Intelligent Systems in Production Engineering and Maintenance III

Topology optimization (TO) is a design method that aims to reduce the weight of the component and material costs while providing the required safety during operation by optimizing the shape of the part for the assumed load. This article presents a case study on mass optimization of the part from the automotive industry. The part was optimized for additive manufacturing (AM) by the Laser Powder Bed Fusion (LPBF) method. The main objective of the work carried out was to select a part with an optimization potential and reduce the weight of the part. Morphological analysis was used to select the part. The criteria of maximum overall dimensions of the part, data availability, boundary, complexity of part geometry, and material costs were taken into account. After analyzing the results of the study, a brake pedal was selected as the part for topological optimization. The brake pedal was reverse engineering from the manufacturer’s technical drawings. It was determined that the sections of the selected part are oversized. The presented case study proves that it is possible to save material/mass if AM technologies and TO methods are used for the design and manufacture of automotive parts.

Advanced aerospace materials like Carbon Fiber reinforced polymer (CFRP) contains heterogeneous and anisotropic material characteristics that does not exhibit sufficient toughness before failure. CFRP materials are recently replacing most of the modern applications like aerospace, space exploration and in various exotic engineering applications due to their outstanding strength to super lightweight properties. Manufacturing operations like cutting and machining the CFRP to the required shapes are most challenging aspects that are addressed in recent times. Aim of this research is to investigate the influence of CFRP orientation and layering pattern when machined using WEDM Machining process. As the material is extremely capable, and its heterogeneous structure makes them stand out from other conventional materials investigating its machinability using WEDM is vital. WEDM is extremely capable and could produce parts with intrinsic cuts and high precision. The various parameters involved with WEDM are carefully studied along with the novel metal-CFRP-metal sandwich configuration to machine and the CFRP samples are experimented with these parameters. The results obtained from the research are analyzed and the best suitable combinations of WEDM parameters are determined. To facilitate this, the cut samples are observed under a microscope to closely inspect the samples to discover which parameters had influenced the smoothness and quality of the cut the most.

Rational logistics design is fundamental for successful economic cooperation between Ukraine and the European Union supplying mechanical engineering products. Such aspects will additionally allow countries with expanding economies to determine conditions for building effective logistics in the European market. The growing needs of potential European consumers for mechanical engineering products are due to an increase in demand for cheap semifinished products and components with an inexpensive supply cost. Trade statistics between European countries and Ukraine indicate, in particular, demand increasing for Ukrainian commodities over the past four years. Therefore, logistics chain specifics design requires organizers to identify all conflict situations and risks. The paper highlights a detailed study of technological processes in context relationships between all participants in supply chains. In research, several alternative scenarios are proposed to organize supply chains for mechanical engineering products. The variants set consider each participant's capabilities: technical characteristics, technology features for performing operations, and resistance to risk situations. The perspective algorithm has been proposed to design supply logistics options for mechanical engineering products and created analytical models that consider the impact of random processes on operations execution. Thus, risks rate and failures are also considered at each stage of supply chains. The authors obtained nonlinear and linear models to predict the amount of supply. The influence level of random environmental factors was determined on delivery efficiency according to the restrictions system. Various scenarios of effective management decisions can be proposed based on the results of supply chain modeling for mechanical engineering products.

With the growing use of technology in the manufacturing industry, additive technology has its contribution and potential for further advancements. This paper will discuss the various additive manufacturing processes and the potential of additive manufacturing and 3D printing technology in the 21st-century manufacturing industry. Additive manufacturing and 3D printing technology have been around for decades, but their applications and capabilities rapidly expand. A thorough analysis of additive manufacturing and 3D printing technology is reviewed, focusing on recent advancements made by several researchers and industries. The paper explores the current state of the technology and its potential applications in the future as Industry 4.0 continues to advance. Challenges that can hinder the technology from reaching its full potential are also discussed.

Ultrasonic guided waves offer several advantages, including fast propagation speed, low attenuation, and sensitivity to small damages. These waves are extensively employed in non-destructive testing of plate structures due to the varying sensitivity of different guided wave modes to damage, which enhances the accuracy of damage imaging. However, the presence of multiple modes of guided waves poses challenges such as aliasing of time-domain signal wave packets and difficulty in identifying damage information. To address these challenges, this study proposes the utilization of the f-k domain filtering method. By considering the corresponding relationship between the propagation direction of the guided wave and the frequency wavenumber matrix, combined with the characteristics of the differences in wavenumbers of different modes at the same frequency, a three-dimensional (3D) window function is constructed using numerical simulation and experimental methods. This window function facilitates the extraction of different modes and their corresponding damage reflection signals. Simulation and experimental results demonstrate the suitability of the modal separation method for extracting different modal damage reflection waves in the guided wave damage detection of aluminium plates. Furthermore, when the material parameters of a composite plate are unknown, the imaging data extraction method can be employed to extract the single-mode reference wavenumber for window function construction, enabling single-mode extraction.

Ferromagnetic materials underwent plastic deformation under stress, which in turn caused damage to the components. Nondestructive testing could protect the components from hazards. In this paper, the micromagnetic detection technology was proposed to quantitatively evaluate the stress and plastic deformation of DH steel. According to the stress-strain curve of DH steel, tensile specimens with different amounts of deformation were obtained. The tangential magnetic field, Barkhausen noise, incremental permeability and eddy current signals were synchronously acquired by the micromagnetic detector on DH steel. The feature parameters of the four types of signals were extracted. The coefficient of variation was used as an index to evaluate the repeated detection performance of the micromagnetic detector. The related feature parameters were selected as the input of the multiple linear regression model. The results showed that the incremental permeability signal was the most sensitive to stress. The absolute errors of the multiple linear regression model for stress and plastic deformation were ±1.5% and ±40 MPa, respectively.

In modern solutions of machine tools and technological devices for precision machining, rolling guides are used. Their advantages are low resistance to movement and the possibility of obtaining very good repeatability of positioning of working units. The main structural element is ball screws. During their utilization, there is gradual wear of the cooperating elements of the ball screw-nut assembly and deterioration of their functional properties. As the work is performed by the screw, its working surfaces are subject to abrasive wear, which results in a gradual loss of the accuracy of the machine and the technological quality of the manufactured products. It can also lead to failure due to damage to the ball screws. Applied preventive actions come down mainly to periodic inspections and maintenance of mechanisms. In order to prevent excessive wear of the rolling guides or even machine failure, the authors of the article proposed a prognostic model to determine the wear intensity of the ball screw based on backlash measurements in the lead screw-nut assembly. The article presents a developed model for the prediction of the wear intensity of the rolling guides based on artificial neural networks. The authors obtained a model of prediction accuracy of 81%.

The concept of sustainable development (SD) is gaining more recognition and the chosen SD goals are being implemented in enterprises. Until recently, organizations focused mainly on the economic aspect. Currently enterprises, when determining strategy, performing risk assessment and mapping processes using the VSM (Value Stream Mapping) tool, are increasingly making efforts to incorporate both ecological and social aspects. When defining their mission, vision and goals, enterprises cannot forget to specify indicators which act as a key signpost to business development. The indicator setting is based on SMART methodology and only sporadically is there a reference to SD goals. For monitoring purposes and in order to react quickly enough to process disruptions, enterprises are encouraged to collect data automatically. This will lead to lower level of defective products which have negative impact not only on the environmental but also on the economic aspect.In practice, many articles have been published on VSM and the impact of indicators on aspects of SD. The systematic review of the literature, which was carried out in this paper, confirms that the authors sought evidence of what indicators support SD. The systematic review of the literature performed according to the established research methodology, includes identification of research questions, identification of keywords, selection and exclusion criteria, and analysis of results.The main aim of this article is to obtain information on what indicators are currently in use in enterprises, and then to link them with the SD aspect. The collected input data will be used to develop a model for assessment of the impact of enterprise processes on SD. Following a consultation with experts, an attempt will be made to develop a model serving as a tool supporting small and medium sized enterprises.

The elasto-magnetic (EM) method is a promising pathway for cable force monitoring in cable-stayed bridges. The cable-stayed bridges are usually installed outdoors experiencing daily variations in temperatures, which is believed to have a noticeable influence on EM signal. In this study, EM calibration experiments were performed on a seven-wire steel strand to measure the variation in the main flux. Comprehensive indicators considering sensitivity, hysteresis error, and cable force resolution were used to examine the performances of classic EM parameters and new candidate ones. Seven parameters picked up by the comprehensive indicator were further compared in experiments considering both the effects of force and temperature. Through comparative study, two new parameters demonstrated outstanding ability for both cable force measurement and temperature insensitivity. They were recommended for practical application in cable force monitoring.

Welding techniques, such as electrical resistance spot welding, are widely used in automotive manufacturing. Welded joints of metals consist of complex material zones and regions of different shapes that need to be reflected in the modelling process. Parametric modelling is an efficient tool to develop data and knowledge for the understanding of mechanical behaviour and the effect of key design and material parameters for the applications and technological developments related to the welded joint. This paper presents the focus of an integrated data-led approach for studying electrical spot welding. The use of predictive modelling to evaluate the effects of key parameters of welded joints is analysed. Typical data from a parametric finite element model is presented and used to analyse the effects of sheet thickness on the deformation, stress and strain data. One approach is through comparing the data before fracture and the other approach involves analysing data at comparable displacements before the onset pf severe deformation stage. The use of the data-led predictive modelling in materials and process development, as well as training and application-specific research-technology integration, are discussed.

Monitoring, inspection, maintenance, construction, and restoration are nowadays challenging activities conducted during the process of civil infrastructure management, due to the revolutionary impact of mechatronics and information technology for their automation. In this paper, numerical simulations are proposed for a Cable-Driven Parallel Manipulator designed for inspection and monitoring of buildings and structures. Robots can effectively replace personnel for performing dangerous or unsafe operations. Referring to structures’ inspection, autonomous or tele-operated solutions can be used. In addition to conventional robotics, such as drones, mobile robots and climbing robots, which have become a reality in the last years, Cable-Driven Robots can be used, as completely new application, to locate the terminal link, i.e., the end-effector, carrying suitable sensors and/or specific tools, in wide application areas. In this paper, we address the problem of considering a specific type of buildings, those for which there are not regularly shaped walls or edges. We consider steel glass-façades buildings, with irregular shape. For this kind of buildings, the inspection can be very difficult, time consuming and quite expensive. Considering an irregular shape building, design consideration and simulations results of the inspection are proposed in this paper.

Thermal barrier coatings (TBCs) are widely used in turbine blade for protection of superalloy substrate. Interfacial debonding will lead to serious safety accidents of aircrafts and should be detected in advance. Vibrothermography (VT) and long pulse thermography (LPT) are two kinds of effective non-destructive techniques. In this paper, the two methods were used for defect detection in TBCs. Artificial debonding defects with diameter from 5 mm to 2 mm were fabricated. The results show that both VT and LPT can be successfully used to identify defects with diameter larger than 2 mm. The thermal contrast of the two methods reduces with the decreasing size of debonding defect, and there is a higher thermal contrast in VT than that in LPT, when a proper ultrasonic excitation frequency is selected in VT. Measurement accuracy is investigated by comparing the defect area, which shows that the average value of the relative error is reasonable except for defects with small size. The lateral thermal diffusion effect and imperfect manufacturing process of artificial debonding may be the main causes for the relative error. In addition, parameters of each method should be optimized for better defect detection in TBCs.

Mass, customised production is a strategy, dictated by the need to dynamically and quickly meet customer requirements. Industry 4.0 (I4.0) technologies can be an excellent tool to support the management and workflow of an enterprise, operating according to mass-customisation strategy. Therefore, this paper provides an analysis as to how a manufacturing company can be managed when operating according to mass-customisation strategy having introduced I4.0 technologies; this detailed analysis of the literature is provided particularly in order to understand the possibilities of increasing the efficiency of such production, due to the implementation of I4.0 technology. An innovative approach to assessing the influence of selected I4.0 technologies on the efficiency of mass customised production, in relation to the Customer–Product–Process–Resource (CPPR) framework is proposed, in addition. The concept presented is oriented towards the practical application and is illustrated by a real-life case study of two, selected, European, automotive industry manufacturing companies. The results of in-depth interviews with managers made it possible to build a tool for further survey research in European companies, regarding the management of mass customised production, in relation to the implementation of I4.0 technologies.

Laser ultrasonic Lamb wave detection technology provides technical support for noncontact and online large plate/shell structure detection. Improving detection accuracy and efficiency has always been the goal of inspection personnel. In this paper, we have built a noncontact laser ultrasonic Lamb wave detection platform to achieve rapid localization of abnormal damage in aluminum alloy plates. First, analyze laser ultrasonic Lamb waves’ modal types and wavelength components. Design and optimize a circular laser array based on near-field beamforming theory, with a single transmitter at the center and multiple receivers around the circumference. After extracting single-frequency components using wavelet transform, the azimuth of the scattering wave is estimated using the near-field 2D multiple signal classification(2D-MUSIC). The advantage is that there is no need to collect the reference signal or add window filtering to intercept the wave packet. The results indicate that damage within the 900 cm2 area can be localized within 0.7 s, and the orientation error is within 6°. This method is an efficient method to achieve damage orientation in a large area. However, the problem of the low resolution and artifact interference in multi-damage estimation presented by this method is urgent to be solved in the future.

The article presents actual challenges faced by tire manufacturers and contemporary industry. Directions of development of methods for detecting and eliminating defects generated in the tire production process were discussed, with particular emphasis on methods using artificial intelligence. An exemplary classification of tire defects is presented. It was noted that a solution to reduce the amount of tire waste due to exceeding the uniformity limits is needed. Quantities describing tire uniformity were characterized. In the frame of the main purpose of the research, it was checked whether the model based on a traditional artificial neural network (with one hidden layer) can predict the value of conicity (output variable) based on five input variables. To solve this problem, the authors used the Multi-Layer Perceptron (MLP) - machine learning method, due to its ability to train non-linear models in “almost real time”. The parameters of the network structure were determined to guarantee the achievement of root-mean-square error (RMSE) for the training set data at a very low, satisfactory level. The authors see the high potential of using the built model in the mass production of tires. Application of mentioned model will minimize the waste of time and tire components scraps, and also will actually improve the quality of the final product.

The fresh vegetable supply chain (FVSC) is a vital food supply chain for human consumption patterns. There are several hindering issues in the FVSC. Specifically, issues related to logistics operations are directly affecting the socio-economic statuses of the value chain actors and the vegetable ecosystem. Therefore, this research study reviewed the current status of the logistics operations at one of the main economic centers of a developing economy. This economic center operates as a wholesale platform for the FVSC. In this study, Swimlane diagram was improved with the inspiration of Business Process Modeling to visualise the current status conceptual diagram of the FVSC. The key issues related to the activities and processes were identified after assessing the conceptual diagram, known as the “As Is state” model. In the latter part of the study, areas for improvement using technology were identified, and corrective measures were proposed to improve logistics operations in the “To Be State” model. According to the study, integrating the supply chain network with producers, value chain actors, and consumers via a digital platform for data sharing and management will improve supply chain traceability and efficiency. Furthermore, it will increase transparency, allowing the supply chain to be more quality conscious and resilient in order to mitigate operational risks associated with FVSC. This study will contribute to the literature by addressing the current gap between how to digitally transform a traditional FVSC into a data driven digital FVSC.

Lattice structures are a unique class of architected materials characterized by their array of spatial periodic unit cells. These structures can be designed and engineered to provide a range of desired mechanical properties. Their excellent energy absorption properties make lattice structures well-suited for the design of shoe soles. Leveraging the geometric complexity of additively manufactured parts, the mechanical properties of architected materials, and accurate non-intrusive medical data, this research proposes an algorithmic modeling approach for designing customized lattice shoe soles. By integrating conformal and functionally graded lattices with various unit cell types placed throughout the structure based on plantar pressure data, the flexibility of the sole can be controlled locally in areas with high plantar pressure. This can help reduce ground reaction forces during walking and standing, minimizing negative effects on foot health and increasing comfort for the wearer. We leveraged volumetric modeling techniques for error-free Boolean operations and reliable geometry smoothing. In this manner, our algorithm generates an STL file that contains a watertight mesh, ready to be imported into the slicing software.

The use of operational indicators in the process of selecting a machinery park can have a wide practical application. Using the method presented in the article of applying the MTTR (Mean Time to Repair) indicator to determine the parameters affecting the operation of the machinery park, it is possible to direct the decision-making processes of the enterprise to maximize the productivity of the production enterprise. The use of the presented method makes it possible to minimize the total costs associated with new investments, as well as ensure the reduction of losses arising during the inefficient use of existing production resources.

B-pillar structural part is the key component of lightweight automobile body structure. To possess good strength and plastic fit, B-pillar generally has gradient characteristics of mechanical properties along its length, and there is a characteristic transitional range from high strength and low elongation hard parts to low strength and high elongation soft parts. To detect the local mechanical properties, the destructive sampling method is conventionally used for evaluating the mechanical properties of the transition region of automobile B-pillar. It is time-consuming and impossible to directly conduct rapid non-destructive testing of parts. Hence, a micromagnetic automatic detection system for the B-pillar of the body structure is developed to realize the non-destructive evaluation of the mechanical properties of the transition region. The BP neural network model is established by the magnetic characteristic parameters and mechanical performance indicators obtained from the B-pillar. It helps to realize the quantitative characterization of the mechanical properties of the transition region of the B-pillar structural part of an automobile, which has important engineering application prospects.

The Fourth Industrial Revolution means implementing new technologies and creating cyber-physical systems composed of intelligent resources communicating with each other. The widespread digitization of processes increases process efficiency, production flexibility, and the possibility of achieving the contemporary aims of sustainable development, sustainable production and consumption, and efficient energy consumption. Currently, a definite game changer is taking place in the autonomy of cyber-physical systems. Cyber-physical systems are expected to be human-oriented, more resilient to disruption and oriented to the ecological aspects identified with sustainability. The move away from the dehumanization of cyber-physical systems has led to the emergence of the Industry 5.0 concept supported by the European Commission. The new challenges identified by the Industry 5.0 concept, especially in the implementation of human-centric technologies and principles of sustainability and resilience, pose challenges to the knowledge and skills of today’s manufacturing engineers. Hence, the article’s main aim is to identify industrial employees’ essential skills and competencies in implementing Industry 5.0. The achievements and results presented in the article were obtained based on a survey conducted among experts representing universities and Polish companies, mainly meant manufacturing, R&D and service companies. The study includes aspects related to the problem of implementation of digital technologies identified with the fourth industrial revolution in the conditions of development of the concept of Industry 5.0. In addition, the directions of development of knowledge and competencies of employees are indicated, which can serve the development of the educational system of modern engineers.

This research focuses on technological innovation's adaptability in the Sri Lankan tea industry and its economic benefits. The four focused areas below were created to address specific knowledge gaps in this research. These objectives correspond to the study's purposes: Identify existing Internet of Things (IoT) applications in the Tea operational process in Sri Lanka. Assess the efficiency and economic sustainability of tea processing under IoT applications. Identify Issues with the existing technological improvement and challenges. Propose feasible autonomous applications according to the financial ability of the Sri Lankan Tea Industry. The research relies on both primary and secondary data. Factory visits provided observational data, and an expert opinion poll was undertaken among tea industry professionals in selected Sri Lankan companies active in the export market. The results of this study have significant policy implications for the tea industry and guide industry stakeholders on the potential of IoT applications to enhance productivity, reduce costs, and improve quality. The findings may be instrumental in guiding decision-making regarding IoT technology adoption and promoting economic sustainability in the Sri Lankan tea industry.

This paper is devoted to a create a digital twin for a robot equipped with pneumatic actuators. Implementing a digital twin in this context holds great promise, as it enhances controllability, an essential feature for modern pneumatic robots. The proposed technology for creating a digital twin of a soft robot with pneumatic muscles has numerous applications, including cellular production, where it can optimize the work environment and reduce the required space. The comparison between a digital twin of a pneumatic robot and its physical counterpart is discussed. The simulation results showed that the digital twin and the physical robot are nearly identical, with a maximum relative error of no more than 10%. Overall, the statement suggests that the study successfully demonstrated the effectiveness of using digital twin technology to model and simulate the behavior of a physical object. The results indicate that the digital twin technology used in the study can potentially be a valuable tool in soft robotics and cell manufacturing.

This article is a study that is based on a literature review. The research is aimed at a better understanding of the types and content of statistical methods and their features of use for decision-making in the management of parameters of technological systems. During the literature review, more than 200 scientific sources were analyzed, and about 140 articles on the topic were studied. About 80 articles published since 2000 were selected for the work. The conducted research made it possible to identify three main groups of statistical methods that are recommended for use in decision-making regarding the components of technological systems: methods of a high level of complexity, special methods and methods of general purpose. The proposed classification of statistical methods makes it possible to speed up decision-making when choosing a statistical method for research and analysis of parameters of technological systems and more fully reflects the nomenclature of recommended statistical methods.

The paper presents the results of the VR training application in use for electrical technicians. Eight participants were tested, who underwent a virtual training scenario and then provided feedback (in the form of survey study) regarding their subjective impressions of a given solution. The scenario consists of 27 steps and focuses on assembly of a low-voltage connecting cable to an existing installation. For each participant, the time of realization was measured, and the individual stages were controlled and evaluated by the instructor in order to assess the scenario difficulty and potentially identify and introduce any corrections. The paper describes the observations and conclusions that can be drawn by analyzing the entire training procedure and its general reception by users. The scenario has been received favorably by the users and they all managed to finish it successfully. The VR technology has been evaluated as being almost ready for implementation in real classrooms.

Low-pressure carburising processes are an important element of thermo-chemical treatment in such as the automotive, aviation and/or mechanical engineering industries. The reliability of heat treatment equipment is crucial due to the load placed on them and the possible costs associated with downtime. The value of the damaged charge to be treated, can sometimes exceed the value of the kiln itself. This article presents an analysis of low-pressure carburising processes carried out at a pit furnace with ceramic insulation, with special reference to the accumulation of carbon deposits on heating elements. The accumulation of carbon deposits on heating elements and current feedthroughs can lead to excess voltages and to these heating elements becoming damaged. Based on the research conducted, a procedure for burning out the carbon deposit has been developed, which is an element of the predictive maintenance of equipment for low-pressure heat treatment in carburising processes. Carrying out the procedure is based on data collected by a sensor dedicated to detecting the level of carbon deposits.

The beginning of the 21st century initiated a discussion in the literature on new manufacturing paradigms referred to as Industry 4.0, which are a consequence of the unprecedented development of information technology, supporting various areas of human activity. In 2021, the European Commission announced assumptions for the concept of Industry 5.0, drawing attention to the special role of humans in manufacturing processes. This article discusses the essence of vertical integration in the implementation of the assumptions of mass personalization, which is the essence of Industry 5.0. As part of the research work, aimed at a systematic review of the literature, it has been shown that the strategy of vertical integration and its strengths can be the basis for building an effective policy in a period of turbulent changes, characteristic of the modern market. A special role was devoted to cobotic systems, which are a key element in the effective implementation of vertical integration.

The aim of the paper is to present the concept of integrating an image recognition system based on elements of artificial intelligence with the in-house monitoring system, thus creating an intelligent system for supervising intralogistics transport trolleys. The work also presents a complete methodology for preparing a system using the YOLOv5 model for image analysis and classification. The work also presents the profits from the implementation of new algorithms and new methods of using already existing systems in the company.

The 5th industrial revolution primarily focuses on collaborative robotics, sustainability and artificial intelligence. These main components are focused on the employee and his activities during assembly. Cobots will help employees during assembly, artificial intelligence based on image recognition identifies objects, and the last task that needs to be fine-tuned during assembly is workplace optimization and employee training. This can be achieved using Lean methods (POKA YOKE method, 5S method, SMED method, SPC method and PUSH-PULL method). In this paper, we want to present the creation of a complex training game methodology focusing on using the Poka Yoke method. We describe the step-by-step process of preparing a training game, implementing the Pick-to-Light system, and comparing the proposed game without and with the introduction of the Pict-to-light system. The Lean management training game methodology has significant benefits for preparing students for Industry 5.0, which focuses on integrating digital technologies and automation into industrial processes. The proposed procedure can be used for students‘ and employees’ education in small and medium-sized enterprises.

In this paper, a method for stress measurement of semi-infinite structural is presented based on line-focus acoustic microscopy. Based on the acoustoelastic theory and the superposition of partial bulk wave (SPBW) method, the theoretical model of acoustoelastic surface waves under the uniaxial stress state is established and the effects of stress on the surface wave are investigated for the isotropic semi-infinite structural. Experimental measurements of surface wave velocities under different stress conditions are carried out using an independently developed acoustic microscopy system with a PVDF line focusing probe, and the relationship between stress and surface wave velocity is obtained. Both theoretical predictions and experimental results indicate that tensile stress causes a reduction in surface wave velocity. This research provides a powerful technique for the non-destructive evaluation of thick material. Furthermore, it can be a great tool for the evaluation of stress.

The hydrogen stove pipe is a crucial component of the petrochemical industry, operating at high temperatures for extended periods. Creep cracks, particularly axial cracks in the inner and outer walls, are a common form of damage in these pipes. In this study, the ultrasonic transmission method was utilized to detect creep cracks in the inner wall, while the vertical mutual induction eddy current method was utilized to detect creep cracks in the outer wall. To accommodate actual testing conditions, the specialized fixtures of the transducers, a mechanical structure for crawling on the outer wall, a rotating sweeping mechanism and the multichannel testing mechanism were designed. Additionally, an ultrasonic eddy current control circuit and upper computer control system were developed which can successfully detecting defects in the inner and outer walls of the pipe with exceptional sensitivity and precision. These results have significant implications for improving the safety and reliability of petrochemical operations.

The publication analyzes the concepts of supply chains in the perspective of Industry 5.0. Principles of cooperation of links within the supply chain is crucial to achieve a competitive advantage on a given market. Due to the ubiquitous digitization and globalization, the rules of cooperation within supply chains are also changing. Industry 5.0 concept. it also somehow forces supply chains to be flexible, computerized and digitized in the processes taking place in the supply chain. This article presents three concepts of supply chains based on Industry 5.0. The basis of the research was cooperation with entities from the metal and furniture industry from 2022.

Environmental pollution and its consequences for our planet have led more and more organisations to pay attention to the environmental impact of their products and services. On the one hand, this is due to the requirements of European Union legislation and, on the other, to consumer demands, which further motivates manufacturers to work towards protecting the planet from the harmful effects of their products.There are now a number of tools and methods used to assess environmental impact. Among the most popular tools is the LCA – Life Cycle Assessment analysis, which is used to assess the environmental impact of a product/technology/process. As a result of the LCA technique, business managers are able to identify areas that are a source of environmental or human health burdens [3]. The information extracted from the LCA analysis can be used by the company to, among other things, reorganise the manufacturing and distribution process, redesign the product, replace harmful components with cleaner ones and manage the company in an environmentally friendly manner.This paper performs an LCA analysis for HDPE films, where the main component used for the film production is high-density polyethylene. SimaPro 9.1.1.7 was used for the analysis. The results of the impact of HDEP film technology on the environment were expressed using the ReCiPe Midpoint 2016 eco-indicator.. Based on a life cycle assessment, the environmental effects associated with the HDEP film production technology were estimated, and the impact of the production technology on greenhouse gas emissions was determined.

This paper presents concepts for a chocolate unloading system in the FMCG industry. An analysis of the industry that may be interested in a solution that finds its way into the market has been made. An interview was conducted with a representative of the subject of the study in order to explore the knowledge of chocolate unloading. Based on this information, two concepts were developed. The first was the concept of an added, heated unloading area, which is personalized for the subject of the study. As an alternative solution for the industry, a second concept of a mobile, heated telescopic tunnel was developed. The heat source in both cases can be taken from the room, where the side effect is a high temperature. However, it was pointed out that not all companies have such a room, so a warm air transport system is not considered in the tunnel concept. Two cost estimates and SWOT analyses were prepared for the proposed solutions. The concept of a heated telescopic tunnel proved to be a cost-effective solution, but for safety reasons the concept of an additional unloading area may be more attractive to companies.

The article presents issues related to monitoring the energy consumption of machines and workstations in production processes. Possibilities of designing individualized communication structures and data exchange in the field of distributed production system were emphasized. It was proposed to use advanced meters equipped with communication modules with the possibility of handling data transmission in the wireless Internet network. An exemplary software algorithm for monitoring the energy consumption of selected workstations or machines in the production process was developed.

Nowadays, companies that operate efficiently cover a wide range of different fields of activity, such as finance, logistics, or human resources. Each of the aforementioned aspects produces its own data sets that form the basis for how the company operates. These different fields are often intertwined, requiring data from various modules. This requires the standardization of generated data, leading to the conclusion that one of the most important aspects of running a business is a cooperation between its internal systems. It allows for avoiding inconsistencies in data, which may have very adverse effects, especially for enterprises that operate in multiple fields. Such cooperation is achieved by integrating applications supporting all fields of activity pursued by the enterprise into one cohesive whole. In light of the aspect mentioned above, the article elaborates on the challenges and benefits of said integration, showing it the example of possibilities offered by the SAP environment. Attention was primarily focused on integration between different elements of the finance module which, according to the authors, can deliver the greatest benefits by being combined into a single cohesive whole. An example of JPK-FA file generation, as one of the components of that system, was discussed. The properties of that solution as well as the direct benefits of using that application were discussed. Studies were conducted to demonstrate the speed of the applied technology, which significantly accelerates the operation of the enterprise in the field selected by the authors.

There are many challenges facing organizations. A complex and dynamic environment requires constant change and improvement of activities and reconfiguration of processes carried out in organizations. Market requirements and customer expectations force companies to seek for and apply ever new techniques and solutions. The aim of this article is to present the concept of Throughput Accounting in a production system operating under small batch production conditions as a support for decision-making. This paper also compares the results of using three different costing systems in a resource-constrained manufacturing environment. In contrast to traditional methods that focus on cost reduction, Throughput Accounting is a profit-focused method of achieving goals, based on maximizing throughput.

The article describes the process of creating a risk matrix, as a part of the methodology of risk reduction and analysis. The methodology will be applicable in the development risk analysis of new products in the automotive industry company. It can be used in organizations whose activity is based on running projects linked with each other by a network of dependencies, where each of the company's products is individual, but the course of development is similar. The method uses, among others, a risk matrix, dividing the project development cycle into stages, for which the implementation of progress can be estimated using the project management triangle, and exceeding the set thresholds results in the need to make design decisions. The method may support the management in making quick decisions regarding resource management focused on reducing the existing risk. The matrix will improve the flow of information within the organization, thus enabling quick response to the need to make significant changes that increase the chances of additional profit or reduce the risk of project failure including additional investments, additional budget, search for new suppliers, negotiations with the client, construction of prototype tools.

This article presents the issues related to the corrosion processes occurring in the steel elements from which road machines are made. The types of corrosion processes that occur in metals exposed to an aggressive environment are presented, and the problems of chemical corrosion of metals are also described. Issues related to the methods of corrosion prevention were also presented, with an emphasis on the use of paint coatings. The article characterizes the causes of corrosion problems by the 5xWhy method and the so-called VoC (Voice of Customer) used in the Six Sigma method. Paint coatings are the simplest, most effective, and cheapest way to protect steel elements against an aggressive corrosive environment. The article also characterizes the most typical and most used paint coatings. The article ends with a summary of recommendations for the maintenance and storage of road machines outside the season in which they are used.

Since the 1980s, brown coal mines in Poland have regularly refurbished belts to reduce the purchase of new belts. The importance of belt refurbishment has increased due to rising prices for new belts and longer delivery times. The cost of refurbishment is less than half the price of a new belt, and the mine can continue operating at a nearby remanufacturing facility. Until recently, miners made decisions to remove belts based on the known lifespan of the belt and visual assessment during regular inspections. Currently, a magnetic diagnostic system is being implemented in one of the mines, allowing for a reliable evaluation of the condition of the core with steel cords. It detects changes in the magnetic field around damage to the magnetized cables in the belt core that indicate damage. The program developed for each section determines numerous parameters describing the condition of the belt, such as the number of defects, the density of defects per linear meter or square meter of the belt, the total defects area of the belt section, and the area of the defects per linear or square meter of the belt. The paper compares various metrics of conveyor belt condition, including those based on age (calendar working time and service life as a percentage of expected operating time) and the steel cord belt condition determined by the DiagBelt system (damage density and damage area per 1 m of belt). The research has found that the objective results of measurements of the belt condition provided by the magnetic diagnostic system have a stronger correlation than the indirect metrics based on the age of the belt.

The article describes issues concerning the organization of production and the ergonomics of workplaces. It then describes the organization of the indicated workstation, proposes its improvement, indicates the differences between manual and robotic workplace, their advantages and disadvantages and the problems associated with the improvement of the workstation. The problem that is described in the article concerns the cutting of the material, in this case - PVC poly(vinyl chloride), which up to now has been done by hand. The problems experienced with manual cutting were related to the long cutting time, the monotonous nature of the work, as well as the quality of the cut and the repeatability of the dimensions, as several pieces are to be assembled at the same time, one on top of the other. The problems identified are also very relevant because of the industry of application of these elements. The cut parts are to be used in the chemical industry. As an improvement, an innovative solution was proposed in which this cutting of the components was carried out by means of a laser, mounted on a robotic arm. The laser cuts made on the workstation were carried out on equipment available to the Department of Engineering Processes Automation and Integrated Manufacturing Systems, on Faculty of Mechanical Engineering. The article also describes the construction of such a workstation and identifies the main problems associated with the robotization of such a workstation.

Milling process is complex process in which the multipoint cutting tool has been used to perform the operation. Therefore, it’s very important to monitor the machining responses during operation like tool wear, forces, vibrations and roughness. The article presents the research methodology using a multi-sensor system that allows monitoring the state of the cutting tool in the milling process. Preliminary analysis of the signals recorded from the accelerometer and the microphone show the differences in the signal values for individual cutting layers for individual samples. Changes in the signal values indicate a change in the state of the cutting tool.

Modern companies are operating under economic conditions resulting from the global crisis. This situation forces organizations to constantly look for solutions to increase the efficiency, productivity, and flexibility of processes, including manufacturing. In practice, this means implementing solutions based on the Lean Management philosophy. These solutions aim to eliminate waste in various spheres and areas of business operations. Concerning manufacturing companies and manufacturing processes, wastage includes overproduction, underproduction, downtime, machine breakdowns, maintaining unnecessary inventory, or prolonged search for tools and materials. This article aims to analyze the causes of low OEE indicator and its improvement based on a new model of maintenance and overhaul of the machinery fleet in the example of an automotive manufacturing company. Based on the analysis, observations, and interviews with employees documented: the calculation of production capacity calculation of the number of correctly produced strips in the period before the introduction of the new plan for maintenance and overhaul of the equipment used on the KP production line, calculation of the OEE indicator for the entire production process on the KP line, creation of a list of failures occurring at the building and vulcanizing stations, as stations constituting a bottleneck in the production process, calculation of the OEE indicator for machines at the building and vulcanizing stations, categorization of machines and creation of a new model for maintenance and overhaul of the equipment used on the KP production line.

The paper discusses issues related to hydropneumatic suspension units (HSU), which are the basic element of suspension in tracked vehicles. The first chapter presents the basic functions of the suspension in this type of vehicles and its advantages and disadvantages. It was presented why the progressive characteristics of the hydropneumatic suspension unit are important. The second chapter presents current design solutions in the construction of a hydropneumatic suspension unit and discusses the construction of suspension in tracked vehicles. The importance of the hydraulic damper was presented on the example of the pressure drop characteristics depending on the flow. A detailed analysis of the operation of the hydropneumatic suspension unit was also carried out, considering the work of individual HSUs on a tracked vehicle. In the third chapter, it was pointed out that the current design of the HSU basically does not allow for the identification of its efficiency. The need to develop a system for predicting emergency states was confirmed. The article discusses important assumptions that should be met by the system for predicting emergency states of control arms. In the following part, the concept of the system for detecting emergency states by measuring the oil pressure in the hydro-pneumatic HSU is presented. It has been proven that the registered pressure drop in the oil chamber in the static position of the hydropneumatic suspension unit may be a parameter indicating a failure of this element. Finally, a possible way of installing a pressure transducer was presented, and an algorithm was developed that could be the basis for the operation of the system for predicting emergency states.

AI as a part of Industry 4.0 moved forward and provide some opportunities for business to integrate it into day-to-day tasks, it can be used to provide automated chat services to customers or copyrighting for goods of the store. Meanwhile the opportunities of using AI, there might be some challenges, which we are describing and analyzing in the article. For example, there are concerns about data privacy and security, as well as the potential for job displacement as AI technologies become more advanced. Additionally, there may be ethical concerns surrounding the use of AI, particularly in the area of customer service. In conclusion, while ChatGPT and other AI technologies present significant challenges to the business world, they also offer tremendous opportunities for growth and success in Industry 4.0. Therefore, it is important for businesses to carefully consider the potential benefits and risks of implementing AI technologies and to develop appropriate strategies for incorporating them into their operations. The purpose of the article is to explore the role of artificial intelligence management in Industry 4.0 and determine whether it represents a challenge or an opportunity.

This paper explores the role of Design Thinking in Industry 4.0 and its impact on innovation in industrial companies. The importance of innovation in the manufacturing industry, particularly in the context of Industry 4.0 and the corresponding need to explore the role of Design Thinking in Industry 4.0 and its potential to boost innovativeness in new products and services is discussed. Design thinking encourages collaboration and experimentation, enabling companies to address complex challenges and develop solutions aligned with user needs. Design thinking, with its user-centred approach and emphasis on collaboration and problem-solving, can drive innovation in this context. By applying the stages of the design thinking process, such as empathizing, defining, ideating, prototyping, and testing, companies can develop user-centred product designs, optimize industrial processes, and facilitate digital transformation. Overall, design thinking offers a valuable methodology for industrial companies to enhance their innovativeness and thrive in the competitive landscape of Industry 4.0. This paper explores the practical application of Design Thinking in the context of Industry 4.0. It discusses how Design Thinking can be used in various areas, including product design, process optimization, service design, and digital transformation. The paper highlights the importance of understanding user needs and behaviours, involving stakeholders, and creating user-centred and innovative solutions by presenting several industrial case studies.

The article presents an automated assembly station designed by students as part of Project Based Learning. The task of the project was to familiarize with the issues of integration of automation and control elements operating in various standards in order to implement the idea of Industry 4.0. The main elements of the station are the Astorino educational robot, gripper, servo drive and other professional elements of industrial automation and IoT systems. Raspberry PI, microcontrollers, etc. are also used. The assembly process of the product in the configuration in accordance with the user’s order is carried out at the station, quality control is carried out during the process using a vision system and various sensors.

The thematic scope of the work includes issues of power hydraulics, energy efficiency and safety of machines as well as issues of devices for construction works of large-size structures. The project is implemented in a joint doctoral school and the PONAR Wadowice company as part of the 6th edition of the “Implementation Doctorate” program. The purpose of the work is to create an energy-saving, modular hydraulic device that increases work safety and reduces the labor intensity of the process of building large-size structures in field conditions. Paper consist the concept of implementing a new technical device. When lifting the structure, the hydraulic system maintains a constant oil flow rate with dynamic pressure changes, maintaining the synchronous movement of the actuators. After reaching a predetermined level, the device must support the entire structure so that construction workers can start the next stage of construction. The designed device, under which research is in progress, would comprehensively support construction companies and actually increase the safety of performed works. The device is powered by a diesel power generator, an important aspect of research work will be the reduction of CO2 emissions by increasing the efficiency of the device and increasing the precision of work. The advantage of the project is its complexity. Optimization of the design in terms of product life cycle, durability and ergonomics.

The objective of this research article is to present the experimental analysis methods and observations for 3D-printed polylactic acid (PLA) samples. In this study, tensile tests have been employed to characterize the anisotropic behavior of the 3D-printed PLA samples. To evaluate the directional characteristics of the materials, the samples were built with various build directions, including flat, on-edge, and up-right, as well as with various build orientation angles ([+45°/−45°], [+30°/−60°], [+15°/−75°], and [0°/90°]). In order to collect the required mechanical characteristics, the tensile samples were loaded into a universal testing machine. This study looked at how the mechanical characteristics of PLA were affected by altering the printing direction and orientation angles. The objective is to assess how altering the raster angle will affect the mechanical characteristics throughout the characterization procedure. The current investigation evaluated the mechanical properties of Fused Filament Fabrication (FFF) printed samples. The tensile tests conducted on samples fabricated in various orientations revealed that PLA (50% filling density) with a flat building direction and a building orientation angle of 75° exhibited the highest tensile load. This study analyzed the fracture surface of the tensile samples and investigated the impact of varying the raster angle and direction on the mechanical properties of 3D-printed parts. The comprehensive tensile testing conducted in this article highlights the importance of conducting tension testing to gain a complete comprehension of the behavior of 3D-printed materials.

The purpose of this paper was to present a methodology of samples preparing process for needs of experimental research of 3D printed samples made of PLA. The main objective of the research was to study specimen’s behavior whilst conducting tensile tests. The idea behind of the research was to investigate the influence of different part printing directions such as flat, on-edge, and up-right, and different printing orientation angles from the set of {(+45°/–45°), (+30°/–60°), (+15°/–75°), (0°/90°)} on mechanical properties of the parts. The second stage of the developed methodology was testing of the specimens on the universal testing stand in order to get the necessary mechanical properties, descripted in the second part of the paper. As mentioned above it allowed to investigate the influence of the printing direction and orientation on the mechanical properties of specimens made of PLA. The aim was to evaluate the outcome of changing the raster angle on the mechanical properties for the characterization process. The present research evaluated the mechanical properties of FFF printed samples. The tensile tests conducted on samples fabricated in various orientations revealed that PLA samples of 50% filling density with a flat building direction and a building orientation angle of 75° exhibited the highest tensile load. This study also analyzed the fracture surface of the tensile specimens and examined the impact of different raster angle and direction on the mechanical properties of 3D-printed parts. The comprehensive tensile testing carried out in this paper highlights the importance of conducting tension testing to gain a complete comprehension of the behavior of the parts manufactured with FFF manufacturing technique.

The paper deals with the assessment of the effectiveness of resource management in production processes. Effectiveness evaluation methods in the production area focus mainly on loss analysis. Therefore, the identification and categorization of losses affecting effectiveness can serve as a base when using (or even developing new) methods of effectiveness evaluation. The main purpose of the work was the identification and categorization of the production losses that affect the effectiveness of disposing the resources necessary for the implementation of production and near-production processes. The identification of the losses of availability, performance and quality (which are coefficients of the effectiveness indicator) was made on the basis of research conducted in cooperation with production enterprises of different sizes and of different areas of production. Losses in the availability, performance and quality of the areas of production, logistics, maintenance, and organization and management were identified. Based on the categorized losses, a worksheet was also developed to support the collection of data in order to estimate the effectiveness indicator for different areas of production.

Risk is inherent in any activity, including manufacturing. The engineers face various factors of risk while managing the production processes, such as accidents, breakdowns, defective parts and much more. Despite the increasing automation of production processes, many activities are still performed with human assistance. The management of human resources, including the scheduling of operators, is - like any other activity - associated with the risk of the emergence of sudden needs for change, usually related to random causes. Risk assessment is a complex task, requiring a holistic approach and the ability to analyze the situation in terms of both past events and the future. In the article, the aim was to verify the possibility of applying the fuzzy logic in this kind of risk assessment. To achieve this, the combination of classic risk assessment method FMEA and the fuzzy sets rules was used, which is called the fuzzy FMEA. It is the combination of two aspects which is getting more and more popular in literature. The research was performed based on data collected in industry.

The article deals with the subject of production scheduling in 3D printing systems. In the era of incremental technologies gaining in popularity, the creation of printer farms, it becomes very important to effectively use such systems in terms of throughput, timely execution of orders, selection of staff with the right number of appropriate competences. 3D printing systems are a specific subgroup of production systems with certain features, limitations, and work organization methods. Thus, the general characteristics of such systems are presented, and the most important features of the model from the point of view of effective task planning are identified. Due to the obligatory participation of human resources and clear disproportions in the length of the duration of individual operations in subsequent stages of the process, the model includes the issue of a varied working time calendar for individual groups of resources. It was proposed that the printing system should work in three shifts and the operators in one shift. An algorithm for creating packages was proposed, in which the batch size is determined directly at the scheduling stage, enabling the system to work in such conditions with the best possible use of resources - 3D printers. The description of the algorithm is illustrated with an example in which the advantages of the system operation are shown on the basis of a schedule prepared using the developed algorithm and a typical way in which the printers work with the maximum filling of the print area.

The conveyor belt offers high performance for continuous material transport from one point to another as an economical transportation device. The rubber belt is the core element in the conveyor belt system and for the optimized use and maximized service life, it has to be observed and maintained as it passes through destructive forces constantly while carrying the material on it. The study of the damage done to the rubber belt and its responsible forces can contribute to controlling and implementing the favorable conditions where the service life of the rubber belt is maximized, which is the overall aim of the chosen research goal. The research goal of presented article is to use the Ishikawa diagram to enlist and categorize the potential causes of damage done to the CB. The recorded and magnetic scanned (DiagBelt + system) data of the past events at the mining site can help in such a study where influenced and influential parameters can be identified using statistical analysis and then followed by machine learning algorithms to identify hidden inter-dependencies within a multivariate system where two distinct sets of variables which are affecting each other during the production process. The presented article is an approach which outlines the possible quantifiable and non-quantifiable parameters which are influencing the wear occurring in the rubber belt operating at the coal mining site. Subsequently, the mentioned quantifiable parameters can be used in the dataset and the controllable non-quantifiable parameters can be countered by removing bottlenecks and overlooked operating conditions at mining sites.

The paper presents the concept of risk analysis and assessment in production systems. Due to the complexity of production systems, their complexity and the high degree of integration of individual functional areas, the presented concept assumes the possibility of dividing risk factors into categories. The categories correspond to the functional areas of an enterprise. The Ishikawa diagram and the 4M (machine, material, method, man) categorization were used to determine the categories. According to the concept presented in the paper, risk factors occurring in a production system were assigned to each category. This assignment made it possible to determine the amount of losses in the production system caused by the occurrence of risk factors in individual areas of the production system. Variant simulations and simulation models specially built for this purpose were used to assess the risk of the production system. The results obtained from the experiments on simulation models allowed to determine the time increments and the amount of losses caused by the occurrence of risk factors in individual functional areas of the system. The presented concept was verified on the example of the steel bolster body production process. The data used for the verification comes from the real production process.

When designing technical systems, one of the most important tasks is to determine their operating parameters in target conditions. Most often, these are model activities aimed at conducting tests on model systems or prototypes of the analyzed systems. Conducting such research also involves their proper analysis. This publication presents a solution proposed for such situations. The publication presents an example of testing a hydraulic system at low temperatures, as well as an analysis of test results and a determination of the scope of objectives based on the weighted Ishikawa diagram. The system was tested at −50 ℃ and problems were identified at this temperature. Operational problems at such a low temperature were then analyzed using a 10M fishbone diagram. The obtained results allow both to define further research procedures and to set further research directions. They also allow for the assessment of interactions between identified problems.

Performance evaluation is the critical method for supply chain management in any industrial sector in order to maintain competitiveness. Subcontractors are important for producing parts to the Tier 1 companies and OEM under the same standardization and delivering the parts on the purchasing schedule. Therefore, the subcontractors need to improve capability, quality and productivity in the level that is accepted from customers. In automotive rubber part supply chain, it includes OEM, Tier 1 companies and Tier 2 companies in order to share resources, information and technology for the whole cluster. This paper proposes the performance evaluation model using ANFIS system to deal with uncertainty and responsiveness. Three major dimensions are measured based on actual sample factory model. They are delivery on time, back order clearance, and quality. The performance evaluation can be evaluated anytime while demands are being changed in order to optimize supplies of the sub-contractors.

Energy evaluation is important for any manufacturing company to stand for competitiveness. Rubber part industry consumes much energy to deform raw material into finished parts and working in long period of time. It performs 2 shifts more than 20 h with high current and working parallel with multi-stage and many machines. Energy saving can control is needed both for economy and sustainability. Therefore, energy assessment is indispensable to improve productivity and efficiency. This paper purposes the energy assessment using FMEA and weight FAHP in the rubber part manufacturing company for automotive industry. FMEA takes the uncertainty and risk parameters before feeding forward into the FAHP before weighting to become Weighted FAHP to obtain the priority of energy consumption and enable apply methodology and control correctly and effectively. The case study is discussed in details.

The study introduces an innovative approach to address the scheduling challenges encountered in the automotive industry’s multi-variant production processes. It focuses on optimizing task assignments among employees with diverse competencies to minimize the overall production time. Managing employee work effectively becomes crucial due to limited workforce availability, directly impacting production timelines, meeting contractor requirements, and achieving measurable savings. To tackle this, the research employs various local search algorithms, including Tabu Search, Simulated Annealing, and Descending Search. Additionally, the study introduces the integration of a neural network as an augmenting element within Tabu Search algorithm, aimed at alleviating constraints and analyzing potential benefits in production optimization.

Bus body structure has been widely made in Thailand using MIG welding process while quality is uncertain and inconsistent because of heat accumulation and skill of labor. Presently, robotic welding is utilized to improve efficiency and productivity as well as quality. The robot is interfaced with welding machine by their controllers. Therefore, welding process with proper parameters is controlled by robot routing as well as the heat accumulative can be control by the robotic welding process control. In general, the weld line is inspected by destruction or non-destruction. However, such approach is expensive and time consuming. This paper proposes an effective methodology to predict the weld line stiffness based on the parameters used on the MIG welding robotic process using ANFIS modeling. Collection reference data and expert rules are the major concerned and converted into fuzzy rules.