SIMULATION MODELING FOR QUALITY AND PRODUCTIVITY IN STEEL CORD MANUFACTURING

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SIMULATION MODELING FOR QUALITY AND
PRODUCTIVITYIN STEEL CORD MANUFACTURING    
 
 
Can Hulusi Türkseven, Gürdal Ertek   Faculty of
Engineering and Natural Sciences Sabanci
UniversityOrhanli, Tuzla, 34956Istanbul, Turkey
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• Steel cord manufacturing system
• Distinguishing characteristics
• Various production settings
• Applicability of simulation as a management
  decision support tool

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Steel Cord Manufacturing

• Main reinforcement material in manufacture of
  steel radial tires
• Continuous processes where wire semi-products are
  stored on discrete inventory units (spools)

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Steel Cord Manufacturing

• Special considerations applicable to a narrow
  scope of industries
• (Ex the reversal of the wire wound on the
  spools at each bunching operation)
• Cable manufacturing (electric/energy/fiber-optic)
• Nylon cord manufacturing
• Copper rod manufacturing

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The Manufacturing Process

• Steel rod wire, is thinned into filaments
  which are used in successive bunching operations
  to construct the steel cord final products.
• Intermediate wire products are wound onto spools
  of varying capacities.

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The Manufacturing Process
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The Manufacturing Process

• Payoff filament coming out of wet drawing
• Core bunched wires entering next bunching
  operation
• Take-up output of each bunching operation
• Construction the final steel cord product
• The take-up becomes the core for the
  following bunching operation.

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The Manufacturing Process
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Cross-section of a Steel Cord
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Change-overs

• When run-out of a spool
• Change-over Setup performed by a skilled
  operator to feed the next spool
• When the take-up spool is completely full
  Change-over of take-up
• Wire typically wasted at every change-over
• Tying of changed spools results in a knot.

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Change-overs for (3915)
Change-overs for (39)
Change-overs for (3x1)
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Wire Fractures

• Wire fractures, random breaks of the wire due
  to structural properties
• Uncontrollable
• May also result in considerable number of
  additional knots.
• Cause?
• previous fractures?
• the locations of previous knots?
• core and payoff lengths?
• Statistical analysis of the data did not suggest
  any patterns

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Rejected Spools

• Tire manufacturers prefer that the spools with
  the final cuts of steel cords contain no knots at
  all.
• Rejected spools Final spools that contain
  knots
• Management objective to decrease the number of
  knots and the number of rejected spools

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Research Motivation

• Optimal spool lengths for each bunching
  operation
• Minimize rejected spools
• Such that spool lengths are within a certain
  percentage of the current spool lengths

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Unique Challanges

• Knots locations are reversed at every spool
  change
• When a wound spool of length h with knot
  locations (k1, k2, ..., kn) is fed into the
  bunching operation, the unwinding results in knot
  locations (h-kn, ..., h-k2, h-k1).

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Simulation Model

• Programmed in C (MS Visual C)
• GUI with Borland Delphi
• 1 minute running time for a 10 ton production
  schedule (10 simulation experiments)
• Why general-purpose language?
• There are complexities (ex reversing of knot
  locations at bunching operations) that would be
  next to impossible to reflect using spreadsheets
  and would have to be custom-programmed if a
  simulation language or modeling software were
  used.

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Simulation Model

• Input Parameters
• Usage ratios
• Wire densities
• Fracture ratios
• Machine characteristics and quantities
• Knotting time
• Final spool length
• Decision Variables
• Spool lengths

• Outputs
• Number of accepted spools
• Number of rejected spools
• Rejected wire length
• Throughput time

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Results

• Accurate estimation of the system performance
  measures
• Validated with historical data
• Accuracy can be increased through increasing
  simulation run lengths and number of simulations

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Conclusions / Suggestions

• Some of the current operational rules used by
  operators are proven to be useful
• Ex Performing a take-up change-over if only a
  few hundred meters have remained on the bunching
  operation
• Feasibility of implementing dynamic control
  policies can be investigated

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Future Work

• Machine break-downs
• Dynamic spool selection
• Feasibility of machinery
• Simulation optimization
• Generic modeling environment to analyze systems
  with similar manufacturing characteristics