Production Line Research Articles

Virtual Simulation and Experiment of Quality Inspection Robot Workstation

(1) Background: Quality inspection robots are widely used in automated production lines. However, the design cycle is long, iteration costs are high, and algorithm development is challenging. It is difficult to perform effective validation during the design phase. Applying virtual reality technology to simulate quality inspection robot workstations offers a new approach to addressing the issues. (2) Methods: The research creates a simulation platform for quality inspection robot workstations based on a virtual reality architecture. The platform creates an immersive quality inspection robot workstation operation interface and conducts testing of the inspection process, thereby validating the rationality of the quality inspection robot workstation design. Building upon this foundation, we conducted experimental comparisons of various defect detection algorithms. (3) Results: Compared to the traditional YOLOv7 algorithm, the improved YOLOv7 algorithm achieved an 18.1% increase in recognition precision. Experimental results demonstrate that the quality inspection robot workstation simulation platform can be applied to validating workstation design proposals. (4) Conclusions: It has a positive impact on reducing the research and development costs of quality inspection robot workstations and shortening the defect recognition algorithm development cycle.

A Configuration Management Strategy for Modelbased Product Line Engineering in Aircraft Systems Development

AbstractAircraft systems development is complex and time‐consuming. Model‐based Product Line Engineering (MBPLE) aims to reuse assets between projects to accelerate the development of systems at their early stage. Despite guidance from standards, MBPLE practitioners still face the challenge of deploying an appropriate configuration management strategy. This paper presents and demonstrates a configuration management strategy to support practitioners deploying MBPLE for aircraft systems development. We developed this strategy to comply with ISO/IEC 26580 and address pending standard ambiguities using best practices from product lines for systems, software, business processes, and systems of systems. The proposed strategy supports long‐term product line evolution, management of different asset types, and independent product environments.

Hyundai's Modular MBSE Approach to ‘Purpose Built Vehicle’ Architecture Development

AbstractThis paper discusses an ongoing effort at Hyundai to develop a model‐based systems engineering (MBSE) methodology for cross‐domain vehicle architecture development that is practical at the enterprise level. Our approach follows a modular modeling process that complements MBSE. In the age of smart mobility, automobile systems are indeed interdependent elements of a system of systems (SoS). Connectedness favors numerous mobility features that emerge due to the interfaces among these constituent systems. Managing emergent product line variations, changing consumer demands coupled with faster market response require manufacturers to modularize their architecture development processes. This can help scale MBSE across vehicle programs. This study proposes a modular system architecture approach for developing Hyundai's purpose‐built vehicle (PBV) concept that maintains a link to the legacy vehicle breakdown structures already in use. Using the Arcadia method, the ‘to‐be’ developed electric vehicle is expressed as a hierarchical functional partitioning of the subsystem modules. A physical architecture is defined as a solution to the functional partitioning based on an existing vehicle breakdown in a combined ‘top‐down/bottom‐up’ workflow thus capturing a realistic system decomposition. In the SoS hierarchy, the PBV is at the top level and is partitioned into multiple levels of nested subsystem architectures owned and developed by designated module teams in a distributed modeling environment. Results of the preliminary architecture modularization effort indicate significant potential for benefits over classical architecture modeling such as iterative knowledge capture, enhanced reusability across projects, products and programs, and distributed vehicle performance development across the extended MBSE enterprise, which includes the tier 1/2 suppliers.

The artfulness of historical playwriting in Richard III: Shakespeare and English Tacitism

Art seems to be especially fruitful as a starting point for a re-reading of Shakespeare's Richard III as an example of an English history play that is more commonly understood in terms of nature or politics. Richard's reputation for being unnatural, that is physically and morally deformed, certainly makes nature a productive line of enquiry. Politics is also immediately relevant to a play about Richard III, whose demise marked the rise of the Tudor dynasty. However, I have chosen to consider the artfulness of Richard III to show how Tacitism informed Shakespeare's approach to historical playwriting.

Collision Avoidance and Give Way of Heterogeneous and Variable-Sized Multiple Mobile Robots Based on Glued Nodes

Multiple mobile robot systems (MMRSs) play an important role in workshops, storage and other scenarios. A complex MMRS can contain heterogeneous robots, and even the robot sizes are not fixed, making it more difficult to avoid collisions. As a widely studied method, the zone-controlled method is not accurate enough for a system with heterogeneous and variable-sized robots, and it increases the difficulty of applying MMRS. Based on the concept of glued nodes, this paper proposes a more accurate calculation method than the zone-controlled method to avoid collisions among heterogeneous and variable-sized robots. In order to improve the efficiency of calculating glued nodes, this paper proposes a time-to-space method, which has a constant complexity after the system runs long enough. In addition to collision avoidance, this paper also studies the problem of giving way of idle robots. This paper proposes a method which can detect those idle robots blocking the working robots and plan paths for the idle robots to find avoidance nodes to give way to the working robots. Simulation experiments are carried out based on a real automated production line scenario, and the experimental results prove the effectiveness and efficiency of the proposed methods. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In a complex MMRS, the size of different robots can be different, and even the size of a robot is different when loaded and unloaded. One of the motivations of this paper is to avoid collisions in such a complex MMRS. A collision avoidance method is proposed to avoid collisions among robots by allocating nodes in real time. At the same time, this paper also addresses the problem of idle robots blocking working robots. If an idle robot blocks some working robots, an avoidance node will be found for the idle robot to give way to the working robots. The methods proposed in this paper can be applied to the roadmap of any structure. This means that in a scenario, regardless of the structure of roadmap and the different sizes of robots, the methods can be applied directly. The methods have been applied to many practical industrial projects in warehousing, manufacturing and other scenarios, and greatly reduces the difficulty of applying MMRS. In future research, there is a need to improve the efficiency of the methods so that they can be applied to a large-scale system.

UVLHub: A feature model data repository using UVL and open science principles

Feature models are the de facto standard for modelling variabilities and commonalities in features and relationships in software product lines. They are the base artefacts in many engineering activities, such as product configuration, derivation, or testing. Concrete models in different domains exist; however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serializing feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents ▪ , a repository of feature models in UVL format. ▪ provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo – one of the most well-known open science repositories – providing a permanent save of datasets and following open science principles. ▪ includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling.

Research and design of automatic cutting machine for propellant NDSI-2K and FCG-2.B41M

This article introduces the results of research on a new solution in the process of cutting and selecting propellants used for the double-based tubular propellant production line of Factory Z195/General Department of Defense Industry. The traditional method is usually manual, using the foot pedal force of the worker through a mechanical drive system to pull the cutting knife down to cut the propellant. It takes a lot of time, labor and product quality is not high. After cutting it is necessary to lathe the ends of propellant tube to meet technical requirements. With the new solution, the propellant is cut automatically, quickly, safely and accurately and the selection of the propellant is carried out through a weighing conveyor system based on the principle of classification by weight. The entire working process is controlled by a sensor systemand PLC programerthrough a monitoring computer located in the control room. Processing data can be stored and periodically exported for report purposes.

Japanese Prefabricated Housing Manufacturers

Japanese prefabricated housing manufacturers have gained international recognition for their innovative approaches to the whole design process, ranging from initial design to innovative cutting-edge technologies, state-of-the-art automated production lines, meticulous workmanship, and mass customisation. In this entry, three manufacturers (Daiwa House, Sekisui House, and Misawa Homes) were selected as case studies for close examination. By studying these leading companies, researchers and industry professionals can gain valuable insights into best practices, challenges, and innovations within the Japanese prefabricated housing sector. The research methods involved a desktop study of available information on websites, articles, and reports, as well as undertaking two study tours on residential sustainable design in Japan in 2022 and 2023. These three manufacturers were discussed and compared with respect to their development trajectories, design customisation, research capabilities and technological advancements, sustainable initiatives and procurement, as well as their after-sale services. They have demonstrated their adaptability and flexibility in response to natural disasters and the transformation of the needs in society. They are all keen on reducing the environmental impacts of their work towards zero carbon emissions and a sustainable future.

Production Floor Relayout to Optimize Material Handling Distance at PT. Sidoagung Farm Magelang

PT. Sidoagung Farm Magelang is one of the industries engaged in animal feed. The problem in this company is the arrangement of machines per department on an irregular production line, so that the interrelated production processes are quite far apart. Machines that have the same function and are far apart include: corn grinding machine and soybean grinder 9 meters apart, mixer machine 1, mixer machine 2 and mixer machine 3 each 1.5 meters and 18 meters apart, packaging 1 and packaging 2 is 27.4 meters away. In order to overcome these problems, this study proposes a method to optimize distance using a Group Technology approach, namely the Rank Order Clustering (ROC) method for grouping machines with similar parts. The design of the proposed layout uses Blockplan Software and the calculation of the distance with the rectilinear formula. The results of this study resulted in 3 grouping machines. Group 1 grinding machines are 1 meter apart, group 2 mixer machines are 1 meter apart each, group 3 packaging machines are 1.5 meters apart. The total displacement of the material handling distance using the rectilinear formula in the initial layout is 191 meters, while for the displacement of the material handling distance, the proposed layout is 117.5 meters. With the comparison of the initial and proposed layout distance is 73.5 meters so that the proposed layout optimizes the distance between machines by 62%.

Maintaining the good store: lessons about caring practices from Swedish 100-year-old retail stores

ABSTRACT This article is about small-scale independent single-store retailers that have been in business since the first half of the 20th century – an overlooked group of actors in retail research. Research has mapped the broader structural changes in the retail industry that have benefitted large-scale operations during the last decade. Still, there is an absence of explanations for the continuous existence of small-scale retail businesses with product lines competing with large-scale actors. Retail research tends to take economic profitability and growth as starting points to interrogate the capacity of businesses to successfully compete. Against this background, the longevity of inner-city small-scale independent stores dating back to the early 20th century remains a puzzle, which calls for looking towards alternative theories to find reasons for the persistence of this line of retail. We engage with this puzzle by exploring practices of valuation engaged by store owners in a selection of small-scale, independent stores established in Gothenburg and Stockholm (Sweden) before the 1950s. We draw on understandings of values as produced through social practices and inquire how forms of caring practices figure in the day-to-day maintenance of the stores as means through which they produce value. The article builds on ethnographic fieldwork focusing on in-store interviews with store owners, employees, and customers complemented with observations. We find that care figures in these stores as expressions of attention and presence, of maintenance and of tacit knowledge, and suggest that the retailers’ focus on the caring practices identified – rather than on prioritizing growth – is key to their continued, long-term existence. Anchored in an understanding of retail as situated in broader social and political processes, and as such also impacting society at large, we moreover emphasise the importance of attentiveness and valuation of, the caring practices that small-scale store owners engage in.

Expert Twin: A Digital Twin with an Integrated Fuzzy-Based Decision-Making Module

Digitalization and the application of modern Industry 4.0 solutions are becoming increasingly important to remain competitive as product ranges expand and global supply chains grow. This paper presents a new Digital Twin framework to achieve robustness in manufacturing process optimization and enhance the efficiency of decision support. Most digital twins in the literature synchronously represent the real system without any control elements despite the bidirectional data link. The proposed approach combines the advantages of traditional process simulations with a real-time communication and data acquisition method using programmable logic controllers designed to control automated systems. In addition, it complements this by utilizing human experience and expertise in modeling using Fuzzy Logic to create a control-enabled digital twin system. The resulting "Expert Twin" system reduces the reaction time of the production to unexpected events and increases the efficiency of decision support; it generates and selects alternatives, therefore creating smart manufacturing. The Expert Twin framework was integrated, tested, and validated on an automated production sample system in a laboratory environment. In the experimental scenarios carried out, the method production increased production line utility by up to 28% and the number of re-schedules can be halved.

Advanced Monitoring of Manufacturing Process through Video Analytics.

The digitization of production systems has revolutionized industrial monitoring. Analyzing real-time bottom-up data enables the dynamic monitoring of industrial processes. Data are collected in various types, like video frames and time signals. This article focuses on leveraging images from a vision system to monitor the manufacturing process on a computer numerical control (CNC) lathe machine. We propose a method for designing and integrating these video modules on the edge of a production line. This approach detects the presence of raw parts, measures process parameters, assesses tool status, and checks roughness in real time using image processing techniques. The efficiency is evaluated by checking the deployment, the accuracy, the responsiveness, and the limitations. Finally, a perspective is offered to use the metadata off the edge in a more complex artificial-intelligence (AI) method for predictive maintenance.

Prediction of Operational Noise Uncertainty in Automotive Micro-Motors Based on Multi-Branch Channel–Spatial Adaptive Weighting Strategy

The acoustic performance of automotive micro-motors directly impacts the comfort and driving experience of both drivers and passengers. However, various motor production and testing uncertainties can lead to noise fluctuations during operation. Thus, predicting the operational noise range of motors on the production line in advance becomes crucial for timely adjustments to production parameters and process optimization. This paper introduces a prediction model based on a Multi-Branch Channel–Spatial Adaptive Weighting Strategy (MCSAWS). The model includes a multi-branch feature extraction (MFE) network and a channel–spatial attention module (CSAM). It uses the vibration and noise data from micro-motors’ idle operations on the production line as input to efficiently predict the operational noise uncertainty interval of automotive micro-motors. The model employs the VAE-GAN approach for data augmentation (DA) and uses Gammatone filters to emphasize the noise at the commutation frequency of the motor. The model was compared with Convolutional Neural Networks (CNNs) and Multilayer Perceptrons (MLPs). Experimental results demonstrate that the MCSAWS method is superior to conventional methods in prediction accuracy and reliability, confirming the feasibility of the proposed approach. This research can help control noise uncertainty in micro-motors’ production and manufacturing processes in advance.

Comparative characteristics of the morpho-biophysical qualities of meat quail eggs

In 2023, more than 140 million units were produced in Russia. quail eggs, i.e., one egg per person per year. In this segment, the country is significantly inferior to many countries with developed poultry farming. But demand creates supply and in recent years the production of quail eggs has been intensively increasing, the share of which in the total balance of produced food eggs is 0.3% and is gradually growing. New breeds, crosses and lines of both egg and meat productivity are appearing. The purpose of the study was a comparative analysis of the morpho-biophysical qualities of eggs from the white Texas and Pharaoh meat breeds. However, there is practically very little information about the quality of eggs obtained from such breeds, despite the fact that the eggs are widely used both for incubation and in human nutrition. Therefore, the study of the morpho-biophysical qualities of quail eggs for meat production is not only relevant, but also of high practical importance. It was found that the weight of eggs of the Pharaoh breed was 8.5% higher compared to eggs of the white Texas breed, and the egg shape index was almost 3% lower. A comparison of the indicator characterizing the quality of protein in the studied breeds showed that the indicator of Hau units of Texas quail breed eggs was 88.74 and exceeded this indicator for Pharaoh eggs by 5.02%. In general, it should be said that the morpho-biophysical qualities of Texas white eggs were significantly different from those of the Pharaoh breed.

Integrating Natural Deep Eutectic Solvents into Nanostructured Lipid Carriers: An Industrial Look.

The industries are searching for greener alternatives for their productions due to the rising concern about the environment and creation of waste and by-products without industrial utility for that specific line of products. This investigation describes the development of two stable nanostructured lipid carriers (NLCs): one is the formulation of a standard NLC, and the other one is the same NLC formulation associated with a natural deep eutectic solvent (NaDES). The research presents the formulation paths of the NLCs through completeness, which encompass dynamic light scattering (DLS), zeta potential tests, and pH. Transmission electron microscopy (TEM) and confocal microscopy were performed to clarify the morphology. Cytotoxicity tests with zebrafish were realized, and the results are complementary to the in vitro outcomes reached with fibroblast L132 tests by the MTT technique and the zymography test. Infrared spectroscopy and X-ray diffractometry tests elucidated the link between the physicochemical characteristics of the formulation and its behavior and properties. Different cooling techniques were explored to prove the tailorable properties of the NLCs for any industrial applications. In conclusion, the compiled results show the successful formulation of new nanocarriers based on a sustainable, eco-friendly, and highly tailorable technology, which presents low cytotoxic potential.

SYNTHESIS OF NARMA-L2 NEURAL CONTROLLER FOR TRACTION INDUCTION ELECTRIC DRIVE SYSTEM

In today's world, where technology is developing rapidly, electric drive systems play a key role in a huge range of applications: from industrial production lines to vehicles and household appliances. These systems require high efficiency, accuracy and reliability. It is here that there is a need to improve and optimize the processes of controlling electric drives.In recent decades, neural network controllers, or neuroregulators, have won their place in the world of automatic control. Their unique ability to model complex nonlinear dependencies makes them an ideal tool for applications in electric drive systems. Neuro-regulators can adapt to changing operating conditions, learn from data and optimize the control process depending on specific requirements and conditions.This work is devoted to the possibility of using a neuroregulator in the traction asynchronous electric drive system. In the Matlab/Simulink environment, a simulation model of the AD914-U traction asynchronous electric motor vector control system described in the d,q rotating coordinate system was developed. The synthesis of the NARMA-L2 neuroregulator was performed, which combines the principles of the autoregressive model and the moving average model to provide prediction and control of complex processes. The main idea of this controller is to build a nonlinear transformation of input data that can predict the future states of the system. To demonstrate the capabilities of neuroregulators in traction electric motor control systems, comparative modeling of the NARMA-L2 neuroregulator and the classical proportional-integral regulator was conducted.The results of simulation modeling show that the system with a neuro-regulator shows the best indicators of regulation of the given parameters in transient processes and is a promising tool in the development of high-performance and energy-efficient traction electric drives.

EXPERIENCE OF MODERNISATION OF SORTING TABLES AT THE FLAX PLANT

Modern flax mills are equipped with new production lines for short and long fibres. In particular, the Belgian company Depoortere supplies such lines of various capacities. The equipment allows for continuous processing of flax, complete cleaning of flax seeds. Standard sorting tables are used for sorting flax (manually by length and colour). At the same time, back in the 1980s, based on the modernisation of standard sorting tables, original designs of experimental sorting tables equipped with aspiration devices were created and tested in production conditions. In this paper, an experimental conveyor table with a perforated surface is considered, equipped with a device for removing air contaminated with dust particles. An experimental table with a two-sided arrangement of workplaces with the function of localisation and removal of dust in the process of sorting long flax fibre is presented. The results of testing of experimental tables at Palekh flax plant, comments and suggestions from the employees of the flax plant regarding the design of the tables are presented. The designs of experimental tables equipped with aspiration devices, have significant advantages in comparison with standard tables, can be adapted to modern lines installed at flax plants.

Planning of multi-production line maintenance

Efficiency of production lines is significantly impacted by maintenance activities, which are often overshadowed by the focus on production planning. The symbiotic relationship between maintenance and production activities is a critical yet overlooked factor. We examine the importance of maintenance planning, specifically within the dynamic context of production line operations. In this maintenance planning setting, scarce resources, particularly technicians, are commonly disregarded. Our research addresses the challenge of real-time maintenance planning across multiple production lines by developing a state-of-the-art heuristic, which takes into account machine production states and resource availability and is augmented by re-enactment procedures. We validate the heuristic by employing Markov Decision Processes and digital twin Discrete Event Simulations, which leverage real-world production data. This modeling framework is new for this specific problem. In our experiments, we compare the heuristic against optimal policies and practitioner-based policies. Our heuristic matches the performance of optimal policies in the Markov Decision Processes and significantly outperforms FCFS and practitioner-based policies in the Discrete Event Simulations. Notably, our heuristic is not only effective against standard policies, realizing improvement of 1% to 3%, but it is also the first to be generally applicable to production lines involving multiple machines and resources in real-time.

Automated Shape Correction for Wood Composites in Continuous Pressing

The effective and comprehensive utilization of forest resources has become the theme of the global “dual-carbon strategy”. Forestry restructured wood is a kind of wood-based panel made of wood-based fiber composite material by high-temperature and high-pressure restructuring–molding, and has become an important material in the field of construction, furniture manufacturing, as well as derivative processing for its excellent physical and mechanical properties, decorative properties, and processing performance. Taking Medium Density Fiberboard (MDF) as the recombinant material as the research object, an event-triggered synergetic control mechanism based on interventional three-way decision making is proposed for the viscoelastic multi-field coupling-distributed agile control of the “fixed thickness section” in the MDF continuous flat-pressing process, where some typical quality control problems of complex plate shape deviations including thickness, slope, depression, and bump tend to occur. Firstly, the idea of constructing the industrial event information of continuous hot pressing based on information granulation is proposed, and the information granulation model of the viscoelastic plate shape process mechanism is established by combining the multi-field coupling effect. Secondly, an FMEA-based cyber granular method for diagnosing and controlling the plate thickness diagnosis and control failure information expression of continuous flat pressing is proposed for the problems of plate thickness control failure and plate thickness deviation defect elimination that are prone to occur in the continuous flat-pressing process. The precise control of the plate thickness in the production process is realized based on event-triggered control to achieve the intelligent identification and processing of the various types of faults. The application test is conducted in the international mainstream production line of a certain type of continuous hot-pressing equipment for the production of 18 mm plate thickness; the synergistic effect is basically synchronized after 3 s, the control accuracy reaches 30%, and the average value of the internal bond strength is 1.40, which ensures the integrity of the slab. Practical tests show that the method in the actual production is feasible and effective, with detection and control accuracy of up to ±0.05 mm, indicating that in the production of E0- and E1-level products, the rate of superior products can reach more than 95%.

Reduction of Setup Times in a Metal Fabrication Company Using a Lean-Sigma Approach

Manufacturing companies face demand fluctuations and must deliver the required quantity of parts to their customers within the required time; however, companies face different challenges in fulfilling them. One is technological advances, which make it impossible for them to compete with other countries, such as China, due to financial issues. Therefore, manufacturing companies use continuous improvement methodologies to achieve better performance in their processes. Six Sigma and Lean Manufacturing are some of the best-known approaches. This article briefly presents the application of a lean sigma approach oriented to solving problems. This research proposes a methodology based on Lean Sigma that contrasts what different authors currently do: continuous improvement projects that take up to 12 months to produce results and do not solve a problem. This implementation is conducted in a process that manufactures metal parts and fails to deliver them on time to its customers. Using tools such as the Single Minute Exchange of Die (SMED) in a production line, on-time deliveries were increased from 89 % to 96 %; at the same time, the model change times were reduced by approximately 60 %, which is required for the implementation of this methodology for only four weeks, unlike the traditional six-sigma approach that can take up to 12 months to improve the process.