3 Group Technology / Cellular Manufacturing

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. 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 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 specifiedfamilyof parttypes (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 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 • classicalGT cell • GT center 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). Layout & Design

7. classicalGT 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). 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). Layout & Design

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

10. Typical Manufacturing Cell (2) • Example with 3 workers • Also u-shaped 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 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 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 Layout & Design

14. Items That Are Made with Same Equipment 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 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.) 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) 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. 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. 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 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 Layout & Design

22. Optiz Classification System Layout & Design

23. Optiz in More Detail 0 0 2 2 4 Layout & Design

24. 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. Layout & Design

25. 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. Layout & Design

26. 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} Layout & Design

27. 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. decreasingbinary numbers • Sort columns w.r.t. decreasingbinary numbers Layout & Design

28. Binary Ordering • Sort rows w.r.t. decreasing binary numbers • New ordering of machines: B – D – C – A - E 0101002 = 22 + 24 = 20 20 + 21 + 23 + 25 = 43 20 + 22 + 23 + 24 = 29 20 + 21 + 25 = 35 21 + 22 = 6 24 16 21 2 25 32 20 1 23 8 22 4 Layout & Design

29. Binary Ordering • Sort columns w.r.t. decreasing binary numbers 24 = 16 23 = 8 • New ordering of parts: • 6-5-1-3-4-2 22 = 4 21 = 2 20 = 1 20+21+22=7 20+23+24=25 23 + 24 = 24 21 + 22 = 6 22 + 24 = 20 22+23+24=28 Layout & Design

30. 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 • 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 Layout & Design

31. 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 Layout & Design

32. Example Binary Ordering (contd.) • After sorting of rows and columns: • No change of groups in this example Layout & Design

33. 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 Layout & Design

34. 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 Layout & Design

35. Example Single-Pass Heuristic (contd.) 1 1 2 2 1 2  = 9 machines Layout & Design

36. 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 Layout & Design

37. Example - Step1: Binary Sorting • For binary sorting treat all entries as 1s. • Result is solution Layout & Design

38. 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 Layout & Design

39. Example – Step2 table 1 D, C, A D (0,8), C (0,6), A (0,7) D (0,5), C (0,6), A (0,1) 1 D, C, A D (0,5), F (0,8), B (0,9) D, F, B 2 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 Layout & Design

40. 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 Layout & Design

41. Results of Example Maybe reduction possible?! Layout & Design

42. 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) Layout & Design

43. 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 Layout & Design

44. Decision Variables 1, if part j is assigned to group i 0, otherwise 1, if machine of type k is assigned to group i 0, otherwise = = Layout & Design

45. 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 binary variables Layout & Design

46. Solution of LP • Optimal solution with 10 machines • Theoretical minimum number was 9 machines (not reached because of constraints) • Single pass heuristic used 11 machines Layout & Design

47. 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 Layout & Design

48. 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 Layout & Design

49. Example for Similarity Coefficients • Machine-part matrix Layout & Design

50. Group analysis after binary ordering Layout & Design