Cobots Implementation in the Era of Industry 5.0 Using Modern Business and Management Solutions

The paper describes the possibilities of implementing cobots for the execution of manual tasks in human-cobot collaborative teams to reduce waste within manufacturing systems from the perspective of Industry 5.0. Particular attention is paid to those manufacturing systems where, due to the high costs of possible reorganization, cobots are implemented in the existing system without significant modifications. The work is carried out in collaboration between humans and machines. To illustrate proposed implementation model, a conceptual use case (concept case) corresponding to an actual furniture manufacturing process was developed. The identification of the space for the use of cobots was verified using the value stream mapping method, and the implementation possibilities were analyzed using dedicated simulation software. The production process was mapped in both the value stream map and the simulation software. The potential for time savings in the implementation of the production process and a potential increase in the average production volume were demonstrated. Thus, the implementation possibilities of the presented concept were positively verified. The presented approach forms the basis for innovative solutions based on an interdisciplinary combination of organizational, management, and technical issues from the perspective of cobot use. This offers the opportunity to develop a cost-effective solution for implementing modern cobotic system technology to reduce waste in line with lean management. The concept opens up the perspective for many questions in terms of how and when to implement a cobotic systems solution in an organization. This is particularly relevant from the perspective of a company operating in a specific industry, using selected technologies and work organization methods

DATA ENGINEERING IN CRISP-DM PROCESS PRODUCTION DATA – CASE STUDY

The paper describes one of the methods of data acquisition in data mining models used to support decision-making. The study presents the possibilities of data collection using the phases of the CRISP-DM model for an organization and presents the possibility of adapting the model for analysis and management in the decisionmaking process. The first three phases of implementing the CRISP-DM model are described using data from an enterprise with small batch production as an example. The paper presents the CRISP-DM based model for data mining in the process of predicting assembly cycle time. The developed solution has been evaluated using real industrial data and will be a part of methodology that allows to estimate the assembly time of a finished product at the quotation stage, i.e., without the detailed technology of the product being known

Human–Machine Relationship—Perspective and Future Roadmap for Industry 5.0 Solutions

The human–machine relationship was dictated by human needs and what technology was available at the time. Changes within this relationship are illustrated by successive industrial revolutions as well as changes in manufacturing paradigms. The change in the relationship occurred in line with advances in technology. Machines in each successive century have gained new functions, capabilities, and even abilities that are only appropriate for humans—vision, inference, or classification. Therefore, the human–machine relationship is evolving, but the question is what the perspective of these changes is and what developmental path accompanies them. This question represents a research gap that the following article aims to fill. The article aims to identify the status of change and to indicate the direction of change in the human–machine relationship. Within the framework of the article, a literature review has been carried out on the issue of the human–machine relationship from the perspective of Industry 5.0. The fifth industrial revolution is restoring the importance of the human aspect in production, and this is in addition to the developments in the field of technology developed within Industry 4.0. Therefore, a broad spectrum of publications has been analyzed within the framework of this paper, considering both specialist articles and review articles presenting the overall issue under consideration. To demonstrate the relationships between the issues that formed the basis for the formulation of the development path

Zdalny monitoring zasobów produkcyjnych z wykorzystaniem nowoczesnych narzędzi

The article characterizes and identifies aspects of the changes in contemporary production environments. It presents successively changes related to the process of organization of production processes related to the fourth industrial revolution as well as to the progressive degree of computerization of production systems. The article outlines the solution and context in which they can be applied to composing IT solutions for modern production environments.W artykule scharakteryzowano i zidentyfikowano aspekty zmian we współczesnych środowiskach produkcyjnych. Przedstawia kolejno zmiany związane z procesem organizacji procesów produkcyjnych związane z czwartą rewolucją przemysłową oraz postępującym stopniem informatyzacji systemów produkcyjnych. W artykule przedstawiono rozwiązanie, w jakim można je zastosować przy komponowaniu rozwiązań informatycznych dla nowoczesnych środowisk produkcyjnych

Key role and potential of Industrial Internet of Things (IIoT) in modern production monitoring applications

The following paper presents a key role and potential of Industrial Internet of Things (IIoT) in industrial applications as a solution for monitoring and maintaining manufacturing assets. IIoT is particularly important due to progressing computerisation of hardware resources leading to development of a virtualised model of autonomous real-time production management. Adequately article presents case study of IIoT use in production environment – both methodical and analytic approach is presented

A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR’s) Operating Environment—A Case Study

The contemporary market creates a demand for continuous improvement of production, service, and management processes. Increasingly advanced IT technologies help designers to meet this demand, as they allow them to abandon classic design and design-testing methods in favor of techniques that do not require the use of real-life systems and thus significantly reduce the costs and time of implementing new solutions. This is particularly important when re-engineering production and logistics processes in existing production companies, where physical testing is often infeasible as it would require suspension of production for the testing period. In this article, we showed how the Digital Twin technology can be used to test the operating environment of an autonomous mobile robot (AMR). In particular, the concept of the Digital Twin was used to assess the correctness of the design assumptions adopted for the early phase of the implementation of an AMR vehicle in a company’s production hall. This was done by testing and improving the case of a selected intralogistics task in a potentially “problematic” part of the shop floor with narrow communication routes. Three test scenarios were analyzed. The results confirmed that the use of digital twins could accelerate the implementation of automated intralogistics systems and reduce its costs

Effectiveness of Bonding Steel Elements with Polyester-Coated Paint

The aim of the paper is to assess the impact of the effectiveness of bonding steel elements with paint coating. The adhesive joints were made using two types of the adhesives: two-component epoxy resin adhesive based on Bisphenol A and polyurethane. Three types of adhesive joints were made: (i) reference samples, (ii) samples with a paint polyester coating, and (iii) samples with a zinc primer and paint polyester coating. These coatings were applied using the electrokinetic method. A shear strength test of the adhesive joints (EN DIN 1465 standard), a coating adhesion test (ASTM D3359-B standard), and surface wettability tests (based on contact angle) were used. Through analyzing the test results, it can be seen that the strength of the adhesive joints of the reference samples made with epoxy adhesive is 46% lower than that of the specimens with primer and paint coating applied. However, in the case of the adhesive joints made with the polyurethane adhesive, the aforementioned difference in the strength value of the adhesive joints of the reference samples and paint-coated samples with an applied primer is 76%. Adherends with a paint coating and a previously applied primer obtained the lowest value of the contact angle (38.72°) and are characterized by good wettability

Comparative Analysis of Machine Learning Methods for Predicting Energy Recovery from Waste

In the context of escalating energy demands and the quest for sustainable waste management solutions, this paper evaluates the efficacy of three machine learning methods—ElasticNet, Decision Trees, and Neural Networks—in predicting energy recovery from municipal waste across the European Union. As renewable energy sources increasingly dominate the energy production landscape, the integration of Waste-to-Energy (WTE) processes presents a dual advantage: enhancing waste management and contributing to the renewable energy mix. This study leverages a dataset incorporating economic and environmental indicators from 25 European countries, spanning 2013–2020, to compare the predictive capabilities of the three machine learning models. The analysis reveals that Neural Networks, with their intricate pattern recognition capabilities, outperform ElasticNet and Decision Trees in predicting energy recovery metrics, as evidenced by superior performance in key statistical indicators such as R-value, Mean Squared Error (MSE), and Mean Absolute Error (MAE). The comparative analysis not only demonstrates the effectiveness of each method but also suggests Neural Networks as a pivotal tool for informed decision-making in waste management and energy policy formulation. Through this investigation, the paper contributes to the sustainable energy and waste management discourse, emphasizing the critical intersection of advanced technologies, policy considerations, and environmental stewardship in addressing contemporary energy challenges

Cognitive proximity for innovation: Why matters? an applied analysis.

The purpose of this research is to deepen the study of the influence of cognitive proximity has on the innovative performance of firms, as well as the mediating effect of potential and realized absorptive capacity in this relationship. For this purpose, an empirical analysis has been carried out. The primary data have been analyzed by means of PLS-SEM technique. The results show that the cognitive proximity of firms has both a direct and an indirect impact on their innovative performance, through their potential and realized absorptive capacity. We conclude that cognitive proximity matters for the innovation performance of firms, as it facilitates the understanding and establishment of positive reciprocity agreements between the companies, especially in terms of knowledge. Nevertheless, firms must develop a great capability to absorb new knowledge to exploit the advantages derived from its cognitive proximity to its stakeholders and leverage all the knowledge within their reach