A Complete Cellular Manufacturing System Design Methodology Based on Axiomatic Design Principles

7/31/2019 A Complete Cellular Manufacturing System Design Methodology Based on Axiomatic Design Principles

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A complete cellular manufacturing system design methodologybased on axiomatic design principles

O. Kulak a,1 , M.B. Durmusoglu a, *, S. Tufekci b,2

a Industrial Engineering Department, Istanbul Technical University, Macka, Istanbul 34367, Turkeyb Department of ISE, University of Florida, 303 Weil Hall, Gainesville, FL 32611, USA

Available online 8 January 2005

Abstract

This paper provides a framework and a road map for people who are ready to transform their traditionalproduction system from process orientation to cellular orientation, based on Axiomatic Design (AD) principles. A

feedback mechanism for continuous improvement is also suggested for evaluating and improving the cellulardesign against pre-selected performance criteria. A complete implementation of the proposed methodology at amanufacturing company and resulting performance improvements are also provided.q 2004 Elsevier Ltd. All rights reserved.

Keywords: Cellular manufacturing; Axiomatic design; Implementation guide

1. Introduction

With the increasing popularity of lean thinking, cellular manufacturing has become a signicantfocal point in manufacturing. In concert with this development, there have been numerouspublications on design and improvement of cellular manufacturing systems (CMSs). Among these,we can list part family and machine group determination ( Nancy & Wemmerlov, 2002 ), evaluationof grouping efciency measures ( Sarher & Mondal, 1999 ), group scheduling ( Wemmerlo v, 1992 ),machine layout in cells ( Aneke & Carrie, 1986 ) and capacity planning in cellular manufacturing(Sule, 1991 ). Numerous modeling techniques have also been proposed for part family and machinegroup determination, including visual analysis ( Burbridge, 1969 ; Groover, 1987 ), coding and

0360-8352/$ - see front matter q 2004 Elsevier Ltd. All rights reserved.doi:10.1016/j.cie.2004.12.006

Computers & Industrial Engineering 48 (2005) 765787www.elsevier.com/locate/dsw

* Corresponding author. Tel.: C 90 212 293 1300x2666.E-mail addresses: [email protected] (O. Kulak), [email protected] (M.B. Durmusoglu), [email protected]

(S. Tufekci).1 Tel.: C 90 212 293 1300x2746.2 Tel.: C 1 352 392 6753.


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classication ( Choi, 1992 ; Hyer & Wemmerlo w, 1987 ), clustering algorithms ( Singh & Rajamani, 1996 ),mathematical methods ( Heragu & Chen, 1998 ; Soanopoulou, 1999 ) and articial intelligenceapproaches ( Soleymanpour, Vrat, & Shankar, 2002 ; Zhao & Wu, 2000 ). All these approaches aredeveloped to satisfy only one or limited functional requirements of the CMS design. Approaches, whichinclude all aspects of cellular systemdesign, are very limited. Silveira (1999) provides onesuch approach.This approach intends to integrateconcepts andtechniques into an integrated systemin a logical sequence.This approach, however, is mostly based on his past experience and lacks detailed principles forimplementation. With its scientic basis, the authors believe that axiomatic design (AD) approach ( Suh,1990 ) will provide a sound and systematic basis to cellular manufacturing design.

Many AD applications in designing products, systems, organizations and software have appeared inthe literature in the last 10 years. AD theory and principles have been introduced rst time by Suh(1990) . Black and Schroer (1988) provide denition and use of decouplers for achieving exibility inCMSs. Gunasekera and Ali (1995) have provided a three-stage approach to metal forming process. Thestages are composed of conceptual stage, initial stage and nal stage, respectively. The conceptual stageis designed using AD approach. Suh (1997) provided a conceptual approach for dening, classifying anddesign of systems using AD methodology. Suh, Cochran & Paulo (1988) provided an AD-based modelfor an ideal production system in line with lean principles. Babic (1999) provides a decision supportsystem for arrangement of exible manufacturing systems. This approach uses AD design principlestogether with FLEXY intelligent system. Cochran, Eversheim, Kubin, and Sesterhenn (2000) convert

complex production system into small, exible and decentralized production segments. In this approachthey use lean principles in conjunction with segmentation and AD principles. Cochran, Kim & Kim(2000) provide a performance evaluation system for production system. Chen, Chen, and Lin (2000)proposed a knowledge-based decision support system using independence axiom of AD in order toimprove cell performance. Houshmand and Jamshidnezhad (2002) also provide a lean manufacturingbased production system design model using AD approach. In this model organizational capabilities,technological capabilities and value stream analysis are used as the basis. In addition to the design of manufacturing systems, AD approach has also been used in software design ( Kim, Suh, & Kim, 1991 ),product design ( Tseng & Jiao, 1997 ) and quality system design ( Suh, 1995 ) areas. These studies haveconvincingly shown the applicability and benets of AD in solving industrial problems.

Considering the literature mentioned above, a road map including all functional requirements of CMSdesign is not found. In this study, a methodology is developed using AD principles in order to ll thisvoid in the design process.

2. Methodology

With this work, a road map for people who are ready to transform their traditional production systemfrom process orientation to cellular orientation, based on AD principles is provided. In addition, afeedback mechanism for continuous improvement is also provided for evaluating and improving thecellular design against pre-selected performance criteria ( Fig. 1 ).

Selection of project team, ensuring broad-based participation, analysis of current conversion process,and determining conversion strategy for transition to cellular manufacturing constitute the rst stage of

our proposed methodology. The design of the CMS starts following the preliminary stage. At this stagethe AD approach to cellular manufacturing is presented to the transition and design team in a systematic

O. Kulak et al. / Computers & Industrial Engineering 48 (2005) 765787 766


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Axiom 1 . The Independence Axiom. Maintain the independence of functional requirements.

Axiom 2 . The Information Axiom. Minimize the information content.

Mathematically, the relationship between the FRs and DPs are expressed as

fFRg Z jAjfDPg

Here,

{FR} is the functional requirement vector{DP} is the design parameter vector, and

jAj is the design matrix that characterizes the design. In general each entry a ij of jAj relates the ith FR tothe jth DP. The structure of jAj matrix denes the type of design being considered. In order to satisfy theindependence axiom, jAj matrix should be uncoupled or decoupled design. jAj matrix is classied intothree categories as dened below:

Uncoupled Design (most preferred) . In this design, the jAj matrix is a diagonal matrix indicating theindependence of FR-DP pairs. So each FR can be satised by simply considering the corresponding DP.

Decoupled Design (second choice) . In this design the corresponding jAj matrix is triangular.Therefore the FRs can be answered systematically FR 1 to FR n by only considering the rst n DPs. This

design appears most frequently in real life.Coupled Design (undesirable) . In this design the jAj matrix is has no special structure. Therefore achange in any DP may inuence all FRs, simultaneously. In designing systems with AD principles we tryto avoid coupled design as much as possible.

4. Cellular manufacturing system design through AD principles

Step 1. Choose FRs in the Functional Domain . The rst step in designing CMS is to dene thefunctional requirements (FRs) of the system at the highest level of its hierarchy in the functional domain(Suh, Cochran, & Paulo, 1998 ). At this stage many functional requirements may be established. Eachfunctional requirement established at this stage may lead to a completely different cellularmanufacturing design. Therefore, extreme care should be given to all functional requirements beforea single functional requirement is adopted at this highest level. In this work the following has beenselected as the highest FR.

FR Z Provide customized production

More product variety, in smaller batch sizes with highest quality and more frequent deliveries at lowercosts summarize the needs of customers in the 21st century ( Steudel & Desruelle, 1992 ). Theserequirements are forcing companies to re-evaluate their classical manufacturing systems for moreexibility in response to these customer needs. The exibility of a manufacturing system is measured byits speed and ability to respond to rapidly changing customer needs.

Step 2. Mapping of FRs in the Physical Domain . Design parameters (DPs), which satisfy the FRs

established in the previous step, are selected through a mapping process between the functional domainand the physical domain. In order to make the correct DP selection, the DP set corresponding to the FR



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set established before, must be exhaustively generated. The following DP has been selected to satisfy theFR provided above.

DP Z CMS Design

The production system, which can answer customers needs in an efcient way through elimination of waste, reduction of lead time and improved quality is a CMS designed with lean manufacturingprinciples in mind.

Step 3. Decompose FR in the Functional Domain-Zigzagging between the domains . If the DPsproposed for satisfying the FRs dened in steps above can not be implemented without furtherclarication, the AD principles recommends returning to the functional domain for decomposing theFRs into their lower functional requirement set ( Fig. 2 ). The following lower functional requirements setis dened for decomposing the FR determined in Step 1 above.

FR1 Z Classify and group products/parts and machines for simple material owFR2 Z Develop resources capability based on product specicationsFR3 Z Rearrange resources to minimize wasteFR4 Z Provide production based on customer demand.

Step 4. Find the Corresponding DPxs by Mapping FRxs in the Physical Domain . In satisfying thefour FRs dened above, we move to the physical domain from the functional domain. The following DPsare in response to the FRs listed above.

DP1 Z Procedure for dening product/part families and machine groupsDP2 Z Procedure for developing production resources capabilityDP3 Z Product oriented layoutDP4 Z Pull production control system.

Step 5. Determine the Design Matrix . Once the FR-DP sets are dened in Steps 3 and 4, thecorresponding Design Matrix (DM) provides the relationships between the FR and DP elements. It isimportant to insure that the DM as established satises the Independence Axiom (IA) of the ADprinciples. If the DM matrix is uncoupled or decoupled, then it satises the Independence Axiom of ADprinciples (see Suh (2001) ). The design equation and the DM corresponding to the FR-DP sets are asfollows.

FR1

FR2

FR3

FR4

266664

377775

Z

X

X X

X X X

X X X X

266664

377775

DP1

DP2

DP3

DP4

266664

377775

(1)

This design is a decoupled design, and thus, satises the IA. In the DM above, a symbol X represents astrong relationship between the corresponding FR-DP pair.

Step 6. Decompose FR1, FR2, FR3 and FR4 by going from the Physical to the Functional Domainagain and determine the corresponding DPs .



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F i g

. 2 . T h e d e c o m p o s i t i o n o f C M S d e s i g n .



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4.1. Classication and grouping products/parts and machines branch

This is a very important step in the success of transition from traditional manufacturing to cellularmanufacturing ( Irani, 1999 ). The rst step of this branch is to establish the high volume products throughProduct-Quantity (Pareto) analysis. Therefore the products for CMS are simply determined. The nextstep is to group similar parts (in terms of their operation requirements) into parts families. There areseveral algorithmic procedures to accomplish this task. Most of them use the Machine-Part IncidenceMatrix. These algorithms swap rows and the columns of this matrix until suitable block-diagonal sub-matrices or near block-diagonal sub-matrices are obtained. The parts that fall into the same sub-matrixare candidates to be allocated to a potential cell. Once these potential cell allocations are complete, thenext and the nal step of this branch is to decide on how many of these cells to implement based oneconomic justication principles. The designers perform costbenet analyses on each potential cellformation. In this process, each candidate cells contribution to the companys bottom line in terms of productivity, lead time and protability together with return on investment are calculated. Those cellsthat satisfy the company internal rate of return are recommended for formation.

The functional requirement FR1 (classify and group products/parts and machines for simple materialow) as dened above may be decomposed with DP1 (procedure for dening parts families and machinegroups) in mind as:

FR11Z

Determine high volume products/parts to groupFR12 Z Determine operations and machine types for producing each part familyFR13 Z Cluster the parts/machines based on the similarity of operationsFR14 Z Determine nal number of machine groups.

The corresponding DPs may be stated as:

DP11 Z Product-Quantity Pareto AnalysisDP12 Z Machine-Part Incidence MatrixDP13 Z Parts/machines clustering techniquesDP14 Z Cost Analysis and economic justication techniques.

The design matrix for the above set of FRs and DPs areFR11

FR12

FR13

FR14

266664

377775

Z

X

X X

X X X

X X X X

266664

377775

DP11

DP12

DP13

DP14

266664

377775

(2)

Once again, this is a decoupled design satisfying IA of AD.The functional requirement FR14 (determine nal number of machine groups) as dened above may

be decomposed with DP14 (Cost Analysis and economic justication techniques) in mind as:

FR141Z

Ensure improvements of the cell efciencyFR142 Z Prove the economical performance of the cell.



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DP141 Z Dimensional cell analysisDP142 Z Benets/Costs Analysis.

The design matrix for the above set of FRs and DPs are

FR141

FR142" #Z

X

X X " #DP141

DP142" #(3)

Once again, this is a decoupled design satisfying IA of AD.The functional requirement FR141 (ensure improvements of the cell efciency) as dened above may

be decomposed with DP141 (dimensional cell analysis) in mind as:

FR1411 Z Eliminate inappropriate part assignmentsFR1412 Z Eliminate inappropriate machine assignmentsFR1413 Z Increase capability of bottleneck machine which is required more than one cellFR1414 Z Redesign the products for producing the exceptional parts in the related cellFR1415 Z Remove the exceptional parts that make the system complexFR1416 Z Eliminate the bottleneck machines (The bottleneck machine is either a machine which isrequired more than one cell or a machine which its cycle time is greater than takt time.)FR1417 Z Eliminate the high-level utilization of common machines.


DP1411 Z Parts assigned to proper cellDP1412 Z Inter-cell machine transferDP1413 Z Method EngineeringDP1414 Z Redesigned productDP1415 Z Parts that have been transferred out of the cellular systemDP1416 Z Machine duplication between cells and/or new machine acquisition according to the takt timeDP1417 Z Merging cells.


FR1411FR1412FR1413FR1414

FR1415FR1416FR1417

266666666664

377777777775

Z

X

X X

X X X

X X X X

X X X X X

X X X X X X

X X X X X X X

266666666664

377777777775

DP1411DP1412DP1413DP1414

DP1415DP1416DP1417

266666666664

377777777775

(4)

Once again, this is a decoupled design satisfying IA of AD.



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In this stage, nal assignments of parts to cells are realized. Particular attention is given oneliminating of exceptional parts for decreasing inter-cell part movements. Furthermore dueconsideration is also given to reassignment of machines to different cells for elimination inter-cellmovements. Also due attention is given to the machines which can be used instead of bottleneck machines for improvement of its ability to eliminate the bottlenecks and thus decrease inter-cellmovements. After all these efforts if there are some parts which visit multiple cells, the designs of partsare scrutinized through concurrent engineering for possible design changes which may eliminate ordecrease the inter-cell movements of these parts. If all fails, these parts may be considered to be takenout of the cellular system, completely. In the nal analysis, eliminating the bottleneck machines isconsidered. Machine duplication between cells is an alternative to eliminate the bottleneck and todecrease the rest of the inter-cell movements. In addition, a bottleneck machine may appear in the cellaccording to the takt time. Additional machine alternative is considered to respond to the desired takttime. Although all these efforts are performed, the high-level utilization of common machines betweencells is usual. The designer may consider joining several cells into a larger cell, which require mostcommonly used machines in their operation.

4.2. Resources capabilities development branch

In this stage, activities including waste elimination, for the design of a lean process, rearrangement of

resources in agreement with the takt time, xing training needs and motivation of the workforce areaccomplished.

The functional requirement FR2 (develop resources capability based on product specications) asdened above may be decomposed with DP2 (procedure for developing production resources capability)in mind as:

FR21 Z Develop processFR22 Z Select most appropriate process elementsFR23 Z Determine required training/education needsFR24 Z Motivate labor participations.


DP21 Z Simplied and lean processDP22 Z Production resources selection procedureDP23 Z Multi-purpose labor training programsDP24 Z Gain sharing program.


FR21FR22FR23FR24

2664

3775

Z

X X X X X X X X X X

2664

3775

DP21DP22DP23DP24

2664

3775

(5)

Once again, this is a decoupled design satisfying IA of AD.



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The functional requirement FR22 (select most appropriate process elements) as dened above may bedecomposed with DP22 (production resources selection procedure) in mind as:

FR221 Z Time production in concert with customer pull rateFR222 Z Ensure the selection of right machines (machine assignment)FR223 Z Ensure most efcient material movementFR224 Z Ensure labor exibility in the cellFR225 Z Minimize indirect labor needs.


DP221 Z Determined takt time for each familyDP222 Z Selection of machines according to the information axiomDP223 Z Selection of Material Handling System (MHS) based on MHS principlesDP224 Z Appointing multi-skilled worker to the cellDP225 Z Establishment of self directed work teams.


FR221

FR222FR223FR224

FR225

2666664

3777775

Z

X

X X X X X

X X 0 X

0 0 X X X

2666664

3777775

DP221

DP222DP223DP224

DP225

2666664

3777775(6)

Once again, this is a decoupled design satisfying IA of AD.Appropriate production resources are determined following the development of the master process

based on product specications. The cell needs to operate for satisfying customer demand withoutproducing excessive work-in-process inventories and nished goods. In controlling these two measuresthe cell must operate at the calculated takt time. Once the takt time is at hand, the machines capabilityand stafng can easily be determined for effective operations. Based on selected machines, it becomes

feasible to predetermine on the right material handling equipment. Having the required machines and thematerial handling equipment, the designer can now determine the worker capability for the line.Afterwards, the designer builds the decentralized organization based on self-directed teams in order toreduce the needs of indirect labors.

The functional requirement FR23 (determine required training/education needs) as dened abovemay be decomposed with DP23 (multi-purpose labor training programs) in mind as:

FR231 Z Develop waste elimination focusFR232 Z Develop multi-skilled workers.


DP231Z

Lean Manufacturing training and education programDP232 Z Cross-training program.



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FR231

FR232" #Z X X X " #DP231DP232" # (7)Once again, this is a decoupled design satisfying IA of AD.

Once the resource selection is complete, the education and training requirements of the workers canbe established. For ensuring the full participation of workers in the education and training activities

followed by transition to cellular manufacturing, appropriate gain sharing programs must be establishedand announced to the workers for strong buy in. At this stage, internal and/or external resources arerecruited to establish the required lean manufacturing training. In addition, labor certication programsare also established for developing multi-skilled workers who can operate all equipment in the cell.

The functional requirement FR24 (motivate labor participations) as dened above may bedecomposed with DP24 (gain sharing program) in mind as:

FR241 Z Ensure workers participation for 5S activitiesFR242 Z Ensure worker participation in additional lean manufacturing activities.


DP241 Z 5S Reward systemDP242 Z Kaizen teams reward system.


FR241

FR242" #Z X X X " #DP241DP242" # (8)Once again, this is a decoupled design satisfying IA of AD.

One of the major reasons for failure in the lean journey is the lack of institutionalization of 5Sactivities. Inadequate 5S applications always lead into bigger problems during this transition. One wayto insure the success of lean transition is to ensure the workers participation in 5S activities. This may beaccomplished by preparing appropriate 5S score sheet. With this score sheet, cells with higher scores areawarded additional benets and the winning teams are announced company-wide. In addition,appropriate reward system must also be established to recognize the workers who earn new certicationfor additional operations in the cell. Kaizen teams are established to insure the worker participation inother lean manufacturing activities. With the established gain sharing programs workers are motivated toparticipate in these activities.

4.3. Resource rearrangements branch

At this stage lean manufacturing principles are the guiding principles of this design step. In this step,the focus is the waste elimination. Therefore, in rearranging the resources waste due to motion, material

handling and imbalances between resources is minimized. Without this step the designed cell will notprovide the expected performance.



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The functional requirement FR3 (rearrange resources to minimize waste) as dened above may bedecomposed with DP3 (product oriented layout) in mind as:

FR31 Z Minimize material handlingFR32 Z Eliminate wasted motion of operatorsFR33 Z Minimize waste due to imbalance in the cell.


DP31 Z Material ow oriented layoutDP32 Z Arrangement of stations to facilitate operator tasksDP33 Z Balanced resources in response to takt timeThe design matrix for the above set of FRs and DPs are

FR31FR32FR33

24

35

Z

X X X X X X

24

35

DP31DP32DP33

24

35 (9)

Once again, this is a decoupled design satisfying IA of AD.For many products, material-handling cost accounts 3075% of total production cost ( Irani, 1999 ). It

is imperative to locate cells with heavy trafc close together. This also helps reducing stocks as stock points ( Garza & Smunt, 1994 ). Furthermore, U-shaped cell design allows entry and exit points of a cellclose-by thereby minimizing the burden of material handling. Output stocking point of one cell is used asthe inbound stocking point for the downstream cell. Locations of workstations are determined whichmaximizes the in-sequence parts movements ( Aneke & Carrie, 1986 ).

The functional requirement FR31 (minimize material handling) as dened above may be decomposedwith DP31 (material ow oriented layout) in mind as:

FR311 Z Reduce the travel distances of parts between cells due to the locations of cellsFR312 Z Reduce the parts movements due to the locations of stock pointsFR313 Z Reduce the parts movements due to the locations of machinesFR314 Z Reduce the parts movements due to the material handling system.


DP311 Z Cells locations which minimize the travel distances of parts between cellsDP312 Z Appropriate stock pointsDP313 Z Machine locations which maximize the in-sequence parts movementsDP314 Z Appropriate material handling system.


FR311FR312

FR313FR314

2

664

3

775Z

X X X

X X X X X X X

2

664

3

775

DP311DP312

DP313DP314

2

664

3

775(10)



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Once again, this is a decoupled design satisfying IA of AD.In rearranging the resources of the cell, the ultimate goal is to minimize non-value added time of

operators. This comes from operator movements between stations and operators time spent onequipment setup. In addition, stations designed without serious consideration to human factors andergonomics plays a signicant role in these losses due to strenuous working conditions and potentialwork slow down.

The functional requirement FR32 (eliminate wasted motion of operators) as dened above may bedecomposed with DP32 (arrangement of stations to facilitate operator tasks) in mind as:

FR321 Z Minimize operator movements between stationsFR321 Z Minimize operator time during setupFR321 Z Minimize operators wasted time in processing.


DP321 Z Labor allocation to minimize walking distance under the constraint of takt timeDP322 Z Standard tooling, xtures and auxiliary equipments for each cellDP323 Z Ergonomic interfaces between workers and equipments.


FR321

FR322

FR323

264

375

Z

X

0 X

0 0 X

264

375

DP321

DP322

DP323

264

375

(11)

This is an uncoupled design satisfying IA of AD.An ideally balanced cell should utilize all workers, resources and material handling systems to

their fullest capacity. In accomplishing this task, the cell designer must insure that each machinescycle time, operator cycle time and the material handling cycle time are as near to the takt time aspossible. This will insure a smooth mixed/leveled production satisfying customer demand in most

efcient way.The functional requirement FR33 (minimize waste due to imbalance in the system) as dened abovemay be decomposed with DP33 (balanced resources in response to takt time) in mind as:

FR331 Z Ensure that the longest machine cycle time % takt timeFR332 Z Ensure that each operator cycle time % takt time (Operator cycle time is preferably close tothe takt time)FR333 Z Ensure that automated material handling systems cycle time % takt time.


DP331 Z Fitness control of operations assignment of each machine

DP332Z

Fitness control of tasks assignment of each operatorDP333 Z Speed adjustment of material handling system.



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FR331FR332FR333

24

35

Z

X 0 X 0 0 X

24

35

DP331DP332DP333

24

35

(12)

This is an uncoupled design satisfying IA of AD.

4.4. Production control branch

Satisfying customers by right amount and just-in-time production can only be accomplished throughpull system ( Hopp & Spearman, 2000 ). However, just-in-time systems require a steady pull on allproducts in the family. In order to ensure a steady pull, a leveled/mixed production schedule must beestablished. This leads us into developing the appropriate Heijunka schedule and the necessary visualmanagement tools including Kanban system for successful implementation.

The functional requirement FR4 (Provide production based on customer demand) as dened abovemay be decomposed with DP4 (Pull production control system) in mind as:

FR41 Z Ensure smooth and steady production in assembly lineFR42 Z Provide continuous material/information owFR43 Z Provide continuous feedback information ow.


DP41 Z Leveled/Mixed productionDP42 Z Kanban SystemDP43 Z Information/Report System and visual management tools.


FR41FR42FR43

24

35

Z

X X X X X X

24

35

DP41DP42DP43

24

35

(13)

This is a decoupled design satisfying IA of AD.The functional requirement FR41 (Ensure smooth and steady production in assembly line) as dened

above may be decomposed with DP41 (Leveled /Mixed production) in mind as:

FR411 Z Acquire information on desired product mix/volumeFR412 Z Ensure small batch productionFR413 Z Develop smooth assembly sequence.


DP411 Z Continuous information ow from customers

DP412Z

Minimized setup times (SMED)DP413 Z Selected and improved Method for Assembly Sequence.



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FR411

FR412

FR413

264

375

Z

X

X X

X X X

264

375

DP411

DP412

DP413

264

375

(14)

This is a decoupled design satisfying IA of AD.The ultimate goal of cellular manufacturing (and lean manufacturing) is to convert the make-to-stock production system (push production) to make-to-order production system (pull production). In pullproduction material is pulled through the system starting from the customers all the way to the suppliers.Therefore, appropriate pull systems need to be established for assembly, within-cell material movement,between cells material movement and supplier material movement in the plant. Depending upon theconditions of these different plant zones, proper pull mechanisms (Kanban systems) need to be selected.

The functional requirement FR42 (Provide continuous material/information ow) as dened abovemay be decomposed with DP42 (Kanban System) in mind as:

FR421 Z Ensure information /material ow between cells and assemblyFR422 Z Ensure information /material ow within each cell

FR423 Z Ensure information /material ow between the supplier and manufacturer.


DP421 Z Withdrawal Kanban SystemDP422 Z Production Kanban SystemDP423 Z Supplier Kanban System.


FR421

FR422FR423

264

375

Z

X

X X X X X

264

375

DP421

DP422DP423

264

375 (15)

This is a decoupled design satisfying IA of AD.In order to smooth production, mixed model production schedule at nal assembly cell or pacemaker

cell is prepared. According to this schedule, the parts needed by the cell have to be obtained in necessaryquantities and at necessary times through the supplier cells. Information also has to be ready in neededcells and at needed times.

The functional requirement FR421 (Ensure information /material ow between cells and assembly) asdened above may be decomposed with DP421 (Withdrawal Kanban System) in mind as:

FR4211Z

Transport consistent quantities between cells and assemblyFR4212 Z Ensure timely deliveries.



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DP4211 Z Standard container size from cells to assembly lineDP4212 Z Optimal number of withdrawal Kanban.


FR4211FR4212 Z X X X DP4211DP4212 (16)

This is a decoupled design satisfying IA of AD.In order to obtain needed materials and information ows in CMS, a Kanban system is required.

Production Kanban is an order to launch production within cell. On the other hand, production Kanban isactivated by withdrawal Kanban. Instead of classical Kanban, decouplers, chutes, conveyor, Kanbansquare or operator are used within cell. The appropriate one(s) among them is necessary to be chosen.The selection criteria can be determined as simplicity and cost.

The functional requirement FR422 (Ensure information/material ow within each cell) as denedabove may be decomposed with DP422 (Production Kanban System) in mind as:

FR4221 Z Transport consistent quantities within the cellFR4222 Z Ensure timely deliveries between cell operations.


DP4221 Z Standard container size and one piece ow within the cellDP4222 Z Appropriate arrangement within cell (decouplers, chutes, conveyors, Kanban squares).


FR4221FR4222 Z X X X DP4221DP4222 (17)

This is a decoupled design satisfying IA of AD.Supplier reliability becomes a very important issue in JIT manufacturing. Once the system operates in

pull environment, it is natural to expect the suppliers to also become JIT suppliers. Inadequate lot sizesand/or inadequate deliveries from the suppliers lead into sub-optimal plant performance. Excessiveamount of deliveries and large shipments lead into inated raw material stocks and increased lead timewithout impacting the plant throughput. On the other hand, infrequent and or unreliable deliveries andsmaller than requested batch sizes, lead into lost productivity and starvation of some of the equipmentwithin the plant. Therefore, appropriate procedures for supplier Kanban calculations and suppliercontainer size determination must be implemented at this stage. Some analytical techniques exist forestimating these two parameters.

The functional requirement FR423 (Ensure information /material ow between the supplier andmanufacturer) as dened above may be decomposed with DP423 (Supplier Kanban) in mind as:

FR4231 Z Transport consistent quantities from the supplierFR4232 Z Ensure timely deliveries from the supplier.



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DP4231 Z Standard container size from the supplierDP4232 Z Optimal number of supplier Kanbans.


FR4231

FR4232 Z

X

X X DP4231

DP4232 (18)

This is a decoupled design satisfying IA of AD.Visual management tools are an important part of a lean manufacturing. They play a signicant role in

the success of the lean journey. Therefore, well developed visual management and feedback system willhelp signicantly in improving the newly designed cells and become an important part of the feedback mechanism as proposed in Fig. 1 . These visual tools are simple, yet signicant information tools thathelp workers to assess the system performance and conditions at a glance. Some visual managementtools include reports on production performance, quality performance and TPM related visual toolsincluding OEE measures, to name a few. There are many specic visual tools available in each categorylisted above. The design team must select an appropriate set of visual management tools and their updatefrequencies to support the cellular manufacturing activities. Additional visual management tools may be

added to the system during the feedback cycle.The functional requirement FR43 (Provide continuous feedback information ow) as dened above

may be decomposed with DP43 (Information/Report System and visual management tools) in mind as:

FR431 Z Provide means to improve systemFR432 Z Ensure freshness of data.


DP431 Z Data systemDP432 Z Data acquisition schedule.

The design matrix for the above set of FRs and DPs areFR431FR432 Z X X X DP431DP432 (19)

This is a decoupled design satisfying IA of AD.

5. Implementation and results

A manufacturingcompany producing aluminum walkways,bridges, stairs andramps in USAwasfocusedon CMS implementation for customized production. The proposed methodology was implemented step by

step in transforming its system from the existing classical manufacturing to a CMS. Each stage of implementation based on proposed methodology is summarized in the following sections.



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5.1. Preliminary design stage

Before implementation, the facility layout of the system was functionally organized as shown Fig. 3 .Following the project team selection, plans have been devised for company-wide participation in thetransition to lean and cellular manufacturing. Around this time, 6-day lean manufacturing and TPMworkshops were provided to 80% of the factory personnel.

5.2. Classication and grouping products/parts and machines stage (FR1-DP1)

The rst task was to dene the product families. Based on the machine-part incidence matrix the teamdecided that stairs, ramp and landings were ideal candidates for cellular manufacturing. Ensuingeconomic analysis and justication showed that each cell was economically feasible and desirable. Dueto large sizes of the incoming aluminum raw material stock, it was also economically more acceptable tocut incoming stock to smaller sizes later to be resized at each cell by using the 22 00 saw as a commonmachine at the entrance to the facility.

5.3. Resources capabilities development stage (FR2-DP2)

After determining the desired takt time for each cell, the team proceeded with the selection of theprocess elements. It is at this stage the team concluded that each cell should have its own saw, which ismuch smaller than the large saw that cater to all cells. Furthermore proper allocation of weldingmachines have also been established for each cell and several new power outlets needed to be installed toservice these welding machines. In order to maintain a smooth product ow, each cell received theappropriate number of punches, milling machines and bufng equipment. The educational and trainingneeds of the workers, supervisors and team leaders were established around this time. This was followedby a series of lean manufacturing and TPM workshops for supervisors, team leaders and majority of theworkforce. These team leaders started all out announcement of lean journey, cellular manufacturing andthe importance of 5S activities plant-wide. For maintaining the 5S discipline, 5S evaluation worksheetswere developed and routinely implemented as a prelude for the gain sharing program. Once the standard

work in each cell was dened, proper metrics were developed for continuous improvement monitoring.Based on these metrics, appropriate gain sharing program was developed. This gain sharing program waswidely publicized throughout the plant and a copy of this program was made available to all plantpersonnel.

5.4. Resource rearrangements stage (FR3-DP3)

With the participation of cell teams nal acquisition in each cell was determined. Machine locationswere xed to maximize the in-sequence parts movements. Fig. 4 provides the new layout of the facilitybased on three newly formed cells. Stafng of the cell was nalized based on the current cell takt timerequirements. Tasks were assigned to workers to minimize idle times. Worker assignments according tothe Takt time for ramp cell as an example is shown in Table 1 .



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F i g

. 3 . O l d l a y o u t

b e f o r e t r a n s

f o r m a t

i o n .



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F i g

. 4 . N e w c e

l l u l a r

l a y o u t a f t e r t

h e t r a n s f o r m a t

i o n .



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5.5. Production control stage (FR4-DP4)

Based on rm demand and forecasted sales, production volume and eventually mixed leveledassembly plans were established for each cell. Based on these leveled production plan optimal containersizes and number of containers have been established for each cell. For Kanban implementation, newcarts have been built to transport batches between stations and also act as Kanban signals. Similarly, theKanban operations between the cells and the 22 00 saw supermarket were established throughtransportation carts built in-house. Once again, the sizes of each cart were determined through proper

analytical tools. Before the start of the implementation of cellular manufacturing, material supplierswere not very reliable and usually promised once a week deliveries. Usually the lowest cost suppliershad won the bids without paying attention to their performance both on delivery frequencies andreliability. Through new vendor certication and rating system, all potential suppliers were evaluated.Several visits and conferences were held with current and potential vendors. The need for just-in-timedeliveries and reliability were emphasized in those meetings. After proper negotiations, nal vendorsselected promised daily deliveries with smaller batch sizes responding to companys supplier Kanbansignals. In order to maintain the overall equipment effectiveness, total quality control and just-in-timeproduction, appropriate information feedback system and visual management tools were developed.Through posting of this information at suitable places in each cell, workers were transformed into self-monitoring and continuous improvement teams. With the availability of gain sharing system details,

they were able to evaluate the impact of improvements to their pocketbooks.The rst stage of lean transformation started in May 2000. Table 2 provides the comparativemeasurements of important business metrics as of May 2000 and as of December 2001, for the Ramp

Table 1Worker assignment for ramp cell according to the Takt time

Ramp cell Takt time: 438 s

Mini cells Operations Cycle time (s) Number of workers

Vertical Milling, drilling 300 1Welding, cleaning 840 2

Mounting channel Punching, bufng 360 1Other parts Cutting, punching, bufng,

bendingMax. 1200 3

Assembly Welding, cleaning 1620 4

Table 2Comparison of business metrics

Performance criteria Before cellular manufacturing After cellular manufacturing

Raw material stock (days of inventory) 11 3.5Lead time (days) 18 7Scrap rate (%) 3 1.6Throughput (units pairs) 50 70Overtime (hours/week) 300 60

WIP (days inventory) 6 2.5Material move distances (m) 67 31



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Cell. The travel distance of parts from 67 to 34 m with cellular system design was reduced. This is a 54%improvement. Similarly, the manufacturing lead time has been reduced by 60% to 7 days from itsoriginal 18 days. As expected, we have achieved a solid 58% reduction in WIP. The most strikingimprovement has been achieved in overtime reduction. An 80% reduction in this metric was achieved.One of the primary reasons for this improvement is explained by our new design elimination the 22 00 sawand allocation smaller dedicated saws to each cell.

6. Conclusions

In this paper we provide a complete and concise methodology for transforming a process orientedmanufacturing facility into a CMS. The methodology is based on Axiomatic Design principles. Theproposed process is also implemented at a company that manufactures aluminum ramp rails, landingsand stairwells. The results show that the proposed methodology is sound, easy to follow and implement.Details of the feedback mechanism for continuous improvement of the cellular system under theguidelines of AD principles will be presented at our subsequent publications.

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A Complete Cellular Manufacturing System Design Methodology Based on Axiomatic Design Principles