Transcript IENG 471 Lecture 05 - South Dakota School of Mines and

IENG 471 - Lecture 05
Group Technology –
Production Flow Analysis
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Assignments
 Current Assignment: HW 4
 Download spreadsheet from the Group Technology II Link on the
Materials page – follow the steps for Kings’ Algorithm
 HW:
(HW 4) See Assignment Link
 Individual Assignment
 Can work together in groups, but each person turns in their own
assignment
 PRINT out the initial and final matrix for each problem
 Highlight the family cells on the final matrix
 Interpret the final matrix of family cells – list which items
compose each family, AND discuss how that affects the
operation of the facility
 Next Assignment: Exam I
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Volume, Variety & Automation
100,000
Rembold, et. al.
Transfer
Line
Production Quantity
High
Increasing
Flexibility
Batch
Flow
Line
10,000
Increasing
Productivity
1,000
Medium
Flexible
Mfg Sys
100
Low
Mfg Cell
NC Machine
1
1
Low
10
100
Medium
Part Variety
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1,000
High
4
Layout Impact on Facility’s Machines
 Job Shop Layout
 Group by individual machines
 Add all equipment fractions, then round up*
 Mass Production Layout
 Group by individual products
 Round up* all equipment fractions, then add
 Cellular Layout
 Group by similar part-process families
 Add family equipment fractions, then round up*,
then add
* Multiply number of each machine type by footprint size after rounding
to find the actual space required
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Product
Layout
Medium
Low
Product Volume
High
Layout Patterns
Bulky, Difficult to Move Prod.
(Planes, ships, etc.)
Family / GT
Cell Layout
Bulky, Difficult to Move Equip.
(Precision fixtures)
Fixed Location
Layout
Low
Medium
Process
Layout
High
Product Variety
Can Have Combinations (HYBRIDS)!
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Examples
 For the following situations, what type of
General Layout would you suggest?
 The assembly of bodies for GM midsize SUVs
 Fabrication & Assembly of custom made sheet metal parts
 Fabrication of computer cases for a line of desktop PCs, plus
custom made sheet metal parts
 Assembly of three distinct families of electronic cards for inkjet
printers
 Production of high quality, custom office furniture
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Group Technology (GT)
 Philosophy:
 Use the similarity of current products to simplify
the design and manufacturing of new products
 Some Applications:
 Identify and reuse similar process plans
 Identify and reuse similar CNC programs
 Identify the equipment that may be best used in a
particular machine cell
 Identify and eliminate redundant inventory
 Requirement:
 A taxonomy of part characteristics
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Benefits of GT
 Facilitates formation of part





families and machine cells
Quick retrieval of designs,
drawings, & process plans
Reduces design
duplication
Provides reliable workpiece
statistics
Facilitates accurate
estimation of machine tool
requirements and logical
machine loadings
Permits rationalization of
tooling setups, reduces
setup time, and reduces
production throughput time
 Allows rationalization and




improvement in tool design
Aids production planning
and scheduling procedures
Improves cost estimation
and facilitates cost
accounting procedures
Provides for better machine
tool utilization and better
use of tools, fixtures, &
people
Facilitates NC part
programming.
(Ham)
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How to Identify Groups
 Similar Design Attributes
 Size of parts
 Geometric shape of parts
 Materials
 Technique: Parts Classification & Coding
 Similar Manufacturing Attributes
 Common processing steps (routings)
 Common tools and fixtures
 Technique: Production Flow Analysis
 Similarity groupings are called Part Families
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PFA Introduction
 PFA is Production Flow Analysis
 A subset of Group Technology (GT)
 Goals:
 Reduce material transport efforts
 Reduce set up efforts
 Reduce work in process inventory
 Steps:
 Identify OP-Codes for each Component
 Routing/Process Planning information for each part
 Incidence Matrix
 Blocking (Triangularization) Algorithm
 Cluster Identification
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OP-Codes
 An OP-Code forms an index to an Operation Plan
 An Operation Plan is a generalized sequence of
steps, perhaps common to multiple parts
 An OP-Code Sequence is a method of condensing
the Operation Plan into a compact structure
suitable for data processing
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OP-Code Example
OP Code
01 Saw01
02 Lathe02
Rotational Part
(sectional view)
03 Grind01
04 Insp06
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Operation Plan
Cut to size
Face end
Center drill
Drill
Ream
Bore
Turn straight
Turn groove
Chamfer
Cut off
Face
Chamfer
Grind
Inspect dimension
Inspect finish
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OP-Code Example
OP Code
01 Saw01
02 Lathe02
03 Grind01
04 Insp06
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Operation Plan
Cut to size
Face end
Center drill
Drill
Ream
Bore
Turn straight
Turn groove
Chamfer
Cut off
Face
Chamfer
Grind
Inspect dimension
Inspect finish
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OP Code
Sequence
01
02
03
04
Saw01
Lathe02
Grind01
Insp06
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Incidence Matrix
 Rows represent OP-Codes
(index = i)
 Columns represent Components
(index = j)
 Cell Entries are:
(Mij)
 1 (or mark) - if the component requires the operation
 0 (or blank) - if the component does NOT require the operation
A-112
Saw01
A-115
1
Lathe01
Lathe02
1
Drill01
1
Mill02
1
Mill05
Grind05
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King’s Algorithm – Step 1
 Calculate the total (binary) weight of each column j:
Wj =  2i Mij
After Chang, Wysk, &
i
A1
S01
A2
1
A3
A4
A5
1
1
1
L01
L02
A6
A7
A8
A9
1
1
1
1
1
M02
1
1
1
1
1
M05
1
1
1
1
G06
1
Wj
138
48
10
6
10
64
64
10
10
336
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A0
1
D01
G05
Wang (1998) p.500
Rank
5
3
2
1
2
4
4
2
2
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i
2
1
4
2
8
3
16
4
32
5
64
6
128
7
256
8
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King’s Algorithm – Step 2
 Sort the columns into rank order, then go to Step 3:
A4
A3
A5
A8
A9
S01
1
1
1
1
1
1
L01
1
1
1
1
1
1
L02
A2
D01
1
M02
1
M05
A6
A7
A1
1
1
1
G05
1
1
G06
1
10
10
10
10
48
64
64
138
336
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Wj
Rank
A0
1
2
2
2
2
3
4
4
5
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King’s Algorithm – Step 3
 Calculate the total (binary) weight of each row i:
Wi =  2j Mij
j
A4
A3
A5
A8
A9
S01
1
1
1
1
1
L01
1
L02
1
1
1
A2
A6
A7
A1
1
1
1
D01
1
M02
1
M05
1
1
1
G05
1
1
G06
1
2
4
8
16
32
64
128
256
512
1024
1
2
3
4
5
6
7
8
9
10
2j
j
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Wi
Rank
574
4
2
1
602
5
1088
7
64
2
1408
8
512
3
1024
6
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King’s Algorithm – Step 4
 If all rows are in rank order STOP; otherwise, sort the rows into
rank order, and then go to Step 1:
A4
L01
A3
A5
A8
A9
A2
A6
A7
1
M05
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Rank
1
64
2
1
512
3
1
1
1
1
1
574
4
1
1
1
1
1
602
5
1
1024
6
1
1088
7
1
1408
8
G06
D01
Wi
2
1
G05
L02
A0
1
M02
S01
A1
1
1
1
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King’s Algorithm – Step 1 (2nd time)
 Calculate the total (binary) weight of each column j:
Wj =  2i Mij
i
A4
L01
A3
A5
A8
A9
A2
A6
A7
1
L02
4
2
1
8
3
1
1
1
1
1
16
4
1
1
1
1
1
32
5
1
64
6
1
128
7
1
256
8
D01
1
M05
1
1
18
48
48
48
48
132
256
256
56
448
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i
1
G06
Rank
2i
2
1
G05
Wj
A0
1
M02
S01
A1
1
2
2
2
2
4
5
5
3
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King’s Algorithm – Step 2 (2nd time)
 Sort the columns into rank order, then go to Step 3:
A4
L01
A3
A5
A8
A9
A1
A6
A7
1
G05
1
1
L02
1
1
1
1
1
1
1
1
1
1
G06
1
D01
1
M05
1
1
48
48
48
56
132
256
256
448
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1
48
Rank
1
18
Wj
A0
1
M02
S01
A2
1
2
2
2
2
3
4
5
5
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King’s Algorithm – Step 3 (2nd time)
 Calculate the total (binary) weight of each row i:
Wi =  2j Mij
j
A4
L01
A3
A5
A8
A9
A1
A6
A7
1
L02
Rank
1
128
5
1
64
2
1
1
1
1
1
126
4
1
1
1
1
1
124
3
1
1024
6
1
1152
7
1
1792
8
G06
D01
1
M05
1
1
2
4
8
16
32
64
128
256
512
1024
1
2
3
4
5
6
7
8
9
10
2j
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Wi
2
1
G05
j
A0
1
M02
S01
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King’s Algorithm – Step 4 (2nd time)
 If all rows are in rank order STOP; otherwise, sort the rows into
rank order, and then go to Step 1:
A4
L01
A3
A5
A8
A9
L02
M02
A2
A6
A7
1
M05
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Wi
Rank
2
1
1
64
2
1
1
1
1
1
124
3
1
1
1
1
1
126
4
128
5
1
1024
6
1
1152
7
1
1792
8
1
G06
D01
A0
1
G05
S01
A1
1
1
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King’s Algorithm – Step 1 (3rd time)
 Calculate the total (binary) weight of each column j:
Wj =  2i Mij
i
A4
L01
A3
A5
A8
A9
A2
A6
A7
L02
1
1
4
2
1
1
1
1
1
8
3
1
1
1
1
1
16
4
32
5
1
64
6
1
128
7
256
8
1
D01
1
M05
1
1
1
18
24
24
24
24
26
160
256
256
510
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i
1
G06
Rank
2i
2
M02
Wj
A0
1
G05
S01
A1
1
2
2
2
2
3
4
5
5
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King’s Algorithm – Step 2 (3rd time)
 Sort the columns into rank order, then go to Step 3:
NO CHANGE IN SORTED ORDER!
A4
L01
A3
A5
A8
A9
A2
A6
A7
1
L02
1
1
1
1
1
1
1
1
1
1
1
M02
1
G06
1
D01
1
M05
1
1
24
24
24
26
160
256
256
510
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24
Rank
1
18
Wj
A0
1
G05
S01
A1
1
2
2
2
2
3
4
5
5
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King’s Algorithm – Step 3 (3rd time)
 Calculate the total (binary) weight of each row i:
Wi =  2j Mij
j
A4
L01
A3
A5
A8
A9
A2
A6
A7
L02
1
Rank
1
1
64
2
1
1
1
1
1
124
3
1
1
1
1
1
126
4
128
5
1
1024
6
1
1152
7
1
1792
8
1
G06
D01
1
M05
1
1
2
4
8
16
32
64
128
256
512
1024
1
2
3
4
5
6
7
8
9
10
2j
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Wi
2
M02
j
A0
1
G05
S01
A1
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King’s Algorithm – Step 4 (3rd time)
 If all rows are in rank order STOP; otherwise, sort the rows into
rank order, and then go to Step 1:
SINCE THE ROWS WERE IN RANK ORDER, WE STOP!
A4
L01
A3
A5
A8
A9
L02
M02
A2
A6
A7
1
M05
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Wi
Rank
2
1
1
64
2
1
1
1
1
1
124
3
1
1
1
1
1
126
4
128
5
1
1024
6
1
1152
7
1
1792
8
1
G06
D01
A0
1
G05
S01
A1
(yea!)
1
1
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Partitioning
 Ideally, the cells form mutually exclusive blocks (as below). These
blocks define the Families:
 Family A consists of Components A1, A3, A4, A5, A8, and A9; which
can be machined in a cell performing Operations G05, L01, L02, and
S01
 Family B consists of Components A0, A2, A6, and A7; which can be
machined in a cell performing Operations D01, G06, M02, and M05
A4
L01
A3
A5
A8
A9
A2
A6
A7
1
L02
1
1
1
1
1
1
1
1
1
1
1
M02
1
G06
1
D01
1
M05
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1
G05
S01
A1
1
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1
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Partitioning
 Often, the cells do NOT form mutually exclusive blocks (as below).
In this case, the capability for Operation G06 must be common to
both machining cells:
 Family A consists of Components A1, A3, A4, A5, A8, and A9; which can be
machined in a cell performing Operations G05, G06, L01, L02, and S01
 Family B consists of Components A0, A2, A6, and A7; which can be
machined in a cell performing Operations D01, G06, M02, and M05
A4
L01
A3
A5
A8
A9
A6
A7
A0
1
L02
1
1
1
1
1
1
1
1
1
1
1
M02
1
G06
1
D01
1
1
M05
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A2
1
G05
S01
A1
1
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Strategies for Overlapping PFA Blocks:
 Provide for transporting some components between cells requiring
the overlapping operation(s)
 Pick the component(s) with the smallest volume(s) to transport to
reduce handling costs
 Locate the cells with operation overlap as near to each other as
possible to reduce handling costs
 Avoid scheduling concurrent production runs of the components that
require overlapping operation(s)
 Assumes that the equipment providing the overlapping capability
can be easily moved between cells
 This solution may improve capacity if the overlapping operation
is a bottleneck
 Put equipment capable of the overlapping operation(s) into each cell
requiring it
 Assumes the additional equipment capability is cost justifiable
 This solution will improve capacity if the overlapping operation is
a bottleneck
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Extended GT (PFA)
 Requirements:
 Need for grouping similar items together, and identifying
separable items
 Matrix of related entities:
 Tooling
 Equipment
 Parts
 Integrated Circuits
 Modular Components
 Solution Method: Triangularization
 Direct Clustering Algorithm
 King’s Method
 Kusiak’s Triangularization Method
 Ullman’s Design Structure Matrix
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Relationship (Incidence) Matrix
 Rows and Columns:
 Parts requiring operations on different machines
 Tools (in a CNC magazine) needed to produce
part families
 Departments requiring technicians (shared head
count)
 Departments requiring adjacent location
 ICs requiring modularization
 An entry in the incidence matrix means that there
is a strong relationship between the row and
column items
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