FMEA & FTA

failureclass

Determines the class of a failure according to its severity and occurence rating

Collection failureclass(Collection severity, Collection occurence, Collection designfailure=nothing, Object critical_s=9, Object significant_s=5, Object significant_o=4, Object =4)

  • severity: is the severity rating
  • occurence: is the occurence rating
  • designfailure: is the critical severity
  • critical_s: is the significant severity
  • significant_s: is the significant occurence
  • significant_o:
  • :

faulttree

Collection faulttree(Collection fltnet, Collection dir=1)

  • fltnet:
  • dir:

fmbestaction

Looks for the best action attached to failure causes

Object fmbestaction(Collection initial, Collection attribute, Object level=nothing, Object impstate=nothing, Object impdate=nothing)

  • initial: is the vector containing the current (initial) values
  • attribute: is the name of the task attribute containing the improved value
  • level: is the level that marks failure causes in the fault tree
  • impstate: is the implementation statues
  • impdate: is the implementation date

fmeaform

Collection fmeaform(Collection functions, Collection fct2flt, Collection fltnet, Collection format=0)

  • functions:
  • fct2flt:
  • fltnet:
  • format:

fmearisk

Collection fmearisk(Collection s, Collection o, Collection riskmatrix, Collection faultnet)

  • s:
  • o:
  • riskmatrix:
  • faultnet:

fmmappedrating

Maps a rating given for one side of a matrix to the other side of the matrix. Each row in the resulting vector computes to the maximum of all values in the rating vector which are connected to the row by the matrix.

Object fmmappedrating(Collection matrix, Collection rating, Collection maximize=1, Collection mapmode=1, Collection =1, Collection =1)

  • matrix: The FMEA matrix
  • rating: A vector of ratings for the input side of the matrix
  • maximize:
  • mapmode:
  • :
  • :

fmmappedratingex

Maps a rating given for one side of a matrix to the other side of a second matrix. The two matrices have to have one common dimension. Each row in the resulting vector computes to the maximum of all values in the rating vector which are connected to the row by the matrix.

Object fmmappedratingex(Collection matrix1, Collection matrix2, Collection rating, Collection opt)

  • matrix1: the first matrix
  • matrix2: the second matrix
  • rating: a vector of ratings for the input side of the matrix
  • opt: if true, the function takes the minimum of all connected values, otherwise the maximum

fmnetfaulttype

Collection fmnetfaulttype(Collection net)

  • net:

fmnetrating

Looks up the worst rating of all effects/causes connected to a failure by a automatrix (failure net)

Object fmnetrating(Collection source, Collection net, Object level, Object steps=1)

  • source: is the vector containing the ratings
  • net: is the failure net matrix
  • level: is the fault type index
  • steps: is the level of indirection for the lookup

fmrating

Maps a rating given for one side of a matrix to the other side of a second matrix. The two matrices have to have one common dimension. Each row in the resulting vector computes to the maximum of all values in the rating vector which are connected to the row by the matrix.

Object fmrating(Collection matrix, Collection condition, Collection rating, Collection default)

  • matrix: the first matrix
  • condition: the second matrix
  • rating: a vector of ratings for the input side of the matrix
  • default: if true, the function takes the minimum of all connected values, otherwise the maximum

fmrisk

Collection fmrisk(Collection s, Collection o, Collection d, Collection type=nothing, Collection design_riskmatrix=nothing, Collection product_riskmatrix=nothing, integer mode=risk_matrix, integer lo=250, integer hi=500)

  • s:
  • o:
  • d:
  • type:
  • design_riskmatrix:
  • product_riskmatrix:
  • mode:
  • lo:
  • hi:

fta

Evaluates probabilities for faults in a fault tree analysis

Object fta(Collection tree, Collection operators, Collection probabilities, Object total)

  • tree: a tree of faults
  • operators: a vector or a property containing the boolean operators. Items with a operator equal to 1, probabilities of the child items will be multiplied. For all other values of the operator, the child items will be summed up.
  • probabilities: a vector or property containing the probabilities of the leaf items
  • total: a scalar variable to receive the total probability of the whole tree

haccp

Collection haccp(Collection products, Collection ps, Collection rs, Collection cr, Collection cp, Collection selected=nothing)

  • products:
  • ps:
  • rs:
  • cr:
  • cp:
  • selected:

mcsimportance

Collection mcsimportance(Collection source, Collection probabilities)

  • source:
  • probabilities:

mcsprobability

Collection mcsprobability(Collection source, Collection probabilities, Object inverse=false, Collection p_default=nothing)

  • source:
  • probabilities:
  • inverse:
  • p_default:

mcssensitivity

Collection mcssensitivity(Collection source, Collection best, Collection worst)

  • source:
  • best:
  • worst:

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