1. 3 Group Technology / Cellular Manufacturing
(Inselfertigung)

2. Group Technology (GT)
Observation already in 1920ies: product-oriented departments to manufacture standardized products in machine companies lead to reduced transportation
Can be considered the start of Group Technology (GT): Parts with similar features are manufactured together with standardized processes  small "focused factories" are created as independent operating units within large facilities.
More generally, GT can be considered a “theory of management” based on the principle "similar things should be done similarly“
"things" .. product design, process planning, fabrication, assembly, and production control (here); but also other activities, including administrative functions.
(c) Prof. Richard F. Hartl
Layout & Design

3. When to use GT? See also Chapter 1 (Figure 1.5)
Pure item flow lines are possible, if volumes are very large.
If volumes are very small, and parts are very different, a functional layout (job shop) is usually appropriate
In the intermediate case of medium-variety, medium-volume environments, group configuration is most appropriate
(c) Prof. Richard F. Hartl
Layout & Design

4. Cellular Manufacturing
Principle of GT: divide the manufacturing facility into small groups or cells of machines  cellular manufacturing
Each cell is dedicated to
a specified family of part types (or few “similar” families).
Preferably, all parts are completed within one cell
Typically, it consists of
a small group of machines, tools, and handling equipment
(c) Prof. Richard F. Hartl
Layout & Design

5. Different Versions of GT
The idea of GT can also be used to build larger groups, such as for instance, a department, possibly composed of several automated cells or several manned machines of various types.
GT flow line
classical GT cell
GT center
(c) Prof. Richard F. Hartl
Layout & Design

6. GT flow line
All parts assigned to a group follow the same machine sequence and require relatively proportional time requirements on each machine.
Automated transfer mechanisms may be possible.
 mixed-model assembly line (Chapter 4)
fräsen
(aus)bohren
drehen
schleifen
bohren
(Askin & Standridge,
1993, p. 167).
(c) Prof. Richard F. Hartl
Layout & Design

7. classical GT cell
Allows parts to move from any machine to any other machine. Flow is not unidirectional.
Since machines are located in close proximity  short and fast transfer is possible.
(Askin & Standridge,
1993, p. 167).
(c) Prof. Richard F. Hartl
Layout & Design

8. GT center Machines located as in a process (job shops)
But each machine is dedicated to producing only certain Part families  only the tooling and control advantages of GT; increased material handling is necessary
When large machines have already been located and cannot be moved, or
When product mix and part families are dynamic  would require frequent relayout of GT cell
(Askin & Standridge, 1993, p. 167).
(c) Prof. Richard F. Hartl
Layout & Design

9. Typical Manufacturing Cell (1)
Often u-shaped for short transport
Even if process layout not possible
Often typical material flow
(c) Prof. Richard F. Hartl
Layout & Design

10. Typical Manufacturing Cell (2)
Example with 3 workers
Also u-shaped
(c) Prof. Richard F. Hartl
Layout & Design

11. Advantages of GT Cell
Short transportation and handling (usually within cell)
Short setup times because often same tools and fixtures can be used (products are similar)
High flexibility (quick reaction on changes)
Investment cost low (no advanced technology necessary)
Clear arrangement, few tools/machines  easy to control
High motivation and satisfaction of workers (identification with “their" products)
Small lot sizes possible
short flow times
(c) Prof. Richard F. Hartl
Layout & Design

12. How to Build Groups/Cells
Basic Idea:
Typical Part Families
Items that look alike
Items that are made with the same equipment
(c) Prof. Richard F. Hartl
Layout & Design

13. Items That Look Alike
Most products that look similar are manufactured using similar production techniques (if similar material)
Parts are grouped because they have similar geometry (about the same size and shape)  they should represent a part family,
e.g. cog wheels (gear wheels) of similar size and material
(c) Prof. Richard F. Hartl
Layout & Design

14. Items That Are Made with Same Equipment
(c) Prof. Richard F. Hartl
Layout & Design

15. How to Build Groups/Cells
Visual inspection “Items that look alike”
may use photos or part prints
utilizes subjective judgment (experience)
Classification & coding by examination of design & production data (same equipment)
most common in industry
time consuming & complicated
(c) Prof. Richard F. Hartl
Layout & Design

16. Codes
The code should be sufficiently flexible to handle future as well as current parts
The scope of part types must be known (e.g. parts rotational, prismatic, sheet metal, etc.?)
The code must discriminate between parts with different values for key attributes (material, tolerances, required machines, etc.)
(c) Prof. Richard F. Hartl
Layout & Design

17. Codes Many coding systems have been developed
None is universally applicable
Most implementations require some customization
Functional classification
coding based on part design attributes
coding based on part manufacturing attributes
coding based on combination of design & manuf. attributes
Structural classification
Hierarchical Structure
Chain Type Structure
Hybrid structure (combination)
(c) Prof. Richard F. Hartl
Layout & Design

18. Hierarchical Code
Meaning of a digit depends on values of preceding digits.
The value of 3 in the third place may indicate
the existence of internal threads in a rotational part: "1232"
a smooth internal feature: “2132"
Hierarchical codes are efficient: they only consider relevant information at each digit
But they are difficult to learn and remember because of the large number of conditional inferences.
(c) Prof. Richard F. Hartl
Layout & Design

19. Chain Code
Each value for each digit of the code has a consistent meaning. The value 3 in the third place has the same meaning for all parts.
Easier to learn but less efficient (longer for same info)
Certain digits may be meaningless for some/many parts.
(c) Prof. Richard F. Hartl
Layout & Design

20. Hybrid Code
Both hierarchical and chain codes have advantages, many commercial codes are hybrid (combination of both)
Some section of the code is a chain code and then several hierarchical digits further detail the specified characteristics.
Several such sections may exist.
One example of a hybrid code is Opitz
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Layout & Design

21. Optiz Classification System
Three sections
12345
6789
ABCD
Form Code:
5 digits
describes the primary design attributes, e.g. shape
Supplementary Code:
4 digits
manuf. attributes. e.g.
dimensions, material, accuracy, starting work piece shape
Secondary Code:
company specific, e.g. type and sequence of prod. operations
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22. Optiz Classification System
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23. Optiz in More Detail 2 2 4 0 0 (c) Prof. Richard F. Hartl
Layout & Design

24. (c) Prof. Richard F. Hartl
Layout & Design

25. Production Flow Analysis (PFA)
Basic idea:
Items that are made with the same processes / the same equipment
These parts are assembled into a part family
Can be grouped into a cell to minimize material handling requirements.
(c) Prof. Richard F. Hartl
Layout & Design

26. How to Build Groups/Cells using PFA
Many clustering methods have been developed
Can be classified into:
Part family grouping: Form part families and then group machines into cells
Machine grouping: Form machine cells based upon similarities in part routing and then allocate parts to cells
Machine-part grouping: Form part families and machine cells simultaneously.
(c) Prof. Richard F. Hartl
Layout & Design

27. Machine-Part Grouping: Obtain Block Diagonal Structure
Construct matrix of machine usage by parts
sort rows (machines) and columns (parts) so that a block-diagonal shape is obtained
Then it is easy to build groups:
Group 1: parts {13, 2, 8, 6, 11 }, machines {B, D}
Group 2: parts { 5, 1, 10, 7, 4, 3}, machines {A, H, I, E}
Group 3: parts { 15, 9, 12, 14}, machines {C, G, F}
(c) Prof. Richard F. Hartl
Layout & Design

28. King’s Algorithm (Rank Order Clustering) Binary Ordering
How to obtain block-diagonal shape?
Example: 5 machines; 6 parts:
Interpret rows and columns as binary numbers
Sort rows w.r.t. decreasing binary numbers
Sort columns w.r.t. decreasing binary numbers
part
machine 1 2 3 4 5 6 A - B C D E
(c) Prof. Richard F. Hartl
Layout & Design

29. Binary Ordering Sort rows w.r.t. decreasing binary numbers
New ordering of machines: B – D – C – A - E
part
value
machine 1 2 3 4 5 6 A - B C D E
= = 20
= 43
= 29
= 35
= 6
25 32
24 16
23 8
22 4
21 2
20 1
(c) Prof. Richard F. Hartl
Layout & Design

30. Binary Ordering Sort columns w.r.t. decreasing binary numbers
part
machine 1 2 3 4 5 6
value B - 43 D 35 C 29 A 20 E
24 = 16
23 = 8
New ordering of parts:
22 = 4
21 = 2
20 = 1 =7
= 24
= 6
= 20
=25
=28
(c) Prof. Richard F. Hartl
Layout & Design

31. Result of Binary Ordering
No complete block-diagonal structure
Remaining items: 6, 5, and 3 produced in both cells
Or machines B, C, and E have to be duplicated
part
machine 6 5 1 3 4 2 B - D C A E
value 28 25 24 20 7
2 groups:
Group 1: parts {6, 5, 1 }, machines {B, D}
Group 2: parts { 3, 4, 2}, machines {C, A, E}
Parts 1, 4, and 2 can be produced in one cell
(c) Prof. Richard F. Hartl
Layout & Design

32. Repeated Binary Ordering
Binary Ordering is a simple heuristic  no guarantee that „optimal“ ordering is obtained
Sometimes a better better block-diagonal structure is obtained by repeatingthe Binary Ordering until there is no change anymore
(c) Prof. Richard F. Hartl
Layout & Design

33. Example Binary Ordering (contd.)
part
machine 6 5 1 3 4 2
value B - 60 D 56 C 39 A E 18 28 25 24 20 7  6
Example Binary Ordering (contd.)
After sorting of rows and columns:
part
machine 6 5 1 3 4 2
value B - 60 D 56 C 39 E A 18 28 26 24 20 7  5
No change of groups in this example
(c) Prof. Richard F. Hartl
Layout & Design

34. Single-Pass Heuristic Considering Capacities (Askin and Standridge)
extension of simple rule with binary sorting:
All parts must be processed in one cell (machines must be duplicated, if off-diagonal elements in matrix)
All machines have capacities (normalized to be 1)
Constraints on number of identical machines in a group
Constraints on total number of machines in a group
(c) Prof. Richard F. Hartl
Layout & Design

35. Example Single-Pass Heuristic (Askin and Standridge)
7 parts, 6 machines
Given matrix of processing times (incl. set up times) for typical lot size of parts on machines
Entries in matrix not just 0/1 for used/not used)
All times as percentage of total machine capacity
At most 4 machines in a group
Not mot than one copy of each machine in each group
(c) Prof. Richard F. Hartl
Layout & Design

36. Example Single-Pass Heuristic (contd.)
part
machine 1 2 3 4 5 6 7
sum
min. # machines A
0.3 -
0.6
0.9 B
0.1
0.7 C
0.4
0.5
1.2  D
0.2
1.4  E F
 1.1 1 1 2 2 1 2
 = 9 machines
(c) Prof. Richard F. Hartl
Layout & Design

37. Example Single-Pass Heuristic (contd.)
At least 9 machines are needed
Not more than 4 machines in a group
 at least 9/4 = 2,25 groups, i.e. at least 3 groups
Step 1: acquire block diagonal structure e.g. using binary sorting
Step 2: build groups
(c) Prof. Richard F. Hartl
Layout & Design

38. Example - Step1: Binary Sorting
For binary sorting treat all entries as 1s.
Result is
part
machine 1 5 7 3 4 6 2 D
0.2
0.3
0.5
0.4 - C A
0.6 F B
0.1 E
solution
(c) Prof. Richard F. Hartl
Layout & Design

39. Step 2: Build Groups Assign parts to groups (in sorting order)
Necessary machines are also included in group
Add parts to group until either
the capacity of some machine would be exceeded, or
the maximum number of machines would be exceeded
(c) Prof. Richard F. Hartl
Layout & Design

40. Example – Step2 table Iteration part chosen group assigned machines
remaining capacity 1 2 5 3 7 4 6 1
D, C, A
D (0,8), C (0,6), A (0,7) 1
D, C, A
D (0,5), C (0,6), A (0,1) 2
D, F, B
D (0,5), F (0,8), B (0,9) 2
D, F, B
D (0,1), F (0,5), B (0,9)
D (0,1), F (0,1), B (0,6), C (0,5) 2
D, F, B, C 3
C, E
C (0,7), E (0,5)
C (0,7), E (0,1), F (0,8), B (0,7) 3
C, E, F, B
(c) Prof. Richard F. Hartl
Layout & Design

41. Results of Example Machines used:
One machine each of types: A, E
Two machines of types: B, D, F
Three machines of type: C
Single-pass heuristic of Askin und Standridge is a simple heuristic  not necessarily optimal solution (min possible number of machines)
Compare result with theoretical min number of machines
(c) Prof. Richard F. Hartl
Layout & Design

42. Maybe reduction possible?!
Results of Example
Maybe reduction possible?!
part
machine 1 2 3 4 5 6 7
sum
min. #
heuristic A
0.3 -
0.6
0.9 B
0.1
0.7 C
0.4
0.5
1.2 D
0.2
1.4 E F
1.1
(c) Prof. Richard F. Hartl
Layout & Design

43. LP for min Number of Machines
Minimize total (or weighted) number of machines used when the number of groups is given
Previous example:
At least 9 machines necessary
Every group has at most M = 4 machines
 at least 3 groups (try 3)
(c) Prof. Richard F. Hartl
Layout & Design

44. Given Data ajk ... capacity of machine k needed for part j
i  I groups (cells)
j  J parts
k  K machines
M maximum number of machines per group
(c) Prof. Richard F. Hartl
Layout & Design

45. Decision Variables 1, if part j is assigned to group i 0, otherwise =
1, if machine of type k is assigned to group i = =
(c) Prof. Richard F. Hartl
Layout & Design

46. LP objective: constraints: each part must be assigned to one group
respect capacity of machine k in group i
not more than M machines in group i
binary variables
(c) Prof. Richard F. Hartl
Layout & Design

47. Solution of LP group parts machines remaining capacity 1 2, 4, 6
B, C, E, F
B (0.4), C (0.2), E (0.1), F (0.4) 2
1, 5
A, C, D
A (0.1), C (0.6), D (0.5) 3
3, 7
B, D, F
B (0.9), D (0.1), F (0.5)
Optimal solution with 10 machines
Theoretical minimum number was 9 machines (not reached because of constraints)
Single pass heuristic used 11 machines
(c) Prof. Richard F. Hartl
Layout & Design

48. Other Approaches for Clustering
Constructive algorithms for sorting:
E.g. „direct clustering“ instead of binary sorting
Use similarity coefficients for clustering
Askin Standridge § 6.4.4
Group analysis after binary ordering
Askin Standridge § 6.4.1
(c) Prof. Richard F. Hartl
Layout & Design

49. Clustering using Similarity Coefficients
Define
ni Number of parts visiting machine i
nij Number of parts visiting machines i and j
Similarity coefficient between machines i and j
Proportion of parts visting machine i that also visit machine j
(c) Prof. Richard F. Hartl
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50. Example for Similarity Coefficients
Machine-part matrix
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51. Group analysis after binary ordering
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52. Example
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