An overview of function block enabled adaptive process planning for machining. (April 2015) - Wang, Lihui
Highlights: This paper provides a systematic overview of distributed process planning research. It combines event-driven function blocks to CNC control for adaptive machining. It features detailed treatment of processing algorithms and procedures. A large amount of diagrams are used for the ease of understanding. The results of research findings are validated by case studies. Abstract: Small- and medium-sized enterprises (SMEs) in job-shop machining are experiencing more shop-floor uncertainties today than ever before, due to multi-tier outsourcing, customised product demands and shortened product lifecycle. In a fluctuating shop floor environment, a process plan generated in advance is often found unsuitable or unusable to the targeted resources, resulting both in wasted effort spent in early process planning and in productivity drop when idle machines have to wait for operations to be re-planned. Consequently, an adaptive process planning approach is in demand. Targeting shop-floor uncertainty, the objective of this research is to develop a novel adaptive process planning method that can generate process plans at runtime to unplanned changes. This paper, in particular, presents an overview of adaptive process planning research and a new methodology, including two-layer system architecture, generic supervisory planning, machine-specific operation planning, and adaptive setup planning. Particularly, function blocks are introduced as a core enabling technology to bridge the gap between computer systems and CNC systems for adaptive machining.