A cost-effective knowledge-based reasoning system for design for automation.
Design for assembly automation (DFAA) is an important part of the concurrent engineering strategy for reduction of product manufacturing costs and lead times. An intelligent knowledge-based system (KBS) for design for automation and early cost modelling within a concurrent engineering environment has been developed. This paper focuses upon the development of the design for an assembly automation system. The system framework encompasses an extensive knowledge-based reasoning system, a CAD system, a design analysis for automation module, a design improvement suggestion module, and a user interface. The development process of the system involved three main stages: creating the KBS, developing the design improvement module, and integrating the KBS with the CAD system. The developed system has the capability to: (a) select the most economic assembly technique for the product at an early design stage; (b) estimate the assembly time and cost for manual, automatic, and robotic assembly methods; and (c) analyse the product design for automation and provide the designers with design improvement suggestions of a product to simplify assembly operations without any compromise of the product functionality. The above capabilities of the system have been demonstrated and validated through a real case study.
This output presents an approach to design for automation in order to shorten assembly costs and cycle times. Results have been tested on a pilot study at Ericsson (UK) using an Ericsson Mobile Phone Handset and a Scientific Calculator (Ericsson Mobile Communications Ltd, Lawn Rd Industrial Estate, Carlton-in-Lindrick, Worksop, S81 9LB - Shaun Hopkinsonemail@example.com). The pilot study showed Improvements of around 7-10% in assembly costs and cycle times.
Citation : Shehab, E. M. and Abdalla, H. (2006) A cost-effective knowledge-based reasoning system for design for automation. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 220(5), pp. 1-15.
ISSN : 0954-4054
Research Group : Manufacturing Research