppliers.
CONCLUSION
The first case study, paper has contributed a fuzzy logic approach
supported ASC assessment An unique feature of this ASC assessment
model is that it is incorporated with fuzzy logic approach which enables
the use of linguistic terms to assess the performance of ASC attributes.
The ASC assessment model enables the computation of ranking score of
ASC attributes
34. 34
In Second case study, with an aim to maximize the agility and the
industrial gain from investment, independence axiom design to establish
the analytic process of equipment selection indices, to straighten up the
correlations and influences between the indices of all levels.
