# Reducing the Total Product Cost at the Product Design Stage
###### Abstract
CP provides effective search strategies that reduce time needed to solve a wide range of combinational problems. In the aspect of NPD, the CSP paradigm has been mainly used in the field of product design [8; 9]. The use of CSP paradigm to cost estimation has been presented within the NPD cost, advertising cost, and unit production cost in [10]. This study develops previous research in the context of using the CSP paradigm to finding the trade-off between the cost of product development and the costs related to production and after-sales service. As a result, the contribution of this study is an extension of a cost estimation model towards involving the variables related to product design (e.g., material properties, prototype tests), production process (e.g., the number of defective products), and after-sales stage (e.g., the number of repairs in the warranty period). The cost of testing prototypes of a product increases directly in the number of tests, but at the same time, it can reduce the cost of defective products in manufacturing and after-sales service. Currently used software solutions dedicated to planning an NPD project provide information of the predicted project cost [11; 12]. However, if the company's resources (e.g., the project budget, project team members) are scarce to manage an NPD project according to schedule, project managers may be interested in acquiring information about possible changes to complete the project within admissible resources. Moreover, the total cost of a new product can have an unacceptable level for top executives. Current software solutions do not support project managers in identifying feasible variants of project completion, for which the desired level of the cost is sought. The proposed approach provides foundations to develop a decision support system with the use of computational intelligence in order to build parametric estimation model and simulate a possibility of reducing the total product cost. The paper aims to elaborate an approach for estimating product cost and simulating its reduction through changes in the product design stage. The product cost refers to the whole life cycle of a product including product development, production, and after-sales service. Considering that the production cost usually constitutes the majority of the total product cost, this study mainly focuses on the production process, trying to identify changes at the product design stage that affect cost reduction in manufacturing. Current methods of planning an NPD project use a procedural approach, in which an NPD model is built for a specific problem, and the process of designing the model ends when the structure of the model is sufficient to solve the problem. By contrast, in a declarative approach a single NPD model is developed, and it can be used to formulate various NPD-related decision problems [10]. A declarative representation of an NPD model provides a framework for applying effective techniques towards reducing the search space of possible solutions. This is particularly significant in the case of many decision variables with large domains which have to be involved in simulations. Using a declarative representation of an NPD model, decision-makers obtain more scenarios of feasible NPD project performance than they would if using traditional scenario analysis that includes the basic, optimistic and pessimistic variants. Moreover, decision-makers may acquire variants of NPD project performance which is something new and unexpected for them. This is particularly important in multi-project environments, where resources are shared [10]. This study develops previous research [7; 10] towards using the declarative approach to search for changes in product design that could be reduced the total product cost. The novelty of this research is twofold: specifying a model of the NPD project and company's resources as a set of variables and constraints, and designing a method of developing a decision support system dedicated to cost estimation and simulation of cost reduction.