A psycho-clonal-algorithm-based approach to the solve operation sequencing problem in a CAPP environment

Pertaining to the intricacies involved in the formulation of an optimal process planning system, operation sequencing has been recognized as a complex and crucial task to be accomplished. The operation sequencing problem determines the preferred order to perform a set of selected operations that satisfies the precedence constraints along with the satisfaction of the optimization goals. In general, the problem is characterized by its combinatorial nature and complex precedence relations that make it computationally complex. A psycho-clonal-algorithm-based approach has been proposed in this paper to solve optimally the operation sequencing problem. The objective function has been made more comprehensive for the parts types of varying complexities. This approach is an extension of the artificial immune system (AIS) approach and inherits its characteristics from the Maslow's need hierarchy theory related to psychology. The various need levels present in the algorithm help in maintaining the viability of solution, whereas the path towards optima is revealed by the trait of affinity maturation. Effectiveness of the algorithm is authenticated by solving the problems of varying complexities cited in the literature and comparing its performance with other established metaheuristic approaches

The evaluation of a novel haptic machining VR-based process planning system using an original process planning usability method

This thesis provides an original piece of work and contribution to knowledge by creating a new process planning system; Haptic Aided Process Planning (HAPP). This system is based on the combination of haptics and virtual reality (VR). HAPP creates a simulative machining environment where Process plans are automatically generated from the real time logging of a user’s interaction. Further, through the application of a novel usability test methodology, a deeper study of how this approach compares to conventional process planning was undertaken. An abductive research approach was selected and an iterative and incremental development methodology chosen. Three development cycles were undertaken with evaluation studies carried out at the end of each. Each study, the pre-pilot, pilot and industrial, identified progressive refinements to both the usability of HAPP and the usability evaluation method itself. HAPP provided process planners with an environment similar to which they are already familiar. Visual images were used to represent tools and material whilst a haptic interface enabled their movement and positioning by an operator in a manner comparable to their native setting. In this way an intuitive interface was developed that allowed users to plan the machining of parts consisting of features that can be machined on a pillar drill, 21/2D axis milling machine or centre lathe. The planning activities included single or multiple set ups, fixturing and sequencing of cutting operations. The logged information was parsed and output to a process plan including route sheets, operation sheets, tool lists and costing information, in a human readable format. The system evaluation revealed that HAPP, from an expert planners perspective is perceived to be 70% more satisfying to use, 66% more efficient in completing process plans, primarily due to the reduced cognitive load, is more effective producing a higher quality output of information and is 20% more learnable than a traditional process planning approach