Timothy W. Simpson, Assistant Professor, joint appointment in Mechanical & Nuclear Engineering, and Member ASME, Karthikeyan Umapathy, Graduate Research Assistant, Jyotirmaya Nanda, Graduate Research Assistant, Sachin Halbe, Graduate Research Assistant, Barry Hodge, Managing Engineer
Product customization is a value-added activity that can significantly increase sales by increasing customer satisfaction. Many companies are using product platforms to increase product variety and customization while reducing development costs and time-to-market. While flooding the market with a variety of products may satisfy some customers by providing a substitute for customization, variety is not customization . This subtle, yet important, distinction between variety and customization motivates the need for investigating technologies to facilitate customer involvement during the product realization process, and our focus in this paper is on web-based platform customization strategies enabled by recent advances in information technology. Towards that end, we describe the development of an interactive web-based platform customization framework as an extension of product family design and present a prototype that has been created as part of on-going research with a company that produces customized refiner plates for pulp and paper processing. While the utility of the proposed web-based framework is demonstrated in the context of customizing a refiner plate design, the proposed framework is applicable to a variety of engineered products and enhances customer interaction during the product realization process while reducing design and manufacturing lead-time for custom orders.
Topics: Design, Manufacturing, Plates (structures), Databases, Computer-aided design, Pulp
Charles D. McAllister, Assistant Professor,, Timothy W. Simpson, Assistant Professor, Mem. ASME,
In this paper, we introduce a multidisciplinary robust design optimization formulation to evaluate uncertainty encountered in the design process. The formulation is a combination of the bi-level Collaborative Optimization framework and the multiobjective approach of the compromise Decision Support Problem. To demonstrate the proposed framework, the design of a combustion chamber of an internal combustion engine containing two subsystem analyses is presented. The results indicate that the proposed Collaborative Optimization framework for multidisciplinary robust design optimization effectively attains solutions that are robust to variations in design variables and environmental conditions.