3 Group Technology / Cellular Manufacturing (Inselfertigung)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Optiz Classification System (c) Prof. Richard F. Hartl Layout & Design

Optiz in More Detail 2 2 4 0 0 (c) Prof. Richard F. Hartl Layout & Design

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

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

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

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

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

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 0101002 = 22 + 24 = 20 20 + 21 + 23 + 25 = 43 20 + 22 + 23 + 24 = 29 20 + 21 + 25 = 35 21 + 22 = 6 25 32 24 16 23 8 22 4 21 2 20 1 (c) Prof. Richard F. Hartl Layout & Design

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: 6-5-1-3-4-2 22 = 4 21 = 2 20 = 1 20+21+22=7 23 + 24 = 24 21 + 22 = 6 22 + 24 = 20 20+23+24=25 22+23+24=28 (c) Prof. Richard F. Hartl Layout & Design

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 Layout & Design

Example for Similarity Coefficients Machine-part matrix (c) Prof. Richard F. Hartl Layout & Design

Group analysis after binary ordering (c) Prof. Richard F. Hartl Layout & Design

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