agile manufacturing(1)

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AGILE MANUFACTURING

Seminar on

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 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 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.

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.

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

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

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

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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

Source: Google(www.emeraldinsight.in)

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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

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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

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.

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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’.

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TABLE 5 : Performance rating furnished by experts using linguistic terms pertaining to agile supply chain enabler

‘Virtual Enterprise/Organization’.


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TABLE-6:Importance weights furnished by experts using linguistic terms pertaining to agile supply chain

enabler ‘Virtual Enterprise/Organization


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 performance level of XYZ was assessed as ‘Very Agile’

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Identification of importance indices of ASC attributes is calculated Fuzzy Performance Improvement index (FPII) of ASC attributes

FPII is calculated using the Eq below

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

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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

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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

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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.

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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 axiom2. Information axiom

Information content (I) is defined as follows:

Where, P is the probability of design requirements beingsatisfied

If there are n design requirements, the total informationcontent Itotal is defined as follows:

24Main contents of axiomatic design1. 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

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

26A 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.

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

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,


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From DS11, we can divide DR11 further. Yet, as different work procedure requires different indicator of machining accuracy


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

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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

With the above analytical processes summed up , the equipment selection indicators built based on independence axiom and the design matrix

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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

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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

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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 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.

35 REFERENCES

1. Feng-Tsai Weng & Shien-Ming Jenq :Application integrating axiomatic design and agile manufacturing unit in product evaluation International Journal of Advance Manufacturing Technology (2012) 63:181–189

2. S.Vinodh , S.R.Devadasan , K.E.K. Vimal, Deepak Kumar : Design of agile supply chain assessment model and its case study in an Indian automotive components manufacturing organization

3. R. Anthony Inman, R. Samuel Sale : Agile manufacturing: Relation to JIT, operational performance and firm Journal of Operations Management 29 (2011) 343–355

4.Research starters academic topic overviews Reconfigurable Agile Manufacturing EBSCO Research Starters® • Copyright © 2014 EBSCO Information Services, Inc.

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agile manufacturing(1)

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