MONTE CARLO METHOD AND APPLICATION IN @RISK SIMULATION SYSTEM

The article is an example of using the software simulation @Risk designed for simulation in Microsoft Excel spread sheet, demonstrated the possibility of its usage in order to show a universal method of solving problems. The simulation is experimenting with computer models based on the real production process in order to optimize the production processes or the system. The simulation model allows performing a number of experiments, analysing them, evaluating, optimizing and afterwards applying the results to the real system. A simulation model in general is presenting modelling system by using mathematical formulations and logical relations. In the model is possible to distinguish controlled inputs (for instance investment costs) and random outputs (for instance demand), which are by using a model transformed into outputs (for instance mean value of profit). In case of a simulation experiment at the beginning are chosen controlled inputs and random (stochastic) outputs are generated randomly. Simulations belong into quantitative tools, which can be used as a support for a decision making

SIMULATION AS AN APPROPRIATE WAY OF VERIFYING THE EFFICIENCY OF PRODUCTION VARIANTS IN THE DESIGN OF PRODUCTION AND NON-PRODUCTION SYSTEMS

The paper deals with simulation and her forms of use in designing of production and non-production systems. Points to the possibility of using software can help in planning and subsequently in other phase of the lifecycle production and products. Article informs about some of the advantages of this type of software and his options. Sets out some theoretical knowledge of simulation and in the practical part presents some frequently used simulation software

DIGITIZATION OF BUSINESS PROCESSES AND TECNOMATIX AS A COMPREHENSIVE PACKAGE INSTRUMENT FOR THE CREATION OF THE DIGITAL FACTORY

Current trends in the development of a dynamic and turbulent world economy are largely digitization. Once upon the implementation and application of new production, made the setting and testing of variants directly to the production lines for their full operation. First production tested, set its standards and then began the production program. These procedures were but very costly and lengthy and on-going businesses big money and precious time. Gradual deployment of various software techniques, these processes are transferred into digital form. Technology has come to the point that all business and production processes nowadays we can make this into a digital form. In this way we manufacture everything in detail and test plan prior to the launch date line. Such technology is called Digital Factory

MANNER OF STOCKS SORTING USING CLUSTER ANALYSIS METHODS

The aim of the present article is to show the possibility of using the methods of cluster analysis in classification of stocks of finished products. Cluster analysis creates groups (clusters) of finished products according to similarity in demand i.e. customer requirements for each product. Manner stocks sorting of finished products by clusters is described a practical example. The resultants clusters are incorporated into the draft layout of the distribution warehouse

DIGITALIZATION EFFECTS ON THE USABILITY OF LEAN TOOLS

Current industrial engineering methods and techniques due to the complexity of new knowledge-based methods need to be extended to technologies and tools for modelling and simulation of production processes, logistics flows, production facilities as well as product design. It is important to focus on the whole life cycle of the company as well as the product. The article deals with the effects of digitization on lean-manufacturing tools that are often used in industrial practice

SIMULATION AS PART OF INDUSTRIAL PRACTICE

Article discusses the simulation as an efficient scientific method of problem solving in industrial practice. It creates an overview of the simulation program means used in industrial practice and creates an overview of tools for discrete, continuous, and combined

Applying a complex manufacturing process to a specific product

The article contains description and construction of the finished product, in our case it is the construction of the rear seat for the Ford car. We begin to solve the complex production process of our product by drawing up a production-assembly diagram, where we can see the individual parts of which it consists. Using the longest branch in this diagram we calculate the average assembly time and consequently the coefficient of concurrency. We will use the data to build a tree diagram (chronogram)

Model for Optimizing the Ratios of the Company Suppliers in Slovak Automotive Industry

The Slovak automotive industry consists of various companies and suppliers, with different positions in the supply chain for automotive manufacturers. The accuracy of component deliveries and their quality affect the ultimate competitiveness of the entire automotive industry. The creation of strategic partnerships and stable supplier–customer relationships is currently a necessity. The aim of the article is to design the model for optimizing the ratio of the company suppliers in the Slovak automotive industry. The basis for designing the model was the results of our own research focused on the quality and timeliness of component deliveries from various suppliers. Supply chain members work with multiple subcontractors, using multiple subcontractors to supply the same components. We analyzed the overall quality of delivered components at a certain stage of the supply chain. The quality of the supplied components was the sum of all items from all suppliers. The aim of the proposed model is to determine the optimal percentage of individual suppliers of a particular part so as to minimize the overall risk associated with the supply and inventory of a particular part for the customer. Research methodology was focused on identification of the key performance indicators and key risk indicators of components deliveries by different suppliers. Those indicators provide a basis for the effective results of further research. We designed and used an algorithm for preparing and evaluating the model for optimizing the ratio of the company suppliers in the Slovak automotive industry. This research used modeling methods, simulations, and optimization models. The proposed model was verified in the specific conditions of the automotive supply chain. Deliveries from two subcontractors were simulated. Based on the results of the simulations, the optimal supply ratio of the two subcontractors was determined for a specific component of a member of the supply chain at a higher level. The results of the research can be useful for different suppliers in the Slovak automotive industry. By partially modifying the model and adapting it for different conditions in other industries, the model of optimizing the distribution of supply from individual suppliers can be used for other supply chains