SIMULATION MODELING FOR QUALITY AND PRODUCTIVITYIN STEEL CORD MANUFACTURING

  

 

 Can Hulusi Türkseven, Gürdal Ertek

 Faculty of Engineering and Natural Sciences

Sabancı UniversityOrhanli, Tuzla, 34956

Istanbul, Turkey

• Steel cord manufacturing system

• Distinguishing characteristics

• Various production settings

• Applicability of simulation as a management decision support tool

Steel Cord Manufacturing

• Main reinforcement material in manufacture of steel radial tires

• Continuous processes where wire semi-products are stored on discrete inventory units (“spool”s)

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

The Manufacturing Process

• “Steel rod wire”, is thinned into “filament”s which are used in successive bunching operations to construct the “steel cord” final products.

• Intermediate wire products are wound onto spools of varying capacities.

The Manufacturing Process

Dry drawing I & II

Annealing

Cold air bath

Cold water bath

Acidic solution

Basic solution

Spiralling

Bunching

Wet drawing

Copper plating

Zinc plating

Packaging

to Copper plating

Steel wire rod

Filament

Steel cord

Begin Production

End production

RE

SEA

RC

H F

OC

US

RE

SEA

RC

H F

OC

US

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.

The Manufacturing Process

Bunching 1 Bunching 2 Bunching 3

Bunching 1 Bunching 2 Bunching 3

Bunching 1 Bunching 2 Bunching 3

Bunching 1 Bunching 2

Bunching 2

Bunching 3

Bunching 3

Bunching 3

CASE 3CASE 3

CASE 2CASE 2

CASE 1CASE 1

Cross-section of a Steel Cord

8

Steel wire rod (raw material)

Filament (payoff)

Final product(construction) 3+8+12x0.2+1+1

3+8x0.2 Bunched steel wire

3x0.2 Bunched steel wire

1

2

8

7

10

11

5

4

6

39

12

5 4

1

2

36

7

2 13

Spiral Spiral filamentfilament

Bunching 2 Bunching 3 & Spiralling

Bunching 1

Draw

ing

Operation

Core

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”.

Change-overs for (3x1)

Change-overs for (3+9+15)

Change-overs for (3+9)

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

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

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

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).

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.

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

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

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

Future Work

• Machine break-downs • Dynamic spool selection • Feasibility of machinery• Simulation optimization

• Generic modeling environment to analyze systems with similar manufacturing characteristics