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The management and effective operation of enterprise systems – depending on ever-changing environmental impacts – can only be achieved by an appropriate information management practice. Today, in the corporate environment, an astonishing amount of data (often unstructured) is generated. The efficient processing of these data is by no means straightforward and unambiguous, and thus presents significant challenges for user systems. It is typical of the process that the customer would like to receive the product as soon as possible, but at least at a pre-determined time. Thus the quality of service is determined not only by the quality of the product but also by its availability. As is well known, the mission of logistics is to ensure the ordered product is delivered in the right time, place, quality, quantity and cost. In this mission has a specific product, finite duration, organizational structure with defined responsibilities, activities necessary for its production, and have the resources to carry out these activities. The processing of the product is divided into several stages, which form a separate unit from the managerial point of view. Like product procession, a section has specific products, activities, and organizational structure. The end of the phase is the production / implementation of the products / services specified therein, provided that they meet the required quality criteria. In our paper, we propose a methodology, which – together with the related mathematical model – can offer an opportunity to reduce entropy in logistics processes. The aim of the research is to develop a model that can be used to quantify the logistical process uncertainty. We believe that research will help find a way to overcome the shortcomings of current process management procedures. We give the formal description of the mathematical model and present an example of its application.

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Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Hencz, C., & Hartványi, T. (2020). Optimization of process lability in logistics systems. Science & Technology Development Journal - Engineering and Technology, 3(SI3), Online First.

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