The paper addresses a managerial problem related to ensuring cybersecurity of information and knowledge resources in production enterprises interested in the implementation of INDUSTRY 4.0 technologies. The material presented shows the results of experimental research of a qualitative nature, using two expert inventive methods: brain-netting and a fuzzy formula of inference. The experts' competences included the following three variants of the industrial application of the INDUSTRY 4.0 concept: (1) high production volumes achieved using a dedicated and fully robotic production line (2) the manufacture of short, personalized series of products through universal production cells, and (3) the manufacture of specialized unit products for individual customers. The Google Forms software was used to collect these expert opinions. The conclusions of the research carried out using the brain-netting method point to nine variants of the cybersecurity strategy of IT networks and knowledge base resources in manufacturing enterprises represented by the experts. The results of the research using the fuzzy formula of inference are numerically and situationally defined relations linking the above-mentioned nine strategies with five types of cyber-attacks. The summary record of these relations as the basis for managerial cybersecurity recommendations has a matrix form.

The automotive industry is characterized by a high degree of uncertainty. Companies are facing the challenge of producing different systems simultaneously. Additionally, the global quantity of electric vehicles is also expected to increase significantly. This results in the following capability to remain competitive: Effective and efficient adaptions of production systems to model variations and volume increases. While flexible production is identified as the most promising concept, defining the actual flexibility level of included production resources is essential for its proper realization. A literature review on existing flexibility assessment approaches revealed their emphasis on high-level enablers and limited practical applicability in the automotive industry. In contrast, focusing the assessment on single workstations supports the selection of appropriate production resources. Therefore, a simple and structured standard procedure for a production resource flexibility assessment was developed. This theoretical construct was subsequently complemented with practical insights through its application on two real-life case studies within one automotive engineering company. Summarizing and discussing the findings in combination with a conclusion completed this paper.

In many companies, along with the economic development, the use of integrated management systems is becoming more and more common, which are subject to evolution in terms of, inter alia, offered functions and new user requirements. The main purpose of this paper is to compare selected ERP (Enterprise Resource Planning) systems in the field of production planning and control on the example of the automotive industry. The paper presents the contemporary functioning of the automotive industry against the background of issues related to the integrated management systems used in them. The research part presents the proprietary methodology for the assessment of IT systems used in the automotive industry, which included a user survey. The obtained score allowed to indicate the optimal ERP class system supporting production planning and control.

The main purpose of the paper is to identify and analyse a state of exploratory motivating factors in terms of lean management as the instrument of a policy of human resource management in the face of COVID-19 pandemic implemented in service companies. The main question is: if the motivation system used in the companies works out up against the unpredictable situation such as COVID-19 pandemic? The secondary purpose of the paper is to recognise relations and dependencies between these factors, and the question is: what factors have the strongest or the weakest relations with Lean Staff Management (LSM) tools? This research designed based on interview was conducted due to the lack of existing studies on the current status of motivating factors in terms of lean management tools in two service companies (case studies) in the light of COVID-19. The results show that factors influencing work efficiency in a dominating manner were, primarily, financial incentives (almost 21%), communications (around 21%), and workplace atmosphere (almost 18%). The paper investigates also the benefits and concerns of implementing LSM in service companies during the pandemic. This research might help the service organization’s management to identify the employees‘ problems to implement more effective lean services.

This article presents the assessment of the creative culture and the level of innovativeness in selected manufacture enterprises. The theoretical part of the article discusses the space for creativity in the company and the microfoundations of the pyramid of needs related to creative culture. The pyramid consists of different microfoundations, which were used to create a questionnaire to assess the level of creative culture. This study assessed creative culture according to a model of the hierarchy of needs, developed by the author of this study based on Maslow’s pyramid of needs. The assessment used an innovation questionnaire and a creative culture questionnaire. This article presents a sample analysis of the results obtained from two of the companies that participated in the study. Furthermore, the article summarizes the results obtained from all participating companies and gives recommendations related to establishing creative culture based on these results. Every company should implement appropriate standards to help it develop a creative working environment. The goal of assessing creative culture in a company is to assist managers in building a workplace that fosters creativity, since such a workplace is a significant factor affecting the emergence of innovation. The analysis of the creative culture of the companies revealed their weaknesses and strengths in this respect. The developed methodology will undoubtedly influence an increase of awareness and knowledge of enterprises in the field of creating a pro-creative company culture. Such actions will contribute to the increase of company’s innovation, thus influencing its development.

The activities of the organisation concentrate mainly on meeting customers’ requirements. For this purpose, various activities are being conducted for customer satisfaction surveys. In this context, it is important to predict the quality of the product and the changes in the cost of the purchase product. The purpose of this study is to propose a method for predicting the quality level of a product and change the cost of the product considering current customers’ requirements for a combination of product feature states and pro-quality changes. The method includes the calculation of the quality level of the product using the punctationformalised method, where the level depends on a combination of values of states (parameters) attributes of the product, that is, current and modified. The method was tested as an example of a household vacuum cleaner for which 20 attributes were determined. According to the Pareto rule (20/80), the four product attributes important for customers were selected. Thereafter, for important attributes, possible combinations of the values of these attributes were determined. In addition, an algorithm for determining the possible combinations of product attribute states in the MATLAB program was developed. Additionally, the change in the current cost of the product considering the change in the quality level was estimated. The product cost changes were determined based on the actual cost of the product and the current product quality level. The method allows the determination of all combinations of values of state attributes of the product, such that it is possible to take appropriate improvement actions both in terms of quality and cost. The results from the method allow the prediction of product satisfaction for customers and they are favourable in terms of production cost. Therefore, it is possible to design the product in advance and support the producer in preparatory activities.

Value Stream Mapping has been a key Lean tool since its publication in 1988, offering a strategic view on the reconfiguration of an organization’s processes to reduce overall lead time. It has since been used in many different domains beyond (car) manufacturing. However, the potential offered by its concise representation of both material flow and its controlling information flow seems to have been largely underused. Most literature reports on VSM in the context of waste detection and local improvements. VSM also supports redesigning the material flow (even on a supply chain level) towards (pure) pull systems. However, it fails to adequately give guidance on how to gradually evolve towards this ultimate ideal state. This paper wants to offer a significant contribution to practitioners on how to use VSM to bridge this gap. Another key challenge that remains largely unpublished is how to adapt the planning systems accordingly at each reconfiguration of the material flow. This paper presents extensions to the basic VSM tool to meet these challenges. It includes a more comprehensive 5-level hierarchy that allows to position most lean flow-related techniques. It also extends the basic “door-to-door” VSM with new symbols to accommodate these techniques into the map. Finally, it introduces a new set of 13 questions to support redesigning not only the material flow, but also the information flow. The resulting richer future state maps better support the gradual evolution towards a leaner future shop floor, as illustrated with an example.

Abstract Meeting quality characteristics of products and processes is an important issue for customer satisfaction and business competitiveness. It is necessary to integrate new techniques and tools that improve and complement traditional process variables analysis. This paper proposes a new methodological approach to analyze process quality control variables using Fuzzy Cognitive Maps. Application of the methodology in the production process of carbonated beverages allowed identifying process variables with the greatest influence on finished product quality. The process variables with the greatest impact on carbon dioxide content in the beverage were the beverage temperature in the filler, the carbo-cooler pressure, and the filler pressure.

Lean thinking and Industry 4.0 have been broadly investigated in recent years in intelligent manufacturing. Lean Production is still one of the most efficient industrial solutions in business and research, despite being implemented for a long time. On the other hand, Industry 4.0 has been introduced referring to the fourth industrial revolution. This study aims to analyze the combination of both Industry 4.0 and Lean production practices through a systematic literature review from a Lean Automation perspective. In this field, 189 articles are examined using VOSviewer for cluster analysis. Then, a more detailed analysis is provided to explore how Industry 4.0 and Lean techniques are integrated from a practical perspective. Results highlighted Big Data Analysis and Value Stream Mapping as the most common techniques, also emphasizing a growing trend toward new publications. Nevertheless, few practical applications are identified in the literature highlighting six gaps in the correlation of LA practices.

Industry 4.0 is expected to provide high quality and customized products at lower costs by increasing efficiency, and hence create a competitive advantage in the manufacturing industry. As the emergence of Industry 4.0 is deeply rooted in the past industrial revolutions, Advanced Manufacturing Technologies of Industry 3.0 are the precursors of the latest Industry 4.0 technologies. This study aims to contribute to the understanding of technological evolution of manufacturing industry based on the relationship between the usage levels of Advanced Manufacturing Technologies and Industry 4.0 technologies. To this end, a survey was conducted with Turkish manufacturers to assess and compare their manufacturing technology usage levels. The survey data collected from 424 companies was analyzed by machine learning approach. The results of the study reveal that the implementation level of each Industry 4.0 technology is positively associated with the implementation levels of a set of Advanced Manufacturing Technologies.

This paper proposes the application of the digital numerical control (DNC) technique to connect the smart meter to the inspection system and evaluate the total harmonic distortion (THD) value of power supply voltage in IEEE 519 standard by measuring the system. Experimental design by the Taguchi method is proposed to evaluate the compatibility factors to choose Urethane material as an alternative to SS400 material for roller fabrication at the machining center. Computer vision uses artificial intelligence (AI) technique to identify object iron color in distinguishing black for urethane material and white for SS400 material, color recognition results are evaluated by measuring system, system measurement is locked when the object of identification is white material SS400. Computer vision using AI technology is also used to recognize facial objects and control the layout of machining staff positions according to their respective skills. The results obtained after the study are that the surface scratches in the machining center are reduced from 100% to zero defects and the surface polishing process is eliminated, shortening production lead time, and reducing 2 employees. The total operating cost of the processing line decreased by 5785 USD per year. Minitab 18.0 software uses statistical model analysis, experimental design, and Taguchi technical analysis to evaluate the process and experimentally convert materials for roller production. MATLAB 2022a runs a computer vision model using artificial intelligence (AI) to recognize color objects to classify Urethane and SS400 materials and recognize the faces of people who control employee layout positions according to their respective skills.

The optimal decision regarding the place of production is an essential, sometimes determining factor of its effectiveness. The main drawback in substantiating the optimal location of production is the lack of a system approach to accounting in the analysis of potential sales markets. Orientation, when justifying the optimal location of production, only to some particular sales market (and orientation to specific sales markets is necessary both in terms of taking into account the costs of moving the benefit from the place of production to the places of consumption, and in terms of production capacity, since it depends unit cost of production) is erroneous because it does not take into account many other competitive options. The article develops a system approach to rationale optimal locations and production capacity, based on a comparison of combinations of locally optimal places, the total production capacity of which is equal to the total (system) demand. The variant of combinations of locally optimal places with minimal total costs is systemically optimal. The result of solving the problem will be information about 4 parameters of the production of benefit: “where?” (in what places), “how much?” (in each of these places), “how?” (with what technology in each of these places), “for whom?” (sales markets for each of these places). The system approach proposed in the article to rationale the optimal location of the production of a single benefit can be adapted to a more complex situation, when the optimal location of the production of several benefits is justified at the same time. Further research is promising in the direction of a clearer determination of the boundaries of the space of possible location of production, as well as in the direction of studying the possibility of aggregating potential sales markets.

The current market situation shows that enterprises are still struggling to digitize their business through the integration of the Internet of Things (IoT), artificial intelligence (AI), cloud technologies and other more advanced technologies, but the fifth industrial revolution is knocking on the door. This article deals with the analysis and evaluation of the impact of Industry 5.0 on entrepreneurs. Industry 4.0 analysis provides results based on interviews with practitioners as well as sales representatives. The main part of the article focuses on the business situation, where the goal was to identify existing gaps along with opportunities and threats. This analysis also describes the best way how to transform in times of the next industrial revolution. Study addresses the approach of integrating human workers in the supply chain in cooperation with automated processes. The purpose of this study is to confirm or refute whether companies are ready for another industrial revolution.

One of the most popular heuristics used to solve the permutation flowshop scheduling problem (PFSP) is the NEH algorithm. The reasons for the NEH popularity are its simplicity, short calculation time, and good-quality approximations of the optimal solution for a wide range of PFSP instances. Since its development, many works have been published analysing various aspects of its performance and proposing its improvements. The NEH algorithm includes, however, one unspecified and unexamined feature that is related to the order of jobs with equal values of total processing time in an initial sequence. We examined this NEH aspect using all instances from Taillard’s and VRF benchmark sets. As presented in this paper, the sorting operation has a significant impact on the results obtained by the NEH algorithm. The reason for this is primarily the input sequence of jobs, but also the sorting algorithm itself. Following this observation, we have proposed two modifications of the original NEH algorithm dealing with sequencing of jobs with equal total processing time. Unfortunately, the simple procedures used did not always give better results than the classical NEH algorithm, which means that the problem of sequencing jobs with equal total processing time needs a smart approach and this is one of the promising directions for further research.

This study is aimed at investigating the functionality of Visual Performance Management (VPM), along with determining the necessary features such a method should demonstrate to be an effective and meaningful tool for the development of Lean Management in an organisation. Based on the analysis of a case study in a large manufacturing organisation, a crosscutting assessment of such a system was made, a literature review proves the lack of such a comprehensive study. Six critical features of VPM were identified, they are very practical and giving many interesting insights into studied Lean method. The view emerged from empirical investigated shows VPM as of the wider functionality then only visual information exchange methodology. The VPM serves as cascade information exchange system and has substantial potential to support employee’s participation.

The paper considers the negative pandemic-type demand shocks in the mean-variance newsvendor problem. It extends the previous results to investigate the case when the actual additive demand may attain negative values due to high prices or considerable, negative demand shocks. The results indicate that the general optimal solution may differ to the solution corresponding exclusively to the non-negative realizations of demand.

The new industrial era, industry 4.0, leans on Cyber Physical Systems CPS. It is an emergent approach of Production System design that consists of the intimate integration between physical processes and information computation and communication systems. The CPSs redefine the decision-making process in shop floor level to reach an intelligent shop floor control. The scheduling is one of the most important shop floor control functions. In this paper, we propose a cooperative scheduling based on multi-agents modelling for Cyber Physical Production Systems. To validate this approach, we describe a use case in which we implement a scheduling module within a flexible machining cell control tool.

Since the beginning of the Fourth Industrial Revolution, enterprises have been promising the main advantages and benefits of implementing the Industry 4.0 technologies. However, the perception of new Industry 4.0 technologies may vary between different types of enterprises. The paper focuses on the main advantages of Industry 4.0 technologies for manufacturing enterprises. We analyze the difference of enterprise size and technological intensity in enterprise managers’ perception. The research was conducted based on a questionnaire survey that participated 217 enterprises from the Czech Republic. Statistical analysis showed that higher productivity and production volume are the main advantages of Industry 4.0. The present results show differences between enterprises according to their size. However, differences related to the technological complexity of enterprises have not been confirmed as an essential factor.

The consumption of various forms of primary and secondary energy is one of the main sources of greenhouse gas emissions to the atmosphere. Also, the increase in the prices of energy resources is an important factor affecting the economic profitability of running a business organization. Legal requirements in the European Union also affect the need to implement appropriate solutions aimed at increasing energy efficiency, which translates into the need of implementing Energy Management Systems, based the ISO 50001 standard, in many enterprises.. In the case study presented in the article, which is based on a company from the energy industry in Poland, the most important Energy Performance Indexes and the impact of the quality of their information on the results obtained were reviewed. In the analyzed example, the main process used only 28% of the total energy consumption in the organization. Insufficient attention to auxiliary processes led to an undercut of Energy Performance by nearly 11% in the first year of operation. It is partic-ularly important to properly collect data on auxiliary processes, which are very often omitted or treated in general in companies, and as shown may constitute a significant share in the total amount of energy consumed.

Horizontal Directional Drilling (HDD) is a very complex technology. Although the installation of pipelines by means of this technology is often successful, examples of unsuccessful projects are also known. Due to the complexity of the technology, with the interaction of multiple processes, risks related to uncertainties in these processes play important role. These risks are related to the variability of underground strata, changing natural environment, changes in economic environment, as well as limitations of the equipment, technical disruptions and human factors. This paper describes the risk evaluation results of the FMEA and a Pareto– Lorenz analysis for 14 external risk factors (8 natural or environmental risk factors as well as 6 economic risk factors) in HDD technology. In the proposed approach not only the probability of the external risk factor occurrence was considered, but also its consequences and the ability to detect faults, which were not plainly separated and taken into account in the literature so far. Such an approach has shown the relationship between occurrence, severity and detection for the analysed external failures. Moreover, 40 detection possibilities for the external risks in HDD technology were identified. The calculated risk priority numbers enabled ranking HDD external failures and identified the most critical risks for which the suggested detection options were unsatisfactory and insufficient, and therefore other types of risk response actions need to be explored.

The aim of the work was to develop a prioritizing and scheduling method to be followed in small and medium-sized companies operating under conditions of non-rhythmic and nonrepeatable production. A system in which make to stock, make to order and engineer to order (MTS, MTO and ETO) tasks are carried out concurrently, referred to as a non-homogenous system, has been considered. Particular types of tasks have different priority indicators. Processes involved in the implementation of these tasks are dependent processes, which compete for access to resources. The work is based on the assumption that the developed procedure should be a universal tool that can be easily used by planners. It should also eliminate the intuitive manner of prioritizing tasks while providing a fast and easy to calculate way of obtaining an answer, i.e. a ready plan or schedule. As orders enter the system on an ongoing basis, the created plan and schedule should enable fast analysis of the result and make it possible to implement subsequent orders appearing in the system. The investigations were based on data from the non-homogenous production system functioning at the Experimental Plant of the Łukasiewicz Research Network – Institute of Ceramics and Building Materials, Refractory Materials Division – ICIMB. The developed procedure includes the following steps: 1 – Initial estimation of resource availability, 2 – MTS tasks planning, 3 – Production system capacity analysis, 4 – ETO tasks planning, 5 – MTO orders planning, 6 – Evaluation of the obtained schedule. The scheduling procedure is supported by KbRS (Knowledge-based Rescheduling System), which has been modified in functional terms for the needs of this work assumption.

The automotive industry is a highly competitive sector. Manufacturers must effectively control highly complex production processes in order to fulfil all customer orders for customized cars on time, on budget and to the required quality. In this paper, the authors focus on improving the flow time of asynchronous automotive assembly lines by reducing the buffer time. A simulation-search heuristic procedure was developed and confirmed in a 5 workstations asynchronous assembly line installed in an automotive company. The proposed procedure identifies optimal performing buffer profiles for each storage level which guarantees lowest flow time while keeping the same throughput level. Experiments results show that our new algorithm significantly outperforms existing results, especially for large scale problems.

The purpose of servitization is to provide new business opportunities mainly to manufacturing companies. Companies strive to develop new services through utilizing servitization models, which are required to be applicable in several servitization scenarios. The main objective of this study is to propose a servitization model, known as “end-to-end servitization model” suitable for servitization purposes in companies. The model was developed based on several validated and commonly utilized service design models. Moreover, testing the validity of the model was implemented with the usability survey (usefulness, ease to use, easy of learning and satisfaction) with the Master’s level students, while they were developing new services by utilizing the proposed model. The results of this study indicate that the proposed servitization model can be utilized in different organizations to provide new services. Furthermore, the model can be concluded as useful, easy to use, easy to learn and it is at a satisfactory level based on the empirical evidence.

The green logistics item as a part of distribution processes represents an innovative perspective in many views. This perspective is current from an offer and demand point of view. Many authors examine only the businesses aspect, while labour market acceptance is important. The aim of this article is to create and verify a green distribution model and this examines the green distribution perception from the consumer’s point of view in a context of chosen demographic characteristics. The creation of a green distribution model is supported by secondary research at which consists of four parts – input, transport, production and sale. Model verification was taken with primary research which base was created of 409 respondents. In the study, we use many statistical and mathematical, as well as scientific and philosophical methods. Among the most significant belong Cronbach’s alpha and McDonald’s omega. We used to verify and estimate model reliability, correlation analysis for relation research, one-way ANOVA test for research hypotheses verification and cluster analysis for identification of possible hidden clusters. The model can be considered a reliable one. Results indicate a low influence of distribution ecological factor in a consumer’s perspective, as well, it can be stated, the age, contrary to sex, represents a significant factor in a green distribution perception. Results can be used in both the academic and commercial spheres in various fields and disciplines. The primary survey was conducted in Slovakia, but it would be appropriate to examine the model in other countries, as well as to identify factors that may affect the model of green distribution in the future.