List of Abstracts 2018: SESSION B - PRIMARY LOGISTICS PROCESSES
Date: December 3, 2018
The article has a scientific- pedagogical character. Deals with the justification of the need to prepare "logistics" experts for the field of continuous media and energy logistic in networks. Current logistics is understood as discreet as well as preparation in study programs, respectively. Individual subjects and hence the scientific and professional basis deals with the flow of discrete products, for example, material flows are discretized. The article compares how logistics of discrete flows and operations and continuous flows and operations are identical and different. It also includes the concept of the study program "Logistics of Continuous Media and Energy" and the design of subjects through which this program should be implemented in the future.
Automotive industry, more specifically manufacture of motor vehicles, trailers and semi-trailers (CZ-NACE 29), is one of the most important sectors of the manufacturing industry both in the European Union and the Czech Republic. In 2014, the total waste generated in the EU-28 by all economic activities and households amounted to 2,503 million tons (Eurostat, 2017); 21% of the annual industrial waste production can be attributed to the manufacturing industry. The article focuses on the proposal for methodology of product lifecycle management based on the principle of logistics management in the contemporary context of the circular economy concept. Analyzing documents, the objective is to describe and evaluate logistics spiral of the product lifecycle in such a way that general methodology of pre-recycling will be formulated in the stage of research and development, manufacturing consumption/use (application of preventive approaches and measures enabling and facilitating waste recycling) in the selected part of the manufacturing industry CZ-NACE 29. Application of the general methodology should be in the entire logistics chain, i.e., in all levels of supply chain simultaneously, in all strategies of companies so as to achieve both new forms of business activities and competitive advantage of the entire network organization and, consequently, every company. Meaning of drafted methodological framework is to define an optimal recycling rate from the point of sustainable development, material flow closing and waste recycling optimization. Thus, qualities of sustainability (sustainable supply chain management) and environment (green supply chain management) from the management of the logistics networks integrate into the global society conditions of circular economy.
Metallurgical production is based on the use of a wider range of technological processes, but also on a large number of input raw materials. The current highly competitive environment also brings considerable demands on the optimization of all partial processes and operations. Reducing total costs, increasing the efficiency of individual activities, reducing resource consumption are just some of aspects that must be solved by the current metallurgical enterprises. The quality of input raw materials in the blast-furnace process has a significant influence on the technological and economic parameters. The assessment of input raw materials is complicated due to the variety of parameters monitored. These may be the characteristics of chemical, physical, technological, but also operational-economic characteristics. An interesting alternative is the use of logistics tools based on multi-criteria decision making, which will allow to quantify the significance of all relevant criteria. In the framework of the research carried out, a method of weighing the raw materials in the conditions of a selected iron producer in the Czech Republic was applied. The aim of the article is to present the results of the research and possible areas of further use in the environment of metallurgical primary production.
Containerisation of goods is a trend, that is constantly increasing in a meaning of volume of transported goods. The most of bulk goods are transhipped through container terminals in seaports. Concerning this fact, it is necessary to define logistics operations for loading, transhipping and unloading in every port. A base is an analysis of a current state of container transhipment in seaports and a definition of bottlenecks in logistics chains. Thanks to this a functional logistic terminal model can be established. Result of this research is logistic terminal operations at seaport container terminal and its application at fictitious terminal.
Suppliers are an inevitable part of a logistics chain. It is crucial for each company to select the best possible suppliers. Suppliers’ selection is a typical problem of multi-attribute decision making (MADM). All traditional methods for multi-criteria decision making have already been used to evaluate suppliers. However, very often the ranking of (potential) suppliers is not the final desirable result, because not only the best one, but a set of suppliers must be chosen. An intuitive way would be to select the first n suppliers in the ranking. But, this study shows, that this approach can lead to distorted results. In this paper, the PROMETHEE outranking method of MADM combined with integer programming is used to find the optimal portfolio of suppliers under various constraints (number of suppliers, demand for different types of products, available stocks of suppliers, limited budget of the company, etc.). The proposed application is demostrated using the numerical example.
Production and logistics systems are revolutionary changed nowadays. They gain new features and functionalities. Production starts to be seen as holonic system finally. Machines, robots and products become intelligent, and progressive information and communication technologies become central nervous systems of the future production. In the near future artificial intelligence will take on many management and decision-making activities in the production. Production systems will be able to learn from their past operations. Virtualization will bring massive deployment of sensors into the production, allowing to collect large amounts of data, to generate and process the information and use it to create and apply new knowledge. New production environment will maintain and operate its virtual image using the technologies of the internet of manufacturing and clouds. Without intelligent and adaptive production and logistics, companies will not be able to work effectively in the competitive environment of global markets. The effort to speed up and streamline the design process of intelligent production and logistics systems leads to the current trend of digitization and virtual design of the systems. An effort to improve the level of visualization, transparency, presentation of project outputs, as well as the effort to fully assess the feasibility of the proposed solution and to identify potential collisions in the system designed in the digital environment, leads to the creation and use of 3D models of individual objects as well as complex production and logistic systems. In the article, the authors describe Intelligent design system CEIT Table, which represents an integrated solution for the support of intuitive, team-based design of intelligent production and logistics systems of factories of the future. By a suitable combination of software and hardware, it is possible to accelerate and optimize the entire design process, while maintaining team decision-making. The article describes the basic concept of CEIT Factory Twin, which has been built intensively on the workplace of authors and interactive projection system CEIT Table represents one of its main parts.
The paper presents a genetic algorithm being used for production scheduling in a real-life small batch and multi assortment production company in Poland. The algorithm has been implemented in an already functioning scheduling module of an ERP system. The use of the algorithm generated better quality production schedules and significantly limited staff engagement in scheduling preparation and its control. The details of the algorithm, production system, the range of improvement, conditions which allowed the improvement as well as situation before it are shown in the article. These include planning procedures used before and after the improvement, rationale behind the genetic algorithm development and problems in its every-day use.
The study will present the importance of the market and the scale of cereal production in Poland. Paper will show an analysis of the directions of changes in their supply, sown area, yields and directions of grain distribution including foreign trade (export, import). A typical grain supply chain network will be presented, starting with their production, which takes place mostly in small farms, hence it is very dispersed and requires a good system of connections between grain producers and receivers, good organization of transport and storage. Concentration of deliveries to processing takes place through many channels. A graphical presentation of the flow of raw materials (grains of cereals) and cereal products from primary producers (farmers) through links of trade and agri-food industry to the final consumer will be made. Trends of changes taking place in the organization of cereal supply chains and their processed products will be presented. In the summary, the advantages and disadvantages will be assessed and places of potential changes improving these chains will be indicated.
Technological processes of freight transport are characterized by stochasticity of indicators describing its efficiency. The mentioned randomness is usually could be explained by the stochasticity of demand for transport services. Consideration of the demand parameters stochasticity is especially important in planning deliveries of petrol products, as far as additional costs caused by delays in the deliveries, in this case, could be extremely high. Thus, the accurate prediction model could contribute significantly to the reduction of costs for the distribution of petrol products.
The paper proposes an approach to forecasting the delivery volumes for petrol stations. The authors have developed the prediction model based on time series. The proposed model considers the stochasticity of demand parameters and, due to this, the accuracy of forecasts increases. The paper illustrates results obtained with the use of the developed model for different cases of demand parameters.
Lot of researches claim, that the Industry 4.0 is a future form of industrial development. But managers of Czech companies claim, that their processes are not prepared for this conception. This article is focused on designing of a lean workplace. It is a simpler way to implement one of basic ideas of Industry 4.0 conception. The goal of this workplace is not only to increase productivity but also to optimize material flows in enterprise and fulfill costumers´ demands. The aim of the article is to find the best design of two production lines in a specific enterprise. In the article are used methods of industrial engineering (layout optimization, workplace standardization, work studies). The desired production cycle was used in search of a suitable layout and production lines balancing. Also essential number of operators was considered. In order to find the best layout were time consumptions of all operations counted by two different methods and the results were compared.
The purpose of the article is to investigate artificial neural network ANN use in due-date assignment DDA for standard products in the real-life small batch and multi assortment make-to-order production company. The research was conducted with the historical data and resulted in the ANN aided DDA encoded into the company ERP system. The paper contains a comparison between different due-date assignment methods. The methods include company’s own procedure, multi variable linear regression and multilayer feedforward neural network. The details of quantitative and qualitative input variables, an output variable, the neural network structure and its training are presented in the paper. DDA approach incorporating material deliveries uncertainty was applied to both the linear regression and the neural network methods. DDA using neural network proved to outperform the other analysed methods.