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Inventory processes have significant importance in a company's logistics system and greatly influences its economic operation. Inventory management systems are used in the case of both dependent and independent products. The most used inventory model is the computation of economic order quantity model, which can be used in various types of objective functions and constraints. Logistic processes and their materials handling operations have a great impact on the optimal solution of economic order quantity problems, therefore it is important to consider logistic aspects while using EOQ. Within the frame of this article the authors describe a model considering available storage and transportation capacity, while fixed order lots as size of loading units and quantity discounts are taken into consideration. Two scenarios are discussed to validate the model and highlight the importance of logistics related constraints in computation of economic order quantity.
Ágota Bányai; Béla Illés; Zhumatayeva Gaziza; Tamás Bányai; Péter Tamás. Impact of Logistic Processes on Economic Order Quantity with Quantity Discount: An Optimization Approach. Asian Journal of Advanced Research and Reports 2020, 44 -52.
AMA StyleÁgota Bányai, Béla Illés, Zhumatayeva Gaziza, Tamás Bányai, Péter Tamás. Impact of Logistic Processes on Economic Order Quantity with Quantity Discount: An Optimization Approach. Asian Journal of Advanced Research and Reports. 2020; ():44-52.
Chicago/Turabian StyleÁgota Bányai; Béla Illés; Zhumatayeva Gaziza; Tamás Bányai; Péter Tamás. 2020. "Impact of Logistic Processes on Economic Order Quantity with Quantity Discount: An Optimization Approach." Asian Journal of Advanced Research and Reports , no. : 44-52.
Spread of the Jidoka concept can be phrased as a trend at the production of electronic products. In most of the cases, with the application of this concept, the development of testing procedures (for quality assurance purposes) of the finished products can be avoided. In those cases, when the production process of the appropriate quality product cannot be implemented safely for the establishment of the product testing process (following the production process), changing the number of variety products, change of requirements concerning the electronic products (e.g., instructions related to energy consumption, noise level) and the variation of the required testing capacity make the modification of the established testing process necessary. The implementation of related plans often leads to problems (e.g., not the appropriate storage area, material flow process or material handling equipment having been chosen). The method of process configuration affects the sustainability, since the poorly established process can lead to additional usage of non-renewable natural resources and unjustified environmental impact. For one of the tools of Industry 4.0, we developed such a state-of-the-art testing method with the use of simulation modelling by which the change of testing process can be effectively examined and evaluated, thus we can prevent the unnecessary planning failures. The application of the developed method is also shown through a case study.
Péter Tamás; Sándor Tollár; Béla Illés; Tamás Bányai; Ágota Bányai Tóth; Róbert Skapinyecz. Decision Support Simulation Method for Process Improvement of Electronic Product Testing Systems. Sustainability 2020, 12, 3063 .
AMA StylePéter Tamás, Sándor Tollár, Béla Illés, Tamás Bányai, Ágota Bányai Tóth, Róbert Skapinyecz. Decision Support Simulation Method for Process Improvement of Electronic Product Testing Systems. Sustainability. 2020; 12 (7):3063.
Chicago/Turabian StylePéter Tamás; Sándor Tollár; Béla Illés; Tamás Bányai; Ágota Bányai Tóth; Róbert Skapinyecz. 2020. "Decision Support Simulation Method for Process Improvement of Electronic Product Testing Systems." Sustainability 12, no. 7: 3063.
A globális környezeti problémák a világ minden pontján érzékelhetők, függetlenül attól, hogy mely földrészen élünk. Európában évi 2,5 milliárd tonna hulladékot termelünk, ami jelentős mértékben hozzájárul a környezeti terhelés fokozódásához. Ezt felismerve az Európai Unió 2015-ben hozott döntésének értelmében a közösség stratégiai céljává emelte a körforgásos gazdaság megvalósítását. Jelen cikk keretében a szerzők bemutatják a körforgásos gazdaság jelentőségét valamint a logisztika szerepét a körforgásos gazdaság megvalósításában.
Barna Szászi; Ágota Bányainé Tóth. A logisztika szerepe a körforgásos gazdaságban. Multidiszciplináris tudományok 2020, 10, 37 -42.
AMA StyleBarna Szászi, Ágota Bányainé Tóth. A logisztika szerepe a körforgásos gazdaságban. Multidiszciplináris tudományok. 2020; 10 (2):37-42.
Chicago/Turabian StyleBarna Szászi; Ágota Bányainé Tóth. 2020. "A logisztika szerepe a körforgásos gazdaságban." Multidiszciplináris tudományok 10, no. 2: 37-42.
The just-in-sequence inventory strategy, as an important part of the supply chain solutions in the automotive industry, is based on feedback information from the manufacturer. The performance, reliability, availability and cost efficiency are based on the parameters of the members of the supply chain process. To increase the return on assets (ROA) of the manufacturer, the optimization of the supply process is unavoidable. Within the frame of this paper, the authors describe a flower pollination algorithm-based heuristic optimization model of just-in-sequence supply focusing on sustainability aspects, including fuel consumption and emission. After a systematic literature review, this paper introduces a mathematical model of just-in-sequence supply, including assignment and scheduling problems. The objective of the model is to determine the optimal assignment and schedule for each sequence to minimize the total purchasing cost, which allows improving cost efficiency while sustainability aspects are taken into consideration. Next, a flower pollination algorithm-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase cost-efficiency in just-in-sequence solutions.
Tamás Bányai; Béla Illés; Miklós Gubán; Ákos Gubán; Fabian Schenk; Ágota Bányai. Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach. Sustainability 2019, 11, 3850 .
AMA StyleTamás Bányai, Béla Illés, Miklós Gubán, Ákos Gubán, Fabian Schenk, Ágota Bányai. Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach. Sustainability. 2019; 11 (14):3850.
Chicago/Turabian StyleTamás Bányai; Béla Illés; Miklós Gubán; Ákos Gubán; Fabian Schenk; Ágota Bányai. 2019. "Optimization of Just-In-Sequence Supply: A Flower Pollination Algorithm-Based Approach." Sustainability 11, no. 14: 3850.
In the context of Industry 4.0, the matrix production concept represents revolutionary solutions from a technological and logistics point of view. In a matrix production system, flexible, configurable production and assembly cells are arranged in a grid layout, and the in-plant supply is based on autonomous vehicles. Adaptable and flexible material handling solutions are required to perform the dynamically changing supply-demands of standardized and categorized manufacturing and assembly cells. Within the frame of this paper, the authors describe the in-plant supply process of matrix production and the optimization potential in these processes. After a systematic literature review, this paper introduces the structure of matrix production as a cyber-physical system focusing on logistics aspects. A mathematical model of this in-plant supply process is described including extended and real-time optimization from routing, assignment, and scheduling points of view. The optimization problem described in the model is an NP-hard problem. There are no known efficient analytical methods to find the best solution for this kind of problem; therefore, we use heuristics to find a suitable solution for the above-described problem. Next, a sequential black hole–floral pollination heuristic algorithm is described. The scenario analysis, which focuses on the clustering and routing aspects of supply demands in a matrix production system, validates the model and evaluates its performance to increase cost-efficiency and warrants environmental awareness of the in-plant supply in matrix production.
Ágota Bányai; Béla Illés; Elke Glistau; Norge Isaias Coello Machado; Péter Tamás; Faiza Manzoor; Tamás Bányai. Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production. Applied Sciences 2019, 9, 1287 .
AMA StyleÁgota Bányai, Béla Illés, Elke Glistau, Norge Isaias Coello Machado, Péter Tamás, Faiza Manzoor, Tamás Bányai. Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production. Applied Sciences. 2019; 9 (7):1287.
Chicago/Turabian StyleÁgota Bányai; Béla Illés; Elke Glistau; Norge Isaias Coello Machado; Péter Tamás; Faiza Manzoor; Tamás Bányai. 2019. "Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production." Applied Sciences 9, no. 7: 1287.
The accelerated movement of people towards cities led to the fact that the world’s urban population is now growing by 60-million persons per year. The increased number of cities’ population has a significant impact on the produced volume of household waste, which must be collected and recycled in time. The collection of household waste, especially in downtown areas, has a wide range of challenges; the collection system must be reliable, flexible, cost efficient, and green. Within the frame of this paper, the authors describe the application possibilities of Industry 4.0 technologies in waste collection solutions and the optimization potential in their processes. After a systematic literature review, this paper introduces the waste collection process of downtowns as a cyber-physical system. A mathematical model of this waste collection process is described, which incorporates routing, assignment, and scheduling problems. The objectives of the model are the followings: (1) optimal assignment of waste sources to garbage trucks; (2) scheduling of the waste collection through routing of each garbage truck to minimize the total operation cost, increase reliability while comprehensive environmental indicators that have great impact on public health are to be taken into consideration. Next, a binary bat algorithm is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and then evaluates its performance to increase the cost-efficiency and warrant environmental awareness of waste collection process.
Tamás Bányai; Péter Tamás; Béla Illés; Živilė Stankevičiūtė; Ágota Bányai. Optimization of Municipal Waste Collection Routing: Impact of Industry 4.0 Technologies on Environmental Awareness and Sustainability. International Journal of Environmental Research and Public Health 2019, 16, 634 .
AMA StyleTamás Bányai, Péter Tamás, Béla Illés, Živilė Stankevičiūtė, Ágota Bányai. Optimization of Municipal Waste Collection Routing: Impact of Industry 4.0 Technologies on Environmental Awareness and Sustainability. International Journal of Environmental Research and Public Health. 2019; 16 (4):634.
Chicago/Turabian StyleTamás Bányai; Péter Tamás; Béla Illés; Živilė Stankevičiūtė; Ágota Bányai. 2019. "Optimization of Municipal Waste Collection Routing: Impact of Industry 4.0 Technologies on Environmental Awareness and Sustainability." International Journal of Environmental Research and Public Health 16, no. 4: 634.
Manufacturing and service processes are composed of several elements: Technical, financial, logistics, information and human resources. Staff deployment and staffing is an essential problem in the human resource management domain because the structure of employees would be continuously in an optimal relationship to the jobs to be performed. This paper proposes a conceptual model for the analysis of human resource deployment processes. After a systematic literature review, it was found that algorithms are important tools for the design and control of human resource problems since a wide range of models determines an optimization problem. According to that, the main focus of this research is the modelling and analysis of human resource deployment processes of manufacturing companies using Markov-chain mathematics, also taking into account the absorbing phenomena of employees’ promotion. The main contribution of this article includes the model framework of Markov-chain simulation of a human resource deployment problem; the mathematical description of different human resource deployment strategies with subdiagonal and superdiagonal promotion matrices; the computational results of the described model with different datasets and scenarios. In the case of a given human resource strategy, the Markovian human resource deployment process of a company was analyzed. The analyzed model was the HR deployment of assembly line operators in a multinational company, including six levels of promotion. The results of the scenario analysis show that promotion and recruitment rates have a great impact on the future employees’ structure.
Tamás Bányai; Christian Landschützer; Ágota Bányai. Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy. Sustainability 2018, 10, 3692 .
AMA StyleTamás Bányai, Christian Landschützer, Ágota Bányai. Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy. Sustainability. 2018; 10 (10):3692.
Chicago/Turabian StyleTamás Bányai; Christian Landschützer; Ágota Bányai. 2018. "Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy." Sustainability 10, no. 10: 3692.