Material flow analysis by means of discrete event simulation proved to be a useful tool for decision support by several studies. This case study presents a bottleneck analysis for an Austrian Medium Density Fibreboard (MDF) production plant. The developed model was linked to actual production data and animated. The aim was to picture production, storage and transporting processes from the hot pressing of the boards through to shipping of batched costumer orders with sufficient accuracy. Different scenarios representing varying production programs and warehouse allocation principles were simulated. The results of the reference scenario showed good alignment to the corresponding factory data. At a production program with increased share of cut-to-size panels the saw turned into a bottleneck and the utilisation of the finished goods warehouse increased significantly.The simulation provided useful information about the capability of the production, transport and storage systems and their performance at altered conditions.
Large-scale manufacturing companies use larger automated assembly processes including the use of heavy robotic equipment to put together large products, such as automobiles. The assembly lines in these systems have centralized control, operated by only a few workers. However, the lines, as production elements, are independent in the assembly process. Automated assembly systems are designed to perform assembly operations in a fixed manner product assembly sequence. Four types of systems/operational planning problems are significant: delivery of parts to workstations; single station system; automatic multi-station systems; and partly automation. This paper focuses on the multi-station automated system used for operational assembly.
Large Scale Optimization is a very well-known concept in the context new manufacturing era. There are many applications focused on supply chain and intelligent or smart manufacturing. As part of flow optimization is substituting some workplaces with robotic structures (industrial robots, manipulators, cobots, etc.). Thus, one challenge is to get a good process design, with optimum systems use, with business impact, return of investment (from financial and human resource point of view). Another challenge is to choose the kinematic structure oriented on station's requirements. The robots are particular form of automation with significant costs that increase with the number of joints. But, in the context of Industry 4.0 revolution the use and design of robots and kinematic chain workstations it changes.
The present paper is focused on identify the main conditions that should be followed to obtain an optimum threedimensional (3D) printing, starting with the 3D design software, to printers and characteristics. The purpose of the analysis is to be able to develop an informatic instrument, designed for choosing the appropriate 3D printing characteristics, printers and materials based on the purpose and industry of the printed part. Because the input data are very diverse, with multiple options and the user either has one specific printer, or want a specific material, authors implement fuzzy logic in obtaining the optimum. Since there is no such software on the market, it is believed that the informatic application developed by authors can help the decision makers about their 3D printing process.
Any factory, whatsoever the product it processes and whatsoever the type of material processing, is vulnerable to internal perturbations, among whom the variation of the tool flux is of major importance. The main issue of tool management within the production system consists in the fact that "at request, any tool, of any type and dimension, must be available within the right time, at the right place" to cast off the tool penury in the system. Preventing vulnerability is achieved through management in real time, which, for eliminating the penury and the surplus, must ensure the minimal safety stock, regulated through managerial decision.
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