The introduction of solutions conventionally called Industry 4.0 to the industry resulted in the need to make many changes in the traditional procedures of industrial data analysis based on the DOE (Design of Experiments) methodology. The increase in the number of controlled and observed factors considered, the intensity of the data stream and the size of the analyzed datasets revealed the shortcomings of the existing procedures. Modifying procedures by adapting Big Data solutions and data-driven methods is becoming an increasingly pressing need. The article presents the current methods of DOE, considers the existing problems caused by the introduction of mass automation and data integration under Industry 4.0, and indicates the most promising areas in which to look for possible problem solutions.
This work deals with the study of polymers, and, in particular, polyethylene; its production, types, properties, and usage. The experimental part evaluates the changes of properties of the polyethylene film to be reused under various exposure conditions and selection of the most suitable medium for its application. The film made of low-density polyethylene (LD-PE) was influenced by aggressive media with different pH, specifically Savo for the disinfection, Savo as a Saponate for dish washing and Coca-Cola. On LD-PE films the water absorption and melting temperature evaluation tests were performed. Carried out tests show that the most aggressive medium for LD-PE film from used media is Coca-Cola. The most effective application of LD-PE film like wrapping on container transported is the Savo used as a Saponate for dish washing.
Every year approximately 70 million passenger cars are being produced and automotive industry is much bigger then just passenger cars. The impact of automotive industry on the environment is tremendous. From extracting raw materials through manufacturing and assembly processes, exploitation of the vehicle to the reprocessing irreversible, extensive environmental damage is done. The goal of this study is to show how implementing eco-design processes into supply chain management can reduce the impact of automotive industry on the environment by e.g. reducing the use of the fuel, increasing the use of recycled materials. Focus is on evaluation of current state, environmental impacts and potential improvements for design, raw materials, manufacturing and distribution and end-of-life phase.
Modern methods of testing materials require the use of the latest technologies and combining measurement and calculation methods. It is important to find a quantitative way of describing, among other things, the failures so that it can help to design with high accuracy. This paper studies loading orientations on crack shape and fracture surface changes. The advantage of the entire fracture surface method is simplicity and applicability in studies on other materials, shapes and loadings. A higher values of fracture surface parameters (Sx, Vx) was observed in failure specimens with lower σ/τ (B/T) ratios. It has been observed that largest crack lengths with a small number of cycles occur for loading combinations different then B=T. As well as analyzed surface parameters Sx, Vx, are higher for larger number of cycles to crack initiation (Ni) values.
The axial crushing behaviour of tubes of different section shapes has been extensively investigated as they have an excellent energy absorption, but the thin walled corrugated tube structures have been designed to further improve their energy absorption performance. The study aims to analyze the effect of sinusoidal corrugations along cross section of the tube on peak force, energy absorption and specific energy absorption. In the present work the response surface methodology (RSM) using central composite design (CCD) has been used and simulation work is performed by using ANSYS workbench to explore the effects of geometrical parameters on the responses of constructing models.
Decrease of vehicle emissions require design changes already at the initial concept design. Use of fiber reinforced polymer (FRP) composites in design cause reduction of weight with increasing other properties. Paper presents the case study of proposal material for frame concept of special light vehicle design. The flexural test (basically three-point bending test) of carbon fiber reinforced polymer composite bars with annular and square cross section is presented. Experimental results were verified by numerical simulation finite element method (FEM). The permanent deformation of bar with annular cross section occurred at a force 2 280 N with deflection 4.22 mm. Model numerical simulation by FEM show same course of loading. For bar with square cross section the deformation occurred at a force 2 264 N, with deflection 7 mm. Model numerical simulation by FEM show different trend (under force 2264 N the deflection was 3.4 mm).
The research was supported by the Slovak Research and Development Agency under the contract no. APVV-18-0457, Special Light Electric Vehicle from Unconventional Materials to
Currently, effective quality management of manufactured products is a factor determining the development of manufacturing companies. However, the identification of the source of non-compliance and the analysis of its causes are sometimes underestimated and are not followed by appropriate methodologies. The study aimed to streamline and improve the production process of aluminium pistons for passenger cars by solving the problem related to a significant number of non-compliant products. The analysis of types of nonconformities identified through penetration testing was performed. The use of histogram, brainstorming session and Pareto-Lorenz diagram was proposed, which allowed identifying the causes of the problem. The presented solution shows the practical effectiveness of a sequence of selected instruments to solve production problems. The proposed sequence of methods can be implied in other qualitative analyses in different companies.
The article presents the element of occupational health and safety management in enterprises, with particular emphasis on the identification of occupational hazards. The factors that may be a source of occupational hazards have been classified and divided. The aim of this study was to assess the impact of occupational hazards on work safety in the opinion of employees of micro and small enterprises. The research was carried out using the proprietary questionnaire. The results were verified by means of a direct interview with elements of observation. The research was compared with the trends prevailing in the enterprises of the European Union countries according to the results of the research conducted by EU-OSHA. Polish respondents considered physical and psychophysical factors to be the main occupational hazards. The results turned out to be very similar to those presented by EU-OSHA in its publicly available reports. The basic principle of occupational health and safety management, i.e. identification of occupational hazards, is reliability and correctness. Identification of occupational hazards gives the opportunity to take correct and effective corrective and preventive actions reducing occupational risk, for example through the effective use of personal protective equipment, or a more detailed treatment of both introductory and instructional training. The article also highlights the migration of individual occupational hazards, which depends on many factors, both professional and non-professional.
This study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orders delivered on time (100%). Our study provides a mathematical model with time constraints and large job volumes for a complex distribution network in reality. The proposed mathematical model provides effective solutions for making decisions at logistics companies. Furthermore, our study emphasizes that simulated annealing is a more suitable algorithm than the two others for this vehicle routing problem.
Nowadays there is a huge demand of High Strength Temperature Resistance (HSTR) alloys such as titanium, carbide, nimonics and ceramics in aerospace, defence and electronics. Among these alloys machining of tungsten carbide alloy is of interest, because of its numerous applications. Complex shapes of tungsten carbide are not generally made by traditional manufacturing process. To machine tungsten carbide with high accuracy, non-traditional machining process like Laser beam machining, Electron beam machining and Electrical discharge machining are a proper choice. In the present paper, the authors have machined Tungsten carbide (93% WC and 7%Co) with copper electrode. The machining is performed on EDM MODEL 500 X 300 ENC with VELVEX EDMVEL-2 as dielectric oil. The 17 experiments are carried out based on RSM (Box-Behnken) method. Further, in order to find the optimum combination grey relational approach is used. The results showed that pulse-on-time of 40μs, pulse-off-time of 2μs and current of 8A are optimum combination for machining of Tungsten carbide (93% WC and 7%Co). Lastly, the confirmation experiment has been conducted.