The research deals with improvement of methods and systems of controlling integrated power systems (IPSs) on the basis of intellectualization of decision-making support. Complex analysis of large-scale accidents at power facilities is performed, and their causes and damages are determined. There is substantiated topicality of building condition knowledge-bases as the foundation for developing decision-support systems in power engineering. The top priorities of the research include developing methods of building a knowledge base based on intensity models of control actions influencing the parameters of power system conditions and introducing the smart system into information contours of the automated dispatch control system (ADCS), as well as assessing practical results of the research. To achieve these goals, the authors apply methods of experiment planning, artificial intelligence, knowledge presentation, mathematical simulation, and mathematical statistics as well as methods of power systems studying. The basic research results include regression models of a power system sensitivity to control actions, methods of building a knowledge base based on the models of sensitivity matrices, a structure of the smart decision-support system, a scheme of introducing the decision-support system into the operating ADCS environment. The problem of building a knowledge base of the dispatch decision-support system on the basis of empirical data resulted from calculating experiments on the system diagram has been solved. The research specifies practical efficiency of the suggested approaches and developed models.
The article presents a proposal of use a decision table to support the decision-making process in scope of maintenance management in mining companies. In particular, it refers to decisions related to evaluation and improvement of mining machinery use in the mining production process. The article presents the theoretical foundations of decision tables building and characteristics of the most important stages of creating this table. This whole process was tried to refer specifically the mining industry. For this reason, during construction of the decision tables, the results of research on the effectiveness of the selected mining machines were used. The conducted research provided a lot of data, information and knowledge on the work of the particular mining machines, especially regarding the number and reasons for unplanned breaks during the machines’ work. The developed decision table will consist of conditions, rules and actions whose purpose is to define the recommendations for the particular groups of participants in the mining production process. The obtained results will form the basis for the development of the recommendations and proposals of actions to improve the level of use of mining machines. The authors focused mainly on the practical use of tables to support the decision-making process regarding maintenance and improvement of effectiveness of mining machines. The obtained results confirm the validity of the adopted assumptions. Decision tables can become an important tool that supports the decision-making process within mining companies.
The goal of the paper is to present the application of Business Intelligence systems belonging to the area of business analytics in the domain of logistics and particularly indicate its role and meaning in supporting logistics decision making processes. Its content embraces the characteristic of BI systems, its functionality, construction and benefits resulting from its implementation. The paper also presents review of research and case studies connected to the BI usage in such areas of logistics as optimization of supply chain, managerial dashboard design and improvement of business processes.
One Piece Production Principle Masters Global Market Challenges
Successful companies in global markets must be innovative in product development and able to produce their products at lowest possible total cost, while highest quality and product availability in the markets is self evident. They must be able to manage violent market demand- and product design-changes with flexible and agile manufacturing systems . These challenges ask, in the first place, for new strategies in the field of designing appropriate process technologies, production process structures and, as we will show, new methods and considerations for planning and controlling the sequence of product variants within production programs.
The aim of this paper was to show the application of the ABC and AHP (multi-criteria method for hierarchical analysis of decision processes) as an important part of decision making in supply processes which are realized in the floral industry. The ABC analysis was performed in order to classify the product mix from the perspective of the demand values. This in consequence enabled us to identify the most important products which were then used as a variant in the AHP method.
Janusz Szpytko, Jarosław Smoczek and Artur Kocerba
Integrated System to Aid Supervisory Process of Technical Device
The aim of the paper is integrated system to aid supervisory process of technical device taking into consideration required level of exploitation safety and dependability. Preservation of accepted technical state of the machines and devices requires from users proper decisions which are results of continuous as well as periodically monitoring exploitation parameters' changes. Essential problem is digital drawing and conversion information from process of object exploitation and creating multi-access databases.
In this paper, we propose a method to estimate the probability distribution of the time interval which ellapses between the modifications of the cardinality in a random database query’s result set. This type of database is important either in modeling uncertainty or storing data whose values follow a probability distribution. The result that we introduce is important from the point of view of the database optimization, providing a useful method for an integrated module. In previous research on random databases the sizes of some relational operations results were investigated. This kind of information is rather useful in an analytical database which provides decision-making support. The result we particularly aim to present in this paper concerns the transactional random databases, addressing its specific functionality. It will be proven that the interval of time between the cardinalities changes is exponentially distributed. The proof is based on the technique of the Markovian Jelinski-Moranda model, which is used in the reliability of software programs.
E. Radziszewska-Zielina, E. Kania and G. Śladowski
The goal of the article is the diagnosis and presentation of the problems of the selection of construction technologies for buildings being built in the centres of urban agglomerations. The survey and literature studies that were performed show that the process of selecting these technologies is difficult due to a series of very different difficulties associated with constructing a structure in a city centre and which are sometimes hard to foresee. At the same time there is a lack of decision-making support tools dedicated to the selection of construction technologies that would take into account the problems that occur during the construction of buildings in city centres. The study shows the need to discuss the subject of developing a mathematical model and a decisionmaking support tool based on said model to that end.
The article presents the results of an application of K1/3 weather coefficient to tropical cyclone avoidance manoeuvre on the example of a tropical cyclones GASTON in the North Atlantic in. Avoidance manoeuvre was planned with the use of the Bon Voyage ORS (Onboard Routing System) of the AWT and also with the use of the programme CYKLON. The routes considered in the Bon Voyage system were generated by the route optimization algorithms of the system and routes programmed manually were generated by the system operator. Weather coefficient K1/3 was utilized as an index of safety of navigation in decision making regarding the ultimate route choice of all route variants generated and programmed in both decision making support systems. Results obtained point at the legitimacy of utilizing several decision support systems in solving the problem of tropical cyclone avoidance manoeuvre.
The complexity and dynamics in groupage traffic require flexible, efficient, and adaptive planning and control processes. The general problem of allocating orders to vehicles can be mapped into the Vehicle Routing Problem (VRP). However, in practical applications additional requirements complicate the dispatching processes and require a proactive and reactive system behavior. To enable automated dispatching processes, this article presents a multiagent system where the decision making is shifted to autonomous, interacting, intelligent agents. Beside the communication protocols and the agent architecture, the focus is on the individual decision making of the agents which meets the specific requirements in groupage traffic. To evaluate the approach we apply multiagent-based simulation and model several scenarios of real world infrastructures with orders provided by our industrial partner. Moreover, a case study is conducted which covers the autonomous groupage traffic in the current processes of our industrial parter. The results reveal that agent-based dispatching meets the sophisticated requirements of groupage traffic. Furthermore, the decision making supports the combination of pickup and delivery tours efficiently while satisfying logistic request priorities, time windows, and capacity constraints.