Abstract
Industrial lubrication involves the use of significant amounts of lubricants. How lubricants are manufactured, used, applied and disposed of, has a direct impact on the efficient use of energy in the relevant industry sector. The primary drivers for the use of lubricants are reduction of friction and minimisation of wear. Any new developments that can contribute to these, are critical for survival in a highly competitive environment and should be an ongoing activity. In industrial operations different lubrication requirements will depend on whether the equipment is stationary with or without moving contacts (transformers, gearboxes, mills, turbines, cutting operations, etc.). The selection and use of high-performance lubricants will depend on the origin and type of the base oil, (mineral-oil based, synthetic or plant-oil). The quantities of lubricants used in various operations are affected by the design of the system, (enclosed, once-through or alternative application techniques). Manufacturing, use, disposal and re-processing of lubricants can all have a significant impact on the environment and the extent of this needs to be considered throughout. Before a lubricant can be put to use, its quantitative friction and wear characteristics need to be determined. Determination of these characteristics can seldom be performed in the application environment, since the ideal, lubricated, operating environment is designed for minimal (ideally zero) wear, while a laboratory-based performance test needs to produce quantitative results within a short time. For this reason, laboratory test configurations and operating conditions can often end up to be extreme and far removed from reality. Validating laboratory test results and relating these to the application environment is therefore an important step towards the quantification of friction and wear behaviour. In this presentation an inclusive methodology is proposed whereby the optimal lubricant to use in a given application can be evaluated, compared and selected from an energy-efficiency and environmentallyconscious perspective using available information, supplemented by appropriate in-line process measurements and representative models, similar to their use in model-based control systems.