The article covers issues of supply chain modeling being an important step in the decision- making process. Logistics and supply chain management consider movement and transition of material flow as well as financial, information and other flows associated with it. The characteristics of a flow must be measured considering the dynamics of the flow movement. This determines the importance of simulation modeling in decision-making support system as the approach involves the implementation of modeling system algorithm functioning in a virtual time environment. The literature analysis, on the one hand, allowed to conclude that the traditional approach to functioning process characteristics determination involving consistent problem solving on the level of supply chain element, is limited or not reflecting the specifics of real processes where the parameters variability in time is possible. On the other hand, there is lack of specific recommendations on building models based on principles of system dynamics as a simulation modeling tool which allows to consider process characteristics variability. This determines the aim of the research a part of which presents supply chain simulation model illustrating the possibilities of the approach. The results of the work can be used both in practice for industrial enterprises and for future research.
The paper examines the characteristics of Advanced Planning and Scheduling systems (APS systems). The various definitions of APS systems are analyzed. It is pointed out that the analysis of the experience of implementation of these systems leads to the conclusion about a number of deficiencies that do not allow them to solve specific range of tasks in a demanding planning environment. The key characteristics of demanding planning environments are systematized. Their presence limits the possibility of successful implementation of the standard APS systems. These characteristics include: the uniqueness of the technological processes; high complexity and scope; limited ability to describe and low predictability; high volatility and change sensitivity. The key features that allow classifying the new generation of APS systems are formalizes. The definition for APS systems of new generation is proposed. The comparative analysis of the planning systems of several generations (MRP II, APS I, APS II) is provided. Finally, examples of implementations of the new generation APS systems at Trinicke Zelezarny, Czech Republic; TimkenSteel, USA; VSMPO-AVISMA Corporation, Russia are provided.
The article sets out the strategy for the management of the company based on the vertical integration. Discusses problems in the management of a vertically integrated structure, the need for supply chain management and the implementation of an integrated planning in vertically integrated mining companies. Offers effective methods for solution of problems of integrated planning in vertically integrated mining companies.
Integrated supply chain management is becoming a promising direction of the research; its structure continues to evolve in conditions of integration and synchronization of material, service, information and intellectual flows, which in turn opens up new opportunities for interdisciplinary analysis. Unlike integrated logistics, where the main theoretical and methodological bases are already systematized, in the integrated management of supply chains (mainly, multi-level, called supply networks), this process only gets its development. Therefore, the article analyzes theories, methods, and models, economic metrics, existing terms, and definitions, taking into account the optimization of supply chains and the requirements for reliability, stability, and adaptability. An approach to the formation of integrated management of logistics systems based on the interrelation of the operational, tactical and strategic levels of decisionmaking is proposed. Information technologies, being a basis for supply chain planning, execution, and optimization systems, are recognized as the enabler for the proposed approach to the integrated supply chain management. With the help of IT, it becomes possible to unite the primary business processes throughout the whole chain, as well as using key performance indicators and operational information to identify bottlenecks in supply chains so as to provide their elimination in the most optimal way for the purpose of achieving critical strategies.
Currently, the competitiveness of the company largely depends on how it uses the opportunities offered by modern information technologies. The Internet of things, big data, blockchain, artificial intelligence technologies - all of this brings companies to a new level of interaction and competition, gives new opportunities to build logistics processes, adjusts supply chain management. It is no secret that an important factor of success in the market is the possession of information, or rather knowledge. The development of Internet technologies and mobile devices has led to the fact that a rare event is not fixed by people or any device now: visiting the store, a purchase, a trip, a meeting, etc. Information about these and other events is often in free access in the form of text messages in social networks, blogs, news websites, but the problem is to find, to analyze, and to draw conclusions. Text mining tools help to solve these tasks. The article reviews the experience of using text mining tools to solve problems in management, marketing, finance spheres, discusses possible applications of text mining in logistics and supply chain management. The article describes the process, the main typical text mining tasks, a review of the functionalities of modern text mining tools.
Article includes the approach to development of information OLAP (On-Line Analytical Processing) model for analysis of logistic business processes in retail companies. Solving of analytical tasks via OLAP tool is demonstrated to increase an efficiency of supply chain management in retail companies
It is impossible to manage a contemporary company without strategic planning and regular monitoring of goals and development direction of supply chain. Top management is in charge of solving tasks regarding merges and acquisitions, competition in the regional markets, influences of price change of raw material and components, problems of JIT transportations, demand structure and geography changes in the regional markets, strategic investment program definition.
Nevertheless in practice it is rare when the process of supply chain modeling and design is formalized at Russian companies. Analysis of supply chain efficiency is done sporadically, takes a lot of time, is not accurate and often is at too high level without consideration of the complex influence on the supply chain infrastructure. Trend to increasing complexity of material, financial and informational flows in supply chains of leading companies defines necessity in informational support of such important planning process. In recent decades specialized methods and technologies were built for modeling complex supply chains respecting production, resource, distribution and other constrains. One of the most important goals of these methods and technologies is informational support of strategic supply chain planning. The article provides an overview of typical tasks of supply chain planning, key methods of strategic modeling and also most popular mathematical software for this. The author provides his conclusions and recommendations at the end of the article.
The specifics of tasks, which are assigned to service companies, require concentrating and integrating up-to-date, complete and reliable information formed by the certain rules, and also ensuring prompt provision of this information according to established accessibility order. It is known that tasks, which are addressed during the after-sales service of complex technical products, including the order and supply of spare parts, can be fulfilled in diverse ways and using wide range of knowledge obtained by service company employees. Completely identical conditions of conducting after-sales service occur extremely rarely, the volume of information, that needs to be considered to form rational and reasonable decisions, steadily increases, and applied models, methods and technologies do not provide its complete and adequate account. These circumstances objectively require improvement of informational and technological basis of service company operations. This article contains pertinent problems of informational and analytical operation maintenance of service companies, implementing the after-sales service of complex technical products. It also proposes methodological approach to selecting the rational option for plan dedicated to improvement of informational and technological basis of these operations based on expert decision support system.
The present article is intended to a research of information aspect of the choice of development strategy of logistics organizations involved in container shipping. The standard factors which character and force of influence provides the information basis of the choice (correction) of development strategy of the organizations concerned are determined. The example of practical strategy correction of the logistics company which proves the necessity of information support of decision-making is provided. The information processing methods necessary for making decisions on the choice of development strategy of the logistics organizations are represented.
In this paper, the use of the apparatus of stochastic Petri networks applying to the analysis of supply chains is considering. The storage module and the production module of the logistics system and their interaction with other elements of the system have been analyzed. First, the considered logistical system was represented in the form of a stochastic Petri network, and then two models of one system with different initial conditions were created with the purpose of their behavior analysis and comparison. Analysis of the results of the models was carried out by two methods: the construction of an analytical model of the Petri net; simulation of the model for a specified period. In addition, the paper deals with the problem of exponential explosion; the dependence of possible states number of the system as a function of the change in its parameters was shown. As a result, it was shown how the behavior of the system changes with the change in the timing of the delivery of products and what period is critical for the production deficit.
The technique of creation of imitating model of planning potrebno is considered сти in spare parts for repair and equipment service (in particular, cars). As basis for creation of model the stream of refusals and function vosstano undertakes vleniye. Further on the basis of laws of distribution of random variables of practices between refusals calculate number of refusals for the planned period and planned the consumer nost in spare parts, according to a standard method. It is offered also at creation of model of a stream of refusals of a rolling stock of motor transport to consider a complex of repair influences which treat: major maintenance unit, major maintenance of the car, write-off of the unit or write-off. The concrete example of modeling of a non-stationary stream of refusals is shown is put pour the car Monte Carlo's method.
One of the options for a more flexible approach to analyzing the reliability of supply chains is the principal component analysis (PCA). With a large number of variables describing supply chain, it is a difficult task to analyze the structure of variables in two-dimensional space. Within the analysis of the variables dependencies PCA allows to go from multidimensional space to low-dimensional space, leaving the most informative data in the array for analysis. Based on the generated data set, this paper demonstrates a possibility of applying PCA to supply chain reliability analysis. The generated data set includes observations of 50 supply chains described by five variables. Based on the array, maximizing the linear combination of parameters for each observation, we determined load coefficients and estimates of each of the main components. The calculation of these coefficients made it possible to move from multidimensional space to a two-dimensional one. The two-dimensional representation of all the data whose axes are the first two main components, explaining 84% of the variance, allows to see the structure of all supply chains, to identify outsiders and leaders in this set.