ALBERT

Description: Nowadays, it is necessary to verify the accuracy of servicing work, undertaken by new employees, within a manufacturing company. A gap in the research has been observed in effective methods to automatically evaluate the work of a newly employed worker. The main purpose of the study is to build a new, deep learning model, in order to automatically assess the activity of the single worker. The proposed approach integrates the methods known as CNN, CNN + SVM, CNN + R-CNN, four new algorithms and a piece of work from a selected company, using this as an own-created dataset, in order to create a solution enabling assessment of the activity of single workers. Data were collected from an operational manufacturing cell without any guided or scripted work. The results reveal that the model developed is able to accurately detect the correctness of the work process. The model’s accuracy mostly exceeds current state-of-the-art methods for detecting work activities in manufacturing. The proposed two-stage approach, firstly, assigning the appropriate graphic instruction to a given employee’s activity using CNN and then using R-CNN to isolate the object from the reference frames, yields 94.01% and 73.15% accuracy of identification, respectively.

Description: In recent years, more reports and articles have been published on the necessity of implementing changes to manufacturing processes in the context of sustainable development (SD). The use of IT systems in manufacturing companies creates the opportunity to support changes implemented in the context of adaptation to the concept of SD. This paper proposes and explores a Sustainable Development Card (SDC) within an enterprise, the use of which will enable knowledge about the enterprise’s development level to be gained in the context of SD through the data and information collected from the information system, namely, the Enterprise Resource Planning system (ERP) implemented within a company. This research uses studies from the literature on the subject and also the case study in order to determine the SDC integrated with the ERP system. The Analytic Hierarchy Process (AHP) method is used, which uses validity indicators to allow a manufacturing company’s development to be evaluated within the context of SD. The results were verified by a real case study of a Polish manufacturing company. It was determined that the proposed approach allows SD to be assessed in a manufacturing company and enables the implementation process of SD strategy to be constantly monitored. This paper contributes to theory and practice at the interface of the development and sustainability of a manufacturing company, whereby assessing sustainability is associated with the development of strategy and information systems that are associated with the development of an organisation. The possibilities of using the results of research, in practice, are demonstrated convincingly.

Description: (1) Background: In recent years, many studies regarding the issues of improving the management and effectiveness of the maintenance department of manufacturing companies, in the context Industry 4.0, have been published. This makes it necessary to establish a research gap in the approach to obtaining support in realising management tasks in the maintenance area in the selection of appropriate employees to perform the given activities. (2) Methods: This article uses literature studies and empirical research results from manufacturing companies, in order to determine the approach in supporting the selection of maintenance experts. In the approach, the method used—which is based on rules should there be future any formalisation of the data—is also the Fuzzy Analytic Hierarchy Process (FAHP), which analyses the importance of a given competence, within a manufacturing resource, to undertake repairs. (3) Results: The innovative approach towards the selection of expert workers in a maintenance department is created, in part, in the form of an implemented web-application. The novelty of the “maintenance expert selection map", so-called, is the provision of formal procedures for describing the competence of each maintenance worker and defining the best “state of nature”. (4) Conclusions: In the research that is presented here, the practicality for maintenance managers in the “maintenance expert selection map" was established. This map describes the competence of workers for selecting them for repair work within a given manufacturing resource; the scope of employee training was also determined in this research.

Description: (1) Background: Products, manufactured using additive manufacturing technologies (AM) are increasingly present on the market. The research was undertaken to determine the possibilities of increasing the use of AM technology in Polish manufacturing companies. The aim of the paper is to determinate the level of the AM technology use of Polish Metal and Automotive Manufacturing and the influence of AM technology use on the increase of manufacturing company’s competitiveness–in the context of Polish Manufacturing Companies. (2) Methods: This paper uses literature studies to determinate the AM technology used within the production processes in the automotive and metal industry companies (so called dimensions) and a questionnaire survey, which was carried out on a sample of 250 Polish Metal and Automotive Manufacturing Enterprises. (3) Results: The results were verified by a statistical analysis, using correlation coefficients. Based on the data obtained, it was determined that both metal and automotive Polish companies use, or have in their investment plans, the implementation of AM technology, due to the need to reduce production costs and increase speed and flexibility when responding to customer needs. Moreover, the relationship between applied additive manufacturing technologies and the effects of their use, in enterprises, was analysed. The novelty of our work is defining the dimensions of the AM technology use for our empirical research and determining the influence of AM technology use on the increase Polish manufacturing company’s competitiveness. (4) Conclusions: The possibilities of using the results of research in economic practice were demonstrated. We also highlighted the impracticality for managers to support the selection and implementation of AM technology in the context of obtaining possible benefits for a manufacturing company.

Description: Efforts toward a low-emission economy constitute a common challenge for Polish cities. Solutions are being sought to support Polish, medium-sized cities, that is, cities with about 140,000 inhabitants, to implement and develop low-carbon energy in their public transport systems. This paper proposes and explores a sustainable urban development card for a Polish city, namely, Zielona Góra, the use of which will enable the effects of a public transport system using low-carbon energy to be monitored. This research was based on the two main areas of analysis of a system of low-carbon energy and public transport and were formulated as: (1) Sustainable Development Goals (SDGs) and (2) Indicators of the Satisfaction Rate of Public Transport Passengers (SPTP). This paper used literature studies to determine SDGs as well a questionnaire-cum-survey, which was conducted on a sample of 1022 public transport passengers in Zielona Góra, Poland, to determine SPTP. The results were verified by a real case study of a Polish city, which, in 2019, had the largest fleet of electric buses in Poland; a statistical analysis was also conducted using correlation coefficients. It was determined that the proposed approach allows for low carbon energy public transport to be constantly monitored and analyzed. In the long run, this could be a good benchmark as to how cities might improve their level of sustainability.

Description: In recent years, additive manufacturing technologies have become increasingly widespread with the most intensive development being direct metal deposition (DMD), alloys, and ceramic materials on a metal substrate. This study shows the possibilities of the effective formation of coatings, based on heterogeneous metal alloys (Ni-based alloy and Fe-Al bronze) deposited onto 1045 structural steel. Changes in the microhardness, the microstructure, and the tribological properties of the composite coating, depending on the laser spot speed and pitch during DMD processing, have been considered. It was revealed that if the components of the composite coating are chosen correctly, there are possible DMD conditions ensuring reliable and durable connection between them and with the substrate.

Description: In recent years, general studies on Selective Laser Melting (SLM)/Selective Laser Sintering (SLS)/direct metal deposition (DMD) technologies, as well as studies on detailed issues in this area, have been carried out. However, a research gap is observed in investigations into the features of single tracks in the above-mentioned technologies. On the basis of data published in 2016–2019, an approach was adopted for a preliminary quantitative analysis of the knowledge base and also trends observed in the development of new technologies. This study demonstrates the effectiveness of the data mining technique based on the Bayes algorithm for analyzing trends in processes of additive manufacturing and the practical application of the knowledge received using the Bayes algorithm. After the analyses referred to above were completed, single and double layers of a composite material based on the Ni-based alloy and Fe–Al bronze were analyzed under different processing conditions. The effects of laser spot speeds and pitches on microhardness, microstructure, and interlayers’ features were described. So, the innovative approach, namely, the combination of the analysis of the scientific database of the phenomenon under study and the subsequent experimental investigation of its features, is the scientific novelty of the present study.