MODELING AND ANALYSIS OF MANUFACTURING SYSTEMS Session 8 CELLULAR MANUFACTURING GROUP TECHNOLOGY E. Gutierrez-Miravete Spring 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 DONE SIMILARLYSIMILAR “THINGS” SHOULD BE DONE SIMILARLY “THINGS “ –PRODUCT DESIGN –PROCESS PLANNING –FABRICATION &ASSEMBLY –PRODUCTION CONTROL –ADMINISTRATIVE FUNCTIONS

TENETS OF GROUP TECHNOLOGY CELLSDIVIDE THE MANUFACTURING FACILITY INTO SMALL GROUPS OR CELLS OF MACHINES (1-5) CELLULAR MANUFACTURINGTHIS IS CALLED CELLULAR MANUFACTURING

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

COMMENTS EXPERIENCE STANDARD PROCESS PLANS AND TOOLINGEXPERIENCE ACCUMULATES AND STANDARD PROCESS PLANS AND TOOLING ARE DEVELOPED SHORT-CYCLE, JUST-IN-TIMESHORT-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 TYPES Fig 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 SUCCESSFUL GROUPS TEAM PRODUCTS FACILITIES GROUP LAYOUT TARGET INDEPENDENCE SIZE See Table 6.2, p. 170

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

CODE REPRESENTATION ALPHANUMERIC VS BINARY CODES

THE OPTIZ CODING SYSTEM GEOMETRIC FORM CODEFIVE DIGIT “GEOMETRIC FORM CODE” PLUS SUPPLEMENTARY CODEFOUR DIGIT ‘SUPPLEMENTARY CODE”, PLUS SECONDARY CODEFOUR DIGIT, COMPANY SPECIFIC “SECONDARY 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 KEY MACHINE and –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

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 ROWSENVISION ROWS AS BINARY NUMBERS SORT ROWS BY DECREASING ORDER COLUMNSENVISION NOW COLUMNS 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 UTILIZATION COMPUTE TOTAL SETUP TIME FOR PART i, f im COMPUTE THE TIME AVAILABLE PER MACHINE PER PERIOD R m COMPUTE VARIABLE PROCESSING TIME FOR PART i ON MACHINE m, v im UTILIZATION u im = (f im +v im )/R m

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, n i NUMBER OF PARTS VISITING MACHINE i AND j, n ij

SIMILARITY COEFFICIENT s ij = max ( n ij /n i, n ij /n j ) 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 s ij 4.- THE FINAL GRAPH IS THE MODEL

HIERARCHICAL CLUSTERING 4.- ELIMINATE ARCS WITH SMALL VALUES OF s ij ( < 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