Influence on Phosphate Pretreatments and Organic Coatings on the Sport Welding Characteristics of Zinc Coated Steels

Chatterjee, Kaushik

doi:10.4271/982360

Cited by 1 publication

(3 citation statements)

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“…Phosphate coatings will allow current flow up to a certain thickness, as shown by Chatterjee. 17 It was concluded that increasing the thickness of the phosphate coating decreased the current required to produce a satisfactory weld, due to the higher resistance of the coating layer (Fig. 7).…”

Section: Behaviour Of Interfacial Resistance During Weldingmentioning

confidence: 98%

“…On the other hand, a zinc coated steel with a polyurethane topcoat of thickness 3 mm permitted current flow; in this case, flow was aided by the presence of metallic zinc particles in the polyurethane coating. However, increasing the coating thickness to 7 mm resulted in 17,18 erratic results due to large differences in surface resistance (Fig. 7a).…”

Section: Behaviour Of Interfacial Resistance During Weldingmentioning

confidence: 99%

“…Early work suggested that melting coincided with the peak value of resistance, although present understanding is that initial melting occurs at some a organic coated; b phosphated steel 7 Influence of coating thickness on initial contact resistance and electrode life (no. of welds) when spot welding organic coated and phosphated coated steel (Chatterjee 17 )…”

Section: Dynamic Resistance Relationshipmentioning

confidence: 99%

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Review of resistance spot welding of steel sheets Part 1 Modelling and control of weld nugget formation

Williams¹,

Parker²

2004

International Materials Reviews

167

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Resistance spot welding is the principal method of welding sheet steel products. In practice, the manufacture of welds of acceptable quality depends on the definition of optimum welding parameters and the implementation of suitable controls to ensure constant weld quality over a long production run. The ability to make a weld is best defined by a weldability lobe outlining the available manufacturing tolerances between minimum and maximum limits. Both two-and three-dimensional weldability lobes exist defined in terms of weld time, welding current and electrode force. Production variables influencing weld growth are discussed, particularly the effect of electrode diameter. The importance of welding machine characteristics relative to weld growth is highlighted. In particular, the rigidity of the machine coupled with the weight and frictional effects developed in the electrode head assembly are shown to be important factors influencing weld growth. Also important are the electrical characteristics of the machine, including transformer configuration current waveform and current 'off' time in the nonconducting part of the waveform. A reliable control philosophy is an essential requirement of any inprocess feedback system if high quality spot welds are to be produced in high volume. Various model simulations indicate that changes, with time, in electrode/sheet and sheet/sheet interfacial resistances control weld nugget formation and growth. The relative contributions of these resistances are discussed. Heat generation and temperature distribution in the weld are determined by the current and force distribution across these interfaces. One-, two-and three-dimensional models have been developed to describe the temperature distribution in the weld zone and weld nugget growth. These models have limited application due to inadequate input data to describe the transient conditions appertaining in the weld zone. Current waveform, inductance effects, and friction/rigidity of the electrode head assembly, are not considered. Neural networks and fuzzy logic control have shown promise in classifying weld quality into predetermined groupings. The way forward is to adopt a multidisciplinary approach, taking into account the various interactions between the thermal, electrical, mechanical and metallurgical phenomena developed during the welding process. Models describing these phenomena should be interlinked to simulate heat generation and growth in the weld zone. The resulting model could be coupled with experimentally developed trends to optimise inputs to a neural network, the output of which is used, through a fuzzy logic controller, to take appropriate corrective action to ensure the required weld quality. It is stressed that any mathematical simulation or control system must take into account changes that occur at the welding electrodes as a consequence of electrode wear. The latter are discussed in Part 2 of this review.

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Section: Behaviour Of Interfacial Resistance During Weldingmentioning

confidence: 98%

Section: Behaviour Of Interfacial Resistance During Weldingmentioning

confidence: 99%

Section: Dynamic Resistance Relationshipmentioning

confidence: 99%

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