Neural Network-Based Model for Supporting the Expert Driven Project Estimation Process in Mold Manufacturing

Abstract

The mold making industry is project driven, and as such it has to cope with the characteristics of an individual production process. One of the major sources of risk in project management is the inaccurate forecast of project costs, demand, and other impacts [1]. In the mold production process it is crucial to minimize uncertainty in the early project estimation phase. The estimation phase is commonly a human expert driven activity which is sensitive to the expert's bias. This bias can lead to an underestimation of project resources when the estimator is overconfident, or to over-estimation of project resources when the estimator does not have sufficient confidence that all aspects of the project can be properly covered. Both scenarios have a negative impact on future business. In the case of underestimation, the project will bring economic loss, and in the case of overestimation, it will most likely be assigned to a competitive supplier. The estimator's key competence is to properly collect and evaluate all significant information for making the project estimation successful. The contradiction lies in the fact that the estimator should spend minimal time necessary on estimation activity since usually less than 10% of all offers turn into orders in the mold making industry, as stated in [2] to [4].Estimations in the mold manufacturing business still rely heavily on intuitive methods, which are subjective and prone to reliability and repeatability problems. A solution for these problems is addressed in this article, with the development of a supported expert driven project estimation process.In the project estimation process the volume of manufacturing hours represents one of the most important pieces of information. It reflects the majority of costs in the final project price, and it most significantly shapes the project schedule. The research objective is to develop an ANN-supported, expert driven project estimation process to improve the estimation of the volume of manufacturing hours in the mold production. In addition to the development of a reliable estimation model, it is also very important to properly position the supporting model in the expert driven estimation process. Therefore, in addition to model building, the problem of proper position of the supporting model will be addressed in the paper.Following these aims, first an overview of estimation process is given. Then, the solution for the problem of proper placement of an estimation support model is addressed. Furthermore, the proposed ANN-based model for estimation of the volume of manufacturing hours is presented. Finally, the results of ANN modelling are presented and discussed. THE PROJECT ESTIMATION PROCESSA major challenge of the project estimation process in general is to achieve sufficient project estimation reliability within minimal time consumption for this operation. Estimation reliability is directly related to the amount and quality of the data available at the moment the estimation process takes place. As shown in Fig. 1, the availabi...

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