The Generation of Machining Process Plans Using a Haptic Virtual Reality System

Abstract

Computer Aided Process Planning (CAPP) links the design and manufacture of a machined product defining how the product itself will be manufactured. Decisions made during this phase can have a significant impact on product cost, quality and build time; therefore, it is important that process planners have intuitive tools to aid them in effectively creating process plans. However, in spite of being a strong research area, the actual application of CAPP systems in industry is limited and new modern 3D digital tools in this area have not been researched to any real degree. Traditional process planning is carried out either manually or via a CAPP interface and, from this activity, a set of instructions are generated for the shop floor. However, these CAPP processes can be time consuming and subject to inconsistencies. Current research seeks to automate the generation of work instructions by using previous designs and/or artificial intelligence. However, due to the complexity of manufacturing a wide range of products, the limited range of tools available and differing skills of the workforce, it is difficult to reach a generic solution for practical application. The novel pilot study given in this paper presents one of the first pieces of research comparing and contrasting a traditional manual approach to machined part process planning with an alternative haptic virtual environment. Within this, an operator can simulate the machining of a simple part using a virtual drilling and milling process via a haptic routing interface. All of the operator input is logged in the background with the system automatically generating shop floor instructions from this log file. Findings show that users found the virtual system to be more intuitive and required less mental workload than traditional manual methods. Also their perceptions for the future were that they would need less support for learning and would progress to final planning solutions more quickly.