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Production flow analysis

In operations management and industrial engineering, production flow analysis refers to methods which share the following characteristics:

  1. Classification of machines
  2. Technological cycles information control
  3. Generating a binary product-machines matrix (1 if a given product requires processing in a given machine, 0 otherwise)

Methods differ on how they group together machines with products. These play an important role in designing manufacturing cells.

Rank order clustering edit

Given a binary product-machines n-by-m matrix  , rank order clustering[1] is an algorithm characterized by the following steps:

  1. For each row i compute the number  
  2. Order rows according to descending numbers previously computed
  3. For each column p compute the number  
  4. Order columns according to descending numbers previously computed
  5. If on steps 2 and 4 no reordering happened go to step 6, otherwise go to step 1
  6. Stop

Similarity coefficients edit

Given a binary product-machines n-by-m matrix, the algorithm proceeds[2] by the following steps:

  1. Compute the similarity coefficient   for all with   being the number of products that need to be processed on both machine i and machine j, u comprises the number of components which visit machine j but not k and vice versa.
  2. Group together in cell k the tuple (i*,j*) with higher similarity coefficient, with k being the algorithm iteration index
  3. Remove row i* and column j* from the original binary matrix and substitute for the row and column of the cell k,  
  4. Go to step 2, iteration index k raised by one

Unless this procedure is stopped the algorithm eventually will put all machines in one single group.

References edit

  1. ^ King, J. R., Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm, International Journal of Production Research, Vol.18 1980 http://www.tandfonline.com/doi/abs/10.1080/00207548008919662#.UeAI5eGLe1E
  2. ^ Adapted from MCauley, Machine grouping for efficient production, Production Engineer 1972 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04913845

production, flow, analysis, operations, management, industrial, engineering, production, flow, analysis, refers, methods, which, share, following, characteristics, classification, machines, technological, cycles, information, control, generating, binary, produ. In operations management and industrial engineering production flow analysis refers to methods which share the following characteristics Classification of machines Technological cycles information control Generating a binary product machines matrix 1 if a given product requires processing in a given machine 0 otherwise Methods differ on how they group together machines with products These play an important role in designing manufacturing cells Rank order clustering editGiven a binary product machines n by m matrix bip displaystyle b ip nbsp rank order clustering 1 is an algorithm characterized by the following steps For each row i compute the number p 1mbip 2m p displaystyle sum p 1 m b ip 2 m p nbsp Order rows according to descending numbers previously computed For each column p compute the number i 1nbip 2n i displaystyle sum i 1 n b ip 2 n i nbsp Order columns according to descending numbers previously computed If on steps 2 and 4 no reordering happened go to step 6 otherwise go to step 1 StopSimilarity coefficients editGiven a binary product machines n by m matrix the algorithm proceeds 2 by the following steps Compute the similarity coefficient sij nij nij u displaystyle s ij n ij n ij u nbsp for all with nij displaystyle n ij nbsp being the number of products that need to be processed on both machine i and machine j u comprises the number of components which visit machine j but not k and vice versa Group together in cell k the tuple i j with higher similarity coefficient with k being the algorithm iteration index Remove row i and column j from the original binary matrix and substitute for the row and column of the cell k srk max sri srj displaystyle s rk max s ri s rj nbsp Go to step 2 iteration index k raised by oneUnless this procedure is stopped the algorithm eventually will put all machines in one single group References edit King J R Machine component grouping in production flow analysis an approach using a rank order clustering algorithm International Journal of Production Research Vol 18 1980 http www tandfonline com doi abs 10 1080 00207548008919662 UeAI5eGLe1E Adapted from MCauley Machine grouping for efficient production Production Engineer 1972 http ieeexplore ieee org stamp stamp jsp arnumber 04913845 Retrieved from https en wikipedia org w index php title Production flow analysis amp oldid 1212282957, wikipedia, wiki, book, books, library,

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