Today, hybrid manufacturing technology has drawn significant interests from both academia and industry due to the capability to make products in a more efficient and productive way. Although there is no specific consensus on the definition of the term ‘hybrid processes’, researchers have explored a number of approaches to combine different manufacturing processes with the similar objectives of improving surface integrity, increasing material removal rate, reducing tool wear, reducing production time and extending application areas. Thus, hybrid processes open up new opportunities and applications for manufacturing various components which are not able to be produced economically by processes on their own. This review paper starts with the classification of current manufacturing processes based on processes being defined as additive, subtractive, transformative, joining and dividing. Definitions of hybrid processes from other researchers in the literature are then introduced. The major part of this paper reviews existing hybrid processes reported over the past two decades. Finally, this paper attempts to propose possible definitions of hybrid processes along with the authors’ classification, followed by discussion of their developments, limitations and future research needs.

Machining is one of the major activities in manufacturing industries and is responsible for a significant portion of the total consumed energy in this sector. Performing machining processes with better energy efficiency will, therefore, significantly reduce the total industrial consumption of energy. In this paper, a framework is presented to validate the introduction of energy consumption in the objectives of process planning for CNC machining. The state of the art in process planning and energy consumption in manufacturing research is utilised as a basis for the framework. A mathematical representation of the logic used is presented followed by two sets of experiments on energy consumption in machining to validate the logic. It is shown that energy consumption can be added to multi-criteria process planning systems as a valid objective and the discussion on using resource models for energy consumption estimation concludes the paper. These experiments represent a part test procedure machining proposal for the new environmental machine standard ISO 14955 Part 3

Reliable machining monitoring systems are essential for lowering production time and manufacturing costs. Existing expensive monitoring systems focus on prevention/detection of tool malfunctions and provide information for process optimisation by force measurement. An alternative and cost-effective approach is monitoring acoustic emissions (AEs) from machining operations by acting as a robust proxy. The limitations of AEs include high sensitivity to sensor position and cutting parameters. In this paper, a novel multi-sensor data fusion framework is proposed to enable identification of the best sensor locations for monitoring cutting operations, identifying sensors that provide the best signal, and derivation of signals with an enhanced periodic component. Our experimental results reveal that by utilising the framework, and using only three sensors, signal interpretation improves substantially and the monitoring system reliability is enhanced for a wide range of machining parameters. The framework provides a route to overcoming the major limitations of AE based monitoring