To increase the competitiveness of European industry by advancing the technical acceptability of laser welding over a range of manufacturing industries, the following areas were investigated: weld properties; process sensors; expert system for control of laser welding operations. For laser welding of industrial carbon/manganese components, thermal cycle effects as well as the compositional effects were investigated and quantified. In the case of thermal cycle effects, mathematical models were elaborated which will determine heat affected zone (HAZ) width and maximum hardness. An alternative charpy test was proposed in order to overcome the problems related to weldmetal/parent material strength mismatch. For laser welding of industrial components of stainless steel and titanium, investigations into the thermal cycle-, compositional and geometric effects were carried out to reduce the microfissures in the weld metal. For stainless steel and titanium alloys, optimized welding procedures were developed and verified against tests of mechanical properties. The design expert system (DES) system will predict laser welding parameters for butt-welding of steels. The DES uses criteria of maximum hardness, maximum HAZ width and full penetration in recommending the initial parameters to produce the weld in question. The maximum hardness of the weld HAZ is predicted with an accuracy of 10 %. With respect to sensors for weld penetration and defects monitoring, two different ultrasonic systems were developed. The U2 sensor is a prototype ultrasonic sensing system capable of determining the liquid/solid interface and therefore the width of the weld pool used to monitor the laser welding process on-line. The U3 sensor for on-line defect monitoring of laser welds consists of a pair of ultrasonic transducers connected to an ultrasonic instrument, the P-scan equipment, using the Time-of-Flight Diffraction technique. The prototype monitoring and control expert system (MCES)controls the laser welding process on-line using a number of sensors measuring several dynamic parameters of the process.