Thermal sprayed coatings are widely used for industrial applications. One of the main characteristics that have to be evaluated in a coating is its microstructure that finally determines the coating performance. Several techniques and processes are available for coatings deposition and new materials have been incorporated in the long list of the available ones. Therefore, since microstructure is a key factor to be evaluated, its preparation has to follow some rules in order to inhibit incorrect statements that can arise from wrong interpretation of an incorrect sample preparation. In this work, a series of distinctive materials are thermally sprayed onto low carbon steel substrates. The metallographic preparation of samples for the different coatings is presented and the effects of correct or wrong sample preparation are discussed and correlated to coating microstructure and process characteristics. The coatings were applied by Air Plasma Spray (APS) and Electric Arc Spray.

The economic efficiency of spraying a frequently changing spectrum of parts is strongly dependent on the costs of planning the spray process. In many cases, the robot program for coating a three-dimensional surface is generated directly on the control unit computer. Programming results in costly downtime. At IWS, a technology for off-line programming of robots and CNC systems for thermal spraying (TS) and laser cladding (LC) was developed. Coating programs are developed using CAD data from a workpiece and checked with simulation software. All steps are accomplished off-line without influencing ongoing production. Off-line programming of spray processes for three-dimensional surfaces enables substantial time savings to be realized, more so with increasing part complexity. These programs enable a constant spray distance and traverse speed as well as a permanent spray angle of 90° to the substrate to be achieved.

The Hitachi MaxJet II is a unique multi-purpose combustion gun. It can be used for spraying wire but it also has the capability to spray multiple materials via-powder and powder cord form. The equipment operates using commonly available gases: compressed air, Oxygen and Propane or Mapp gas. It requires no major facility cost since it uses only a 35 cfm air compressor and 115 volt power supply. Safety is assured with a safety purge system, separation of electrical and gases systems and flash back arresters. The small compact system weighs less than two hundred pounds, which makes it easily movable for on site work. It’s low capital investment and high quality coatings with low porosity and excellent bond strengths. The electronic pusher type wire feed provides consistent feed rates for a large variety of wires and wire sizes (1/16”, 1/8”, and 3/16”). The spray gun weighs only three pounds and can be mounted on a robot or used for hand spray applications. It functions well in a shop environment or onsite spraying of bridge components.

The number of parameters and noise factors that influence the plasma spraying process is huge, with over 200 known. Today, only a few parameters such as gas flow rate, current, voltage, spraying distance and substrate roughness can be controlled. In recent years, several particle diagnostic systems have been developed, which give the chance to control processes much better than at present. These techniques are now close to being introduced in industrial applications. In addition to the in-flight particle properties, the surface temperature of the substrate has a large influence on the coating quality. Statistical methods are widely used to quantify the influences of the particle and substrate characteristics. Neural networks provide a greater capability to analyse particle characteristics and substrate temperature data for coating quality control. In this work, the analysis of comprehensive process data and coating characteristics using neural networks is investigated and compared to established design of experiments (DOE) statistical methods.