List of Abstracts 2023: SESSION C - ADVANCED LOGISTICS TECHNOLOGIES
Date: November 9, 2023
In the automotive industry, as in other industries, there is a clear drive to achieve higher efficiency in industrial processes, energy savings, waste minimization and reduction of greenhouse gases. This effort extends to both production areas and associated areas such as logistics. This is particularly true in the automotive industry, where stable and efficient logistic is an important prerequisite for a stable supply of vehicles to final customers. This is also the case in specific production facilities such as foundry plants, where important vehicle components such as engine blocks, gearboxes and clutch housings are currently produced. Foundry plants are planned to be used for production of some components of electric vehicles in the future. This paper focuses on the main specifics of Škoda Auto company foundry plant and the possibilities of applying logistics process innovations in this production plant. In more detail it also focuses on the possibilities of data collection, processing, and digitalization in connection with the transition to Industry 4.0.
Asset inventories, in both the public and private sectors, play a key role in managing assets and maintaining accurate asset records. Traditional inventory is often associated with many risks and adverse events. In recent years, unmanned aerial vehicle (UAV) systems have become increasingly popular as tools supporting inventory processes in companies and beyond. The aim of this publication is to conduct a comparative analysis of adverse events in the traditional and UAV inventory processes. The results of our analysis prove a significantly lower number of adverse events occurring in inventory processes using UAVs. Our analysis is based on the results of research conducted in various sectors of the economy, primarily the production sector of the household appliances industry. In our research, we took into account all stages of the inventory process, from data collection to their processing and analysis. The results of our analysis suggest that inventory using UAV may result in a much lower rate of adverse events compared to traditional methods used so far. The results of this analysis show how the nature of adverse events is changing, and how we refer to specific types of adverse events, such as human and other errors. Our publication describes possible factors affecting the quality and time of inventory processes, as well as the equipment and infrastructure used, which can help minimize inventory-related risks with the support of UAS systems. The conclusions from this analysis will be important for companies that plan to introduce UAVs into their inventory process, as well as for those organizations that intend to optimize the efficiency and accuracy of their existing methods. This publication is intended to provide practical guidance on selecting appropriate inventory tools and strategies that can help minimize adverse events and improve the quality of inventory data.
Developments in the field of computing simulation bring new research opportunities for the field of logistics as well. The Industry 4.0 concepts and trends also brought a new topic which focus on the design of robotic workplace in particular manufacturing halls or companies. The form of the method of designing production workplaces has changed significantly over the last decade, affecting both the logistics and the tools and procedures used in the design. The development of computer visualization tools enables the implementation of virtual production before the first product is even produced. For this reason, the method and procedures of designing production workplaces were changed and reoriented to a visualization form. The paper deals with the development and procedures of designing a production workplace with the help of modern systems.
The idea of excellence in management is an inspiration for many scientists as well as practitioners. It also relates to very complex and multidimensional projects such as ERP venture. The idea of excellence determines also the above-average performance and efficiency in terms of business strategy implementation. The main objective of the study is to answer the following questions: 1) What is the idea of excellence in management in general?; 2) How can we define “Excellence” from logistics perspective? 3) How can we evaluate the level of logistics excellence? To what extent can ERP projects develop the idea of logistics excellence? Research was conducted on the basis of the analytical-synthetic method in the theoretical part and the case-study technique in the empirical part.
The warehouse is a very important component in supply chains (SC). It can appear in all stages of SC implementation, from the supply of raw materials to the delivery of finished products to users. The warehouse is a place of transformation of goods flows in which numerous processes are carried out. The efficiency of the warehouse process implementation greatly impacts the performance of the entire SC. Numerous benefits can be realized by influencing the processes that require the most resources. One of those processes is order-picking. The order-picking process can be influenced on three levels: technical-technological, organizational, and managerial. In this paper, improvement at the management level will be considered by introducing modern technologies such as: pick by light, pick by voice, pick by vision, augmented reality, and others. This paper is dedicated to the selection of modern pick-assist technologies in order to increase warehouse productivity. Technologies were compared and selection based on defined criteria. The Fuzzy Analytic Hierarchy Process (FAHP) method was used to determine the weights of the criteria, while the TOPSIS method was used for determine the rank.
The industrial landscape, including the automotive sector, is constantly striving for transformation in alignment with the principles of Industry 4.0 and broader digital transformation objectives. While numerous research papers elaborate on these concepts, they often do so in abstract terms, resulting in a notable gap between theory and actual implementation. Mixed reality tools, especially smart glasses, emerge as powerful catalysts for bridging this gap, primed to play a pivotal role in propelling industries towards the realization of Industry 4.0 and the evolution of smart factories. This paper delves into the potential applications of these advanced mixed reality tools within the industrial setting. By presenting specific use cases substantiated by proofs of concept, it offers tangible solutions poised for commercial deployment. The paper will further spotlight areas of practical application in production, logistics, and quality assurance, illuminating the path for genuine industrial transformation.
This paper refers to the problem of delivery process improvement. The subject of supply are parts and components for a vehicle production company. The deliveries are performed upon just-in-time system from the external warehouse to the factory. The authors propose a four-stage procedure which combines three research areas, i.e. process analysis, dynamic simulation and simulation optimisation. In the first stage of this procedure, the logistics process is analysed and modelled using process notation. The major process operations, cause and effect relationships, key human and technical resources and their assignment to the activities are identified. In the second stage, the process model is converted into the simulation model of deliveries to enable a dynamic simulation of its operations and to evaluate the process performance. In the third stage, the simulation model is customised and the computational experiments are carried out. Based on the analysis of results many weaknesses of the process are identified. In the fourth stage, the simulation model is extended by a formulation of objective function and constraints to run a simulation optimisation. Finally, the optimal delivery process is proposed. It is compared with the previous result of the authors research where this problem was solved using a stochastic multiple criteria ranking approach. Then the alternative process scenarios were ranked and the one with the highest position in the hierarchy was recommended. This solution and the new one from the current research are juxtaposed in this paper, and the differences between methodological approaches are presented, as well.