MODELING AND ANALYSIS OF MANUFACTURING SYSTEMS Session 8 CELLULAR MANUFACTURING GROUP TECHNOLOGY

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MODELING AND ANALYSIS OFMANUFACTURING SYSTEMS
Session 8 CELLULAR MANUFACTURING GROUP
TECHNOLOGY

• E. Gutierrez-MiraveteSpring 2001

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ORIGINS

• FLANDERS PRODUCT ORIENTED DEPARTMENTS FOR
  STANDARIZED PRODUCTS WITH MINIMAL TRANSPORTATION
  (1925)
• SOKOLOVSKI/MITROFANOV PARTS WITH SIMILAR
  FEATURES MANUFACTURED TOGETHER
• BURBIDGES SISTEMATIC PLANNING

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BASIC PRINCIPLE

• SIMILAR THINGS SHOULD BE DONE SIMILARLY
• THINGS
• PRODUCT DESIGN
• PROCESS PLANNING
• FABRICATION ASSEMBLY
• PRODUCTION CONTROL
• ADMINISTRATIVE FUNCTIONS

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TENETS OF GROUP TECHNOLOGY

• DIVIDE THE MANUFACTURING FACILITY INTO SMALL
  GROUPS OR CELLS OF MACHINES (1-5)
• THIS IS CALLED CELLULAR MANUFACTURING

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A Typical Cell

• Machining Center
• On-machine Inspection Monitoring Devices
• Tool and Part Storage
• Part Handling Robot Control Hardware

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COMMENTS

• CONFIGURING MACHINES INTO COHESIVE GROUPS IS AN
  ALTERNATIVE TO PROCESS LAYOUT
• GROUP CONFIGURATION IS MOST APPROPRIATE FOR
  MEDIUM VARIETY, MEDIUM VOLUME ENVIRONMENTS
  (Fig.1.6, p. 11)

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COMMENTS

• GROUP TECHNOLOGY AIMS TOWARDS A PRODUCT-TYPE
  LAYOUT WITHIN EACH GROUP
• RESULTANT GROUPS DEDICATED EACH TO A FAMILY OF
  PARTS
• NEW PARTS ARE DESIGNED TO BE COMPATIBLE WITH
  EXISTING FAMILIES

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COMMENTS

• EXPERIENCE ACCUMULATES AND STANDARD PROCESS PLANS
  AND TOOLING ARE DEVELOPED
• SHORT-CYCLE, JUST-IN-TIME PRODUCTION BECOMES
  POSSIBLE
• SINCE NEW PARTS AND EXISTING PARTS ARE SIMILAR,
  PRODUCTION IS ACCELERATED

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A GT approach to design

• COMPOSITE PART FAMILIES
• Fig. 6.1 , p. 165

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FACILITY LAYOUT

• EACH PART TYPE FLOWS ONLY THROUGH ITS SPECIFIC
  GROUP AREA
• WORKERS MAY BE CROSS-TRAINED ON ALL MACHINES IN
  GROUP AND FOLLOW PARTS FROM START TO FINISH
• MACHINE SCHEDULING IS SIMPLIFIED
• See Fig. 6.2, p. 166

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FACILITY LAYOUT TYPESFig 6.3 p. 167

• GT FLOW LINE
• ALL PARTS ASSIGNED TO A GROUP FOLLOW SAME
  MACHINE SEQUENCE
• GT CELL
• PARTS CAN MOVE FROM MACHINE TO MACHINE
• GT CENTER
• LOGICAL ARRANGEMENT

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BENEFITS OF GT

• EASE OF DESIGN RETRIEVAL
• DESIGN STANDARIZATION
• SETUP TIME REDUCTION
• REDUCED THROUGHPUT TIME
• INCREASING QUALITY
• REDUCED LABOR COSTS
• INCREASED JOB SATISFACTION

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Generic Benefits of GT

• SIMPLIFICATION
• STANDARIZATION
• See Table 6.1 p. 168
• See also queuing model of GT system with set-up
  time reduction on p. 168

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STEPS IN GT PLANNING

• CODING
• SPECIFICATION OF KNOWLEDGE CONCERNING
  SIMILARITIES BETWEEN PARTS
• CLASSIFICATION
• USE OF CODES TO ASSIGN PARTS TO FAMILIES
• LAYOUT
• PHYSICAL PLACEMENT OF FACILITES

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CHARACTERISTICS OF SUCCESSFUL GROUPS

• TEAM
• PRODUCTS
• FACILITIES
• GROUP LAYOUT
• TARGET
• INDEPENDENCE
• SIZE
• See Table 6.2, p. 170

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CODING SCHEMES

• BASIS OF GT
• GOAL TO COMPACTLY DESCRIBE PART CHARACTERISTICS
  AND DEFINE HOW ACTIVITIES SHOULD BE PERFORMED

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Features of Good Coding Systems

• INCLUSIVE
• FLEXIBLE
• DISCRIMINATING

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ISSUES GUIDING CODE CONSTRUCTION

• PART POPULATION
• CODE DETAIL
• CODE STRUCTURE
• REPRESENTATION
• Opitz Code (F6.5, 6.6, 6.7)

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CODE DETAIL

• EFFICIENCY
• TOO LITTLE VS TOO MUCH INFO
• SHAPE INFORMATION
• SCALE OF DIMENSIONS
• SECONDARY SHAPE INFORMATION
• STANDARD PART VS CUSTOM MADE
• PRODUCTION RATE
• LIFETIME

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CODE STRUCTURE

• CODE TYPES
• HIERARCHICAL (MONOCODE)
• CHAIN (POLYCODE)
• HYBRID
• See Fig. 6.4, p. 173

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CODE REPRESENTATION

• ALPHANUMERIC VS BINARY CODES

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THE OPTIZ CODING SYSTEM

• FIVE DIGIT GEOMETRIC FORM CODE PLUS
• FOUR DIGIT SUPPLEMENTARY CODE, PLUS
• FOUR DIGIT, COMPANY SPECIFIC SECONDARY CODE
• See Figs 6.5, 6.6, 6.7

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ASSIGNING MACHINES TO GROUPS

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GROUP ANALYSIS

• ONCE PARTS ARE CODED, GROUPS MUST BE FORMED
• GOAL
• TO ASSIGN MACHINES TO GROUPS TO MINIMIZE MATERIAL
  FLOW AMONG GROUPS

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STEPS IN GROUP ANALYSIS

• 1.- DETERMINATION OF PART TYPES REQUIRED BY EACH
  MACHINE TYPE
• MACHINE WITH FEWEST PART TYPES IS THE KEY MACHINE
  and A SUBGROUP IS FORMED OF THOSE PARTS VISITING
  THE KEY MACHINE AND THOSE OTHER MACHINES NEED BY
  THE PARTS
• See Example 6.1, p. 178

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STEPS IN GROUP ANALYSIS

• 2.- DO THE MACHINES IN THE SUBGROUP FALL INTO TWO
  OR MORE DISJOINT SETS WITH RESPECT TO THE PARTS
  THEY SERVICE?
• IF DISJOINT SUBSETS EXIST THE SUBGROUP IS DIVIDED
  INTO SUBGROUPS
• EXCEPTIONAL MACHINES ARE REMOVED

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STEPS IN GROUP ANALYSIS

• 3.- SUBGROUPS ARE COMBINED INTO GROUPS OF THE
  DESIRED SIZE
• SUBGROUPS WITH THE GREATEST NUMBER OF MACHINE
  TYPES ARE COMBINED
• EACH GROUP IS ASSIGNED SUFFICIENT MACHINES AND
  STAFF TO COMPLETE ITS PARTS

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THE MACHINE-PART INDICATOR MATRIX

• A BLOCK-DIAGONAL MATRIX IN WHICH ROWS ARE PARTS
  AND COLUMNS ARE MACHINES
• ROWS SUMMARIZE RESULTS OF STEP 1 OF GROUP
  ANALYSIS
• DENSE BLOCKS OF 1S FORM NATURAL MACHINE-PART
  GROUPS
• See Tables 6.3a and 6.3b

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BINARY ORDERING ALGORITHM

• PROVIDES AN EFFICIENT ROUTINE FOR TAKING AN
  ARBITRARY 0-1 MACHINE-PART MATRIX AND TURNING IT
  INTO BLOCK DIAGONAL FORM

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BINARY ORDERING ALGORITHM

• ENVISION ROWS AS BINARY NUMBERS
• SORT ROWS BY DECREASING ORDER
• ENVISION NOW COLUMNS AS BINARY NUMBERS
• SORT COLUMNS BY DECREASING ORDER
• REPEAT UNTIL ORDERING DOES NOT CHANGE
• See Example 6.2, p. 181

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Comment on BO

• BO ignores
• Machine Utilizations
• Group Sizes
• Exceptional Elements

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SINGLE-PASS HEURISTIC

• MACHINE UTILIZATION
• COMPUTE TOTAL SETUP TIME FOR PART i , fim
• COMPUTE THE TIME AVAILABLE PER MACHINE PER PERIOD
  Rm
• COMPUTE VARIABLE PROCESSING TIME FOR PART i ON
  MACHINE m, vim
• UTILIZATION uim (fimvim)/Rm

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SINGLE-PASS HEURISTIC

• 1.- REPLACE THE 1S IN MACHINE-PART MATRIX BY
  ACTUAL MACHINE UTILIZATIONS (T6.4)
• 2.- USING THE PART ORDERING FROM THE BOA
  ITERATIVELY ASSIGN PARTS AND MACHINES TO GROUPS

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SINGLE PASS-HEURISTIC

• 3.- ASSIGN NEXT PART TO THE FIRST GROUP THAT HAS
  SUFFICIENT CAPACITY ON ALREADY ALLOCATED MACHINES
• 4.- IF NO GROUP HAS CAPACITY, ADD MACHINES TO THE
  MOST RECENT GROUP FORMED SO IT CAN HANDLE THE PART

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Single-Pass Heuristic Example

• See Example 6.3, p. 184
• See resulting Table 6.5, p. 185

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SIMILARITY COEFFICIENTS

• EMPHASIS ON LOCATING MACHINES WITH HIGH
  INTERACTION IN THE SAME GROUP
• NUMBER OF PARTS VISITING MACHINE i , ni
• NUMBER OF PARTS VISITING MACHINE i AND j ,
  nij

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SIMILARITY COEFFICIENT

• sij max ( nij/ni , nij/nj)
• INDICATES THE PROPORTION OF PARTS VISITING
  MACHINE i THAT ALSO VISIT MACHINE j (OR
  VICEVERSA, WHICHEVER IS GREATER)

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HIERARCHICAL CLUSTERING

• 1.- EACH MACHINE IS REPRESENTED BY AN ICON (NODE)
• 2.- NODES ARE CONNECTED BY LINES (ARCS)
• 3.- ARCS ARE LABELED WITH THE VALUES OF sij
• 4.- THE FINAL GRAPH IS THE MODEL

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HIERARCHICAL CLUSTERING

• 4.- ELIMINATE ARCS WITH SMALL VALUES OF sij ( lt
  T )
• 5.- ALL CONNECTED MACHINES CONSTITUTE A GROUP
• 6.- DIFFERENT VALUES OF T ARE TRIED TO GET A
  RANGE OF SOLUTIONS

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Hierarchical Clustering Example

• See Example 6.4, p. 186
• See dendogram on Fig. 6.9, p. 188