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MODELING AND ANALYSIS OFMANUFACTURING SYSTEMS
Session 8 CELLULAR
MANUFACTURING GROUP TECHNOLOGY
E. Gutierrez-MiraveteSpring 2001
ORIGINS
• FLANDERS’ PRODUCT ORIENTED DEPARTMENTS FOR STANDARIZED PRODUCTS WITH MINIMAL TRANSPORTATION (1925)
• SOKOLOVSKI/MITROFANOV: PARTS WITH SIMILAR FEATURES MANUFACTURED TOGETHER
• BURBIDGE’S SISTEMATIC PLANNING
BASIC PRINCIPLE• SIMILAR “THINGS” SHOULD BE SIMILAR “THINGS” SHOULD BE
DONE SIMILARLYDONE SIMILARLY
• “THINGS “– PRODUCT DESIGN– PROCESS PLANNING– FABRICATION &ASSEMBLY– PRODUCTION CONTROL– ADMINISTRATIVE FUNCTIONS
TENETS OF GROUP TECHNOLOGY
• DIVIDE THE MANUFACTURING FACILITY INTO SMALL GROUPS OR CELLSCELLS OF MACHINES (1-5)
• THIS IS CALLED CELLULAR CELLULAR MANUFACTURINGMANUFACTURING
A “Typical” Cell
• Machining Center
• On-machine Inspection & Monitoring Devices
• Tool and Part Storage
• Part Handling Robot & Control Hardware
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)
COMMENTS
• GROUP TECHNOLOGY AIMS TOWARDS A PRODUCT-TYPEPRODUCT-TYPE LAYOUT WITHIN EACH GROUP
• RESULTANT GROUPS DEDICATED EACH TO A FAMILY OF PARTSFAMILY OF PARTS
• NEW PARTS NEW PARTS ARE DESIGNED TO BE COMPATIBLECOMPATIBLE WITH EXISTING FAMILIES
COMMENTS
• EXPERIENCEEXPERIENCE ACCUMULATES AND STANDARD PROCESS PLANS AND STANDARD PROCESS PLANS AND TOOLING TOOLING ARE DEVELOPED
• SHORT-CYCLE, JUST-IN-TIME SHORT-CYCLE, JUST-IN-TIME PRODUCTION BECOMES POSSIBLE
• SINCE NEW PARTS AND EXISTING PARTS ARE SIMILAR, PRODUCTION IS ACCELERATED
A GT approach to design
• COMPOSITE PART FAMILIES
• Fig. 6.1 , p. 165
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
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
BENEFITS OF GT
• EASE OF DESIGN RETRIEVAL
• DESIGN STANDARIZATION
• SETUP TIME REDUCTION
• REDUCED THROUGHPUT TIME
• INCREASING QUALITY
• REDUCED LABOR COSTS
• INCREASED JOB SATISFACTION
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
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
CHARACTERISTICS OF CHARACTERISTICS OF SUCCESSFUL GROUPSSUCCESSFUL GROUPS
TEAM
PRODUCTS
FACILITIES
GROUP LAYOUT
TARGET
INDEPENDENCE
SIZE
See Table 6.2, p. 170
CODING SCHEMESCODING SCHEMES
• BASIS OF GT
• GOAL: TO COMPACTLY DESCRIBE PART CHARACTERISTICS AND DEFINE HOW ACTIVITIES SHOULD BE PERFORMED
Features of Good Coding Systems
• INCLUSIVE
• FLEXIBLE
• DISCRIMINATING
ISSUES GUIDING CODE CONSTRUCTION
• PART POPULATION
• CODE DETAIL
• CODE STRUCTURE
• REPRESENTATION
• Opitz Code (F6.5, 6.6, 6.7)
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
CODE STRUCTURE
CODE TYPESHIERARCHICAL (MONOCODE)
CHAIN (POLYCODE)
HYBRID
See Fig. 6.4, p. 173
CODE REPRESENTATION
ALPHANUMERIC VS BINARY CODES
THE OPTIZ CODING SYSTEM
• FIVE DIGIT “GEOMETRIC FORM GEOMETRIC FORM CODECODE” PLUS
• FOUR DIGIT ‘SUPPLEMENTARY SUPPLEMENTARY CODECODE”, PLUS
• FOUR DIGIT, COMPANY SPECIFIC “SECONDARY CODESECONDARY CODE”
• See Figs 6.5, 6.6, 6.7
ASSIGNING MACHINES TO GROUPS
GROUP ANALYSIS
• ONCE PARTS ARE CODED, GROUPS MUST BE FORMED
• GOAL:
TO ASSIGN MACHINES TO GROUPS TO MINIMIZE MATERIAL FLOW
AMONG GROUPS
STEPS IN GROUP ANALYSIS
1.- DETERMINATION OF PART TYPES REQUIRED BY EACH MACHINE TYPE– MACHINE WITH FEWEST PART TYPES
IS THE KEY MACHINE and 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
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
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
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 1’S FORM NATURAL MACHINE-PART GROUPS
• See Tables 6.3a and 6.3b
BINARY ORDERING ALGORITHM
PROVIDES AN EFFICIENT ROUTINE FOR TAKING AN ARBITRARY 0-1 MACHINE-PART MATRIX AND TURNING IT INTO BLOCK DIAGONAL FORM
BINARY ORDERING ALGORITHM
• ENVISION ROWSROWS AS BINARY NUMBERS• SORT ROWS BY DECREASING ORDER• ENVISION NOW COLUMNSCOLUMNS AS BINARY
NUMBERS• SORT COLUMNS BY DECREASING ORDER• REPEATREPEAT UNTIL ORDERING DOES NOT
CHANGE• See Example 6.2, p. 181
Comment on BO
• BO ignores– Machine Utilizations
– Group Sizes
– Exceptional Elements
SINGLE-PASS HEURISTIC
MACHINE UTILIZATIONMACHINE 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 = (fim+vim)/Rm
SINGLE-PASS HEURISTIC
1.- REPLACE THE 1’S 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
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
Single-Pass Heuristic Example
• See Example 6.3, p. 184
• See resulting Table 6.5, p. 185
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
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)
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
HIERARCHICAL CLUSTERING
4.- ELIMINATE ARCS WITH SMALL
VALUES OF sij ( < T )5.- ALL CONNECTED MACHINES
CONSTITUTE A GROUP
6.- DIFFERENT VALUES OF T ARE TRIED TO GET A RANGE OF SOLUTIONS
Hierarchical Clustering Example
• See Example 6.4, p. 186
• See dendogram on Fig. 6.9, p. 188