SimDataSim - Development of a methodology for similarity-based product configuration in order to increase economies of scale

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Especially in machinery and plant engineering companies an increase in the product variety has been observed in recent years. Given the heterogeneous and fragmented markets, new product variants are introduced in order to meet the needs of individual customer groups as precisely as possible. For this reason, more and more companies structure their products in a modular design in order to produce almost individually configurable product variants, without a huge loss in economies of scale. However, various configurations of product orders cause different direct and indirect costs, since, for example, adaptations to existing product variants need to be made. Especially the sale of unprofitable product variants to strategic customers leads to an uneconomical increase in variety, although at an early stage in the configuration process a preferred variant, that means a predefined default configuration of the product, should be offered to a customer ideally. However, companies lack a vivid, continuous and cross-departmental analysis and visualization of the variety in particular in the configuration process. The objective of the proposed research project is to develop a methodology for determining the optimum product configuration by the similarity analysis of existing product variants, in order to optimize the economies of scale along the order fulfillment process of a company in the field of mechanical engineering companies. Simultaneously, a cost-benefit-optimum product configuration is offered to the customer. By applying similarity analysis, a product order can be assessed with respect to its strategic benefit and the caused direct and indirect costs in order to determine the optimum configuration of the product order. Firstly, description models for the description of product orders from different perspectives and for the determination of similarities are developed. Explanatory models deliver the interactions in terms of the strategic importance of customers, the meeting of customer requirements and the induced costs along the order fulfillment process. In the design model, a methodology is developed based on an algorithmic method that enables the iterative optimization of the product configuration. The applicability of the method is ensured by the validation in industrial companies.