Tomaž Berlec

Self-organizing neural network-based clustering and organization of production cells

Organizing and optimizing production in small and medium enterprises with small batch production and many different products can be very difficult. This paper presents an approach to organize the production cells by means of clustering-manufactured products into groups with similar product properties. Several clustering methods are compared, including the hierarchical clustering, k-means and self-organizing map (SOM) clustering. Clustering methods are applied to production data describing 252 products from a Slovenian company KGL. The best clustering result, evaluated by an average silhouette width for a total data set, is obtained by SOM clustering. In order to make clustering results applicable to the industrial production cell planning, an interpretation method is proposed. The method is based on percentile margins that reflect the requirements of each production cell and is further improved by incorporating the economic values of each product and consequently the economic impact of each production cell. Obtained results can be considered as a recommendation to the production floor planning that will optimize the production resources and minimize the work and material flow transfer between the production cells.

A method of production fine layout planning based on self-organising neural network clustering

Organising and optimising production in small and medium enterprises with batch production and many different products can be very difficult due to high complexity of possible solutions. The paper presents a method of fine layout planning that rearranges production resources and minimises work and material flow transfer between production cells. The method is based on self-organising map clustering which organises the production cells into groups sharing similar product properties. The proposed method improves the internal layout of each cell with respect to a material flow diagram and a from-to matrix, and fine workspace positioning also considers various restrictions on placement, specifications and types of transportation. The method is particularly suitable for improving the existing layouts. The method was applied in the Slovenian company KGL d.o.o. and promising results were achieved. A reduction by more than 40% in the total transport length with respect to the current production layout was observed.

Risk Management of Cyclically Recurring Project Activities of Product Realisation

An extended risk-analysis procedure for new product/service realisation projects is presented in this paper. The usual risk analysis of project activities is based on evaluation of the probability that risk events occur and on evaluation of their consequences. Product/process realisation projects are cyclically recurring, so the third parameter has been added in the proposed procedure: an estimate of the incidence of risk events. On the basis of the calculated activity risk level in a three-dimensional risk analysis, a project team prepares preventive and corrective measures that should be taken according to the status indicators. An important advantage of the proposed solution is that the project manager and team members also take into account the recurring risk events in risk management. By successive elimination of sources of recurring risk events, the three-dimensional risk analysis of project activities can be transformed to the well-known two-dimensional risk analysis. A template was created in the MS project environment. The project team used the template for testing the proposed methodology in a case study of realisation of a die-cast tool for manufacturing a car component.

SOM-Based Clustering and Optimization of Production

An application of clustering methods for production planning is proposed. Hierarchical clustering, k-means and SOM clustering are applied to production data from the company KGL in Slovenia. A database of 252 products manufactured in the company is clustered according to the required operations and product features. Clustering results are evaluated with an average silhouette width for a total data set and the best result is obtained by SOM clustering. In order to make clustering results applicable to industrial production planning, a percentile measure for the interpretation of SOM clusters into the production cells is proposed. The results obtained can be considered as a recommendation for production floor planning that will optimize the production resources and minimize the work and material flow transfer between the production cells.