Na wstępie artykułu krótko scharakteryzowano specyfikę procesów biznesowych w towarzystwie ubezpieczeń. Duże ilości danych zawarte w bazach danych wykorzystano do analizy dwóch podstawowych procesów – przypisu składki i realizacji świadczeń. Do zadań prognozy krótkoterminowej zastosowano sztuczną sieć neuronową. Scharakteryzowano etapy wstępnego przetwarzania danych, wyniki uczenia sieci oraz omówiono końcowe wnioski.
EN
In the beginning, business processes in Insurance Company were briefly characterized. Huge amounts of data included in data bases were used to analyze two business processes – sales income and insurance benefit. For short forecasting tasks an artificial neural network was used. Introductory stages of data processing and network learning results were characterized. At the end, final conclusions were discussed.
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Mechanical engineering companies which manufacture complex products (CNC machine tools, production lines) require a long implementation time, preparation of complicated technical documentation and total involvement of construction and technology engineers throughout the whole design and production process. The data used in the major area of such enterprises come mainly from departments involved in the preparation of technical production. The area of technical production preparation generates the largest volume of data in the ERP system. This stems from the prototypical nature of products and the necessity to create new construction and technology specifications virtually for each order separately. One of the major files in ERP systems is the material index file. Material indices, including standards of use, comprise a bill of materials. This is a basis for establishing demand for materials according to the Material Requirements Planning (MRP). Bills of materials are supplemented with technological operations, which is necessary for planning of production and balancing production capacity. The contribution of technical production preparation is important from the point of view of the budget and implementation schedule for the order. Thus, the design construction and technology for a product should be planned and registered in the ERP system. The costs of qualified engineering labour and depreciation of CAD and CAE software packages are high, moreover labour consumption while designing prototypes may reach thousands of working hours. For this reason, employees of design and technology areas should register the number of working hours spent on each project [1]. While developing the bill of materials and technologies, engineers deal with the monitoring of standard manufacturing costs. In this article an evaluation method of ERP effciency in the area of the technical preparation of production is presented. The method is elaborated on the basis of the experience of many implementations of ERP systems of industrial engineering companies.
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Today, it is hard to imagine a production company which is not using information technology. IT (Information Technology) infrastructure and software have become indispensable tools used by the majority of companies. Moreover, many companies could not run their business if it was not for effcient IT infrastructure and involvement of highly qualified IT specialists. The interpretation of the ERP (Enterprise Resource Planning) vary depending on whether it is used by a company, an IT market analyst or software distributor. The ERP systems are defined as a cohesive integration of processes in functional areas of the company, which improve work flow and order management, standardizes business practices, improve materials accounting and facilitates supply chain management [1]. The paper describes methodology of continuous improvement of the ERP system functionality on the basis of a user satisfaction survey, data analysis and the Deming Cycle. The proposed methodology is a result of many practical functionality innovations implemented in ERP systems, executed in order to improve business, logistic, production and decision processing. Some of the implemented innovations have been described using the example of manufacturing companies. The necessity of constant adaptation and improvement of the ERP system functionality caused by changing market conditions and the necessity of adapting enterprises executing engineer-to-order production to these changes is the principal reason for applying the presented methodology. The research is based on the survey and case study analysis of a manufacturing company (Delta company). The illustrative examples are also given.
Enterprise Resource Planning (ERP) are nowadays a software packages that can support all business activities of enterprises [1], [8], [10], [11]. The production enterprises often implement an ERP systems to improve important functions in such functional areas as sales, product design and technology, material management, purchasing or production planning. Absolute majority of them implement ERP in administration areas such as human resource, controlling, financial accounting or capital assets. The implementation of ERP is expensive and time-consuming process that often can fall flat. The enterprises that successfully implemented ERP don’t want to change the system long time to unique disturbances. But employers of the enterprise realize only the transactions in ERP that are necessary for property workflows and managers analysis. The lack of important data in the ERP system can result with impossibility of strategic analyses performance [12], [14], [16]. In the situation ERP can not support strategic decisions of managers too. In the paper an ERP evaluation method based on data analysis is proposed. The authors of the article claim that value of ERP system is consist of two important components: possibility for improving of critical business processes and possibility for critical decision support. The model of ERP evaluation system for project driven enterprise is proposed. The illustrative examples are given.
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