Automated Cost Estimation of Product Variants - A Tool for Enhanced Producibility
The estimation of product cost is a central activity in the design process. Most companies act in an environment of high competition where the market sets the product price. This, in combination with a focus on satisfying the shareholders demand for return on investment, results in a focus on cost as a constraint. Hence, cost is one of the most fundamental criteria for the evaluation of design proposals (French, 1999). However, the manufacturing cost is often calculated late in the product development process when most details are fixed. This means that cost information feedback often arrives too late to be taken into account. That feedback could otherwise have guided the design towards cost-effective, easily produced solutions. Cost estimation is also commonly a task separated from product design and performed by cost accountants. This work distribution requires resources and can be afflicted with loss of information, leading to low quality in the estimations. This subdivision is also not efficient in the search for the best solution, where a number of variant designs are to be evaluated and compared in a short time. When different courses of action are to be evaluated, small changes in customer requirements, product design and production properties have to be handled with caution. Even seemingly small changes can result in undesired effects, such as: low level of conformability with the production system, highly increased cost, and extended manufacturing lead-time.
The fact that application software is getting more and more adaptable enlarges the possibility of in-house-developed cost estimation systems that can be used as a means for enhanced producibility. This calls for systematic methods for system development that ensure system functionality, quality and longevity.
This work has resulted in a framework supporting the development of automated systems encompassing the entire workflow: the design of the product variant, the process planning, the cost estimation, the analysis of the effects on the producibility metrics and, finally, the selection of the most favourable course of action. The framework consists of: the procedure for system development, the definition of information models, the clarification of the relations between information models, the guidelines for parametric solid models, and the means for automated process planning and cost estimation.
The framework has been used when implementing an industry demonstrator. The system can act as a means for enhanced producibility. Different product, production and cost aspects can be studied through the use of multi-objective optimisations, sensitivity analysis, and what-if scenarios enabled by the system. The system can serve as a decisions tool that enables the evaluation of different courses of action in the early stages in the development of product variants. This can imply better decisions and, in the long run, a better company understanding and awareness of the relationships between the product properties, the manufacturing resources requirements/constraints, the manufacturing processing, the cost structure, and the cost level.
Design for Producibility