Product Assembly Research Articles

Analisis Beban Kerja Karyawan Perakitan Kemasan Bedak untuk Memenuhi Permintaan

PT. XYZ is a Foreign Investment (PMA) company that specializes in the plastic cosmetic packaging printing industry and produces more than a thousand packaging variants. This research focuses on the assembly part of the DK-274 baby powder packaging. The problem found in this research is the delay in achieving the demand target which originates from worker fatigue due to work pressure and other factors during the production process. In this research, workload measurements will be carried out and determine the optimal or ideal number of workers to meet demand. By using several research methods, including work sampling and work load analysis (WLA), which functions to determine the workload and the optimal number of workers. After the method was applied, the results showed that assembly of the DK-274 baby powder packaging product required a manufacturing time of 1.40 minutes per product unit with an average workload of 109.04% (overload). From the results of this research, the labor solution used in assembly DK-274 baby powder packaging uses 7 workers and 1 automatic press machine. By calculating using work load analysis, it was found that there was no additional workforce. The production alternative requires the company to provide overtime for 7 workers. With this implementation, the company only incurs less costs compared to increasing the number of workers

Cost Control of “J” Metallurgical Products Based on Job Analysis

Compared with traditional costing, activity-based costing calculates costs down to the activity level, which is more accurate than traditional costing. In the process of cost control, activity-based costing can analyze the cost drivers of each operation and provide management with accurate cost information, so that cost control is not limited to post-event accounting, but runs through product procurement, production, assembly, and debugging. The whole process of product production. Secondly, this article uses Company M as a case to analyze the differences between traditional costing and activity-based costing in the cost accounting and cost control processes. Finally, by using activity-based costing to analyze the entire production process of “J” metallurgical products of Company M, cost control suggestions for Company M are given, so that the problems existing in the procurement process and production process of Company M can be solved.

Effective GA Operator for Product Assembly Sequence Planning

Effective GA Operator for Product Assembly Sequence Planning

A Modular Albumin-Oligonucleotide Biomolecular Assembly for Delivery of Antisense Therapeutics.

Antisense nucleic acid drugs are susceptible to nuclease degradation, rapid renal clearance, and short circulatory half-life. In this work, we introduce a modular-based recombinant human albumin-oligonucleotide (rHA-cODN) biomolecular assembly that allows incorporation of a chemically stabilized therapeutic gapmer antisense oligonucleotide (ASO) and FcRn-driven endothelial cellular recycling. A phosphodiester ODN linker (cODN) was conjugated to recombinant human albumin (rHA) using maleimide chemistry, after which a complementary gapmer ASO, targeting ADAMTS5 involved in osteoarthritis pathogenesis, was annealed. The rHA-cODN/ASO biomolecular assembly production, fluorescence labeling, and purity were confirmed using polyacrylamide gel electrophoresis. ASO release was triggered by DNase-mediated degradation of the linker strand, reaching 40% in serum after 72 h, with complete release observed following 30 min of incubation with DNase. Cellular internalization and trafficking of the biomolecular assembly using confocal microscopy in C28/I2 cells showed higher uptake and endosomal localization by increasing incubation time from 4 to 24 h. FcRn-mediated cellular recycling of the assembly was demonstrated in FcRn-expressing human microvascular endothelial cells. ADAMTS5 in vitro silencing efficiency reached 40%, which was comparable to free gapmer after 72 h incubation with human osteoarthritis patients' chondrocytes. This work introduces a versatile biomolecular modular-based "Plug-and-Play" platform potentially applicable for albumin-mediated half-life extension for a range of different types of ODN therapeutics.

Automated assembly of products by a robot-manipulator with dynamometric control of screw joint tightening

In this work, we develop a conceptual scheme for a robotic complex to perform the installation of parts and their fastening using threaded joints by a robot manipulator. A test bench was created on the basis of a KUKA KR6 R900 industrial robot-manipulator. The robot control software was implemented using the KUKA Robot Language. The proposed actuators are the authors' original development. Two variants of the actuator with screw tightening control are proposed. The first actuating device uses the rotational motion of the robot hand flange to tighten the screws. The second actuating device is equipped, on one side, with a gripper for mounting parts on the product and, on the other side, with a drive tool with a predetermined tightening torque limit. It is shown that both actuating devices ensure a complete cycle of screwing a fastener into a workpiece, from engaging to tightening with the required torque. In the first device, the tightening force is controlled with a strain gauge, the signal from which is processed by an Arduino Mini microcontroller located in a rotating device. The signal is forwarded wirelessly to a stationary controller that sends a stop signal to the robot. It was experimentally established that, due to the presence of the wireless interface, some delay is observed between reaching the torque limit value and stopping the robot rotation during signal transmission. As a result, the value of the actually reached torque may exceed the set value by 60%. In the second device, where torque limitation is based on the current in the drive motor, the absolute error of the torque setting does not exceed 0.8 N·m in the range from 0 to 25 N·m or 3.03% (the error of standard torque wrenches is about 4%). In order to meet the requirements of state-of-the-art cyber-physical production systems, the proposed complex should be complemented with intelligent functions of controlling the process of tightening screw joints on the basis of machine learning methods.

A feedback learning-based selection hyper-heuristic for distributed heterogeneous hybrid blocking flow-shop scheduling problem with flexible assembly and setup time

Distributed manufacturing is increasingly common due to economic globalization. It has important practical significance to optimize global supply chains by considering cooperative scheduling of distributed production and flexible assembly. This paper studies a distributed heterogeneous hybrid blocking flow-shop scheduling problem with flexible assembly and setup time (DHHBFSP-FAST). The objective is to minimize makespan of all products. To tackle such problem, a mixed-integer linear programming model (MILP) is presented to formulate it. Then, a feedback learning-based selection hyper-heuristic (FLS-HH) is proposed, which contains high-level control strategies and low-level heuristics. For the high-level control strategies, the transition information between each pair of low-level heuristics is collected, then a feedback learning-based selection method is presented based on such transition information, which can automatically select the appropriate low-level heuristics. For the low-level heuristics, to assign jobs/products to machines, a composite dispatch rule is proposed. To generate an initial domain solution with high quality, a constructive heuristic based on double evaluation indexes is developed. The critical jobs and products are analyzed to avoid invalid searching. Based on such analysis, several low-level heuristics are presented to search the domain solution space, which combine six problem-specific perturbation heuristics and two local searches to balances exploration and exploitation. Comprehensive numerical experiments are carried out. The effectiveness of the proposed MILP and the special designs of FLS-HH are verified. To verify the effectiveness of FLS-HH, we compare it with 10 existing high-performing approaches. The comparison results show that FLS-HH significantly outperforms its competitors in solving DHHBFSP-FAST.

Data-driven analysis and human-centric assignment for manual assembly production lines

Flow production-oriented assembly production lines have become crucial in various industries with the development of Industry 4.0, leading to mass customization and personalized production. In addition, Industry 5.0 has emerged, which emphasizes human-centric design. Manual assembly production line balancing, considering worker ergonomics, has also gained substantial attention. This study aims to solve the line balancing problem through combination optimization considering ergonomic risks based on many studies on human-centric production lines. A framework of the data-driven analysis and assignment for manual assembly production lines is proposed herein. The proposed framework defines and analyzes the process difficulty and the worker’s process ability and assigns a skilled worker to a process through the presented heuristic algorithm. To demonstrate the applicability of the proposed framework, a case study was conducted on an experiment imitating a home appliance assembly line in the United States. This paper provides empirical evidence of a framework aimed at realizing human-centric business objectives through case study. Future studies on the data-driven analysis and assignment for manual assembly production lines are anticipated to exhibit a range of variations such as line balancing problems and evaluation methods.

Framework for metamodel-based design optimization considering product performance and assembly process complexity

This paper proposes a method for simultaneous evaluation of the assembly process complexity together with the performance of the future product. It allows for product design optimization, considering different aspects of the future design at the early stage of the development process. The proposed method, embodied in a fully automated framework, substitutes the traditional sequential development process with a more efficient and rapid combined procedure, which addresses multiple design aspects simultaneously. Design for assembly (DFA) rules, used as quantitative metrics of the ease-of-assembly of the whole product and individual assembly operations, are automatically evaluated together with performance metrics, estimated based on finite element (FE) simulations. The direct solution to this optimization problem might be inefficient or impossible since it requires the recurrent evaluation of computationally expensive discrete and continuous functions with unknown behavior that represent the optimization objectives and constraints. For that reason, the proposed framework employs regression models based on the Gaussian process and artificial neural networks, thus achieving the optimal design of a product as a result of metamodel-based design optimization (MBDO). The suggested approach is demonstrated in the optimization of a gearbox assembly, considering its mechanical performance and assembly process. Comparing the results of the metamodel-based and direct design optimization shows that MBDO allows finding a better solution using a three times smaller computational budget. In addition, analysis of the results obtained using stationary sampling data sets of different sizes highlighted the limitations of the employed sampling procedure.

Physiological workload assessment for highly flexible fine-motory assembly tasks using machine learning

In assembly of small-volume products, tasks are still frequently executed manually. However, the lead times foreseen for these tasks, often do not take into account the actual capabilities of the employees, which in turn leads to increased workload and the associated stress among the employees. This paper investigates how a commercially available wearable low-cost sensor and two machine learning algorithms can be applied to measure and evaluate heart rate, heart rate variability and respiration rate to establish a relationship with workload. The investigated algorithms, namely Random Forest and K-Nearest-Neighbours are able to distinguish between tasks phases and rest phases as well as between easy and difficult tasks executed by the employee, which is the main novelty of this paper.

Coordination and optimization decision of assembly building supply chain under supply disruption risk

Assembly buildings, in the context of the low-carbon transformation of the construction industry, achieve superior outcomes in terms of carbon emission reduction, enhancement of building uniformity, and optimization of resource utilization as compared to traditional buildings. However, the supply chain for assembly building is marked by a significant susceptibility to risk and a need for timely fulfillment of requirements. This paper examines the risk of disruption and capacity limitations in the assembly building supply chain resulting from supply disruptions. It establishes a three-tier supply chain for assembly buildings, including primary component suppliers, backup suppliers, assembly manufacturers, and retailers. The study compares the optimal decision-making and coordination strategies of the supply chain members under centralized, decentralized, and joint agreements. The supply chain dual-source procurement decision coordination model is constructed by incorporating capacity constraints and analyzing the effects of supply disruption probability, repurchase coefficient, revenue sharing coefficient, cost, and other parameters on the expected profits of the supply chain members using arithmetic simulation. Research has indicated that when the likelihood of a disturbance occurring rises, the anticipated financial gain for the main provider decreases, while the predicted financial gain for the secondary supplier increases. The implementation of a collaborative agreement between the assembly maker and the parts backup provider would result in much greater anticipated profits compared to the decentralized decision-making approach. The impact of the revenue sharing coefficient on the predicted earnings of retailers and assembly manufacturers is more significant compared to the repurchase coefficient. The selection bias between NA and NB techniques under capacity constraints mostly arises from the assertiveness of the wholesale asking prices of inexpensive component suppliers, leading assembly manufacturers to increasingly prefer the NA option. This paper's research successfully achieves the contractual coordination of the assembly building supply chain, enhances the resilience of the assembly building supply chain, and promotes the long-term sustainable development of the assembly building supply chain.

Виброактивность электромеханических устройств вследствие наличия технологических погрешностей

This article discusses a theoretical justification for the presence of vibration in operating modes of electromechanical devices due to technological errors occurring during the machining of parts and assembly of products. The reason for the presence of a dense spectrum of vibration caused by technological errors in the structural elements of ball bearings (outer and inner rings, balls, and cage) is also denoted. The analytical dependence of the vibration amplitude on the magnitude of technological errors is shown. It follows from the results of the analysis that for the most effective minimization of the vibration activity of an electromechanical device, it is necessary to use broadband damping, which is liquid–viscous in most cases. In addition to the above, it is advisable to apply damping in the cascade version. When solving the system of vibration equations for an electromechanical device, replacing ball bearings with sliding bearings eliminates the first four terms, which characterize a wide and dense vibration spectrum of the ball bearings in the operating mode of the electromechanical device.

Preliminary comparison between manual assembly and intelligent human-robot collaborative assemblies in terms of quality and assembly time

In recent years, the use of Human-Robot Collaboration (HRC) in manufacturing systems has grown significantly, within the framework of Industry 4.0 and emerging Industry 5.0. Collaborative robots, thanks to their ability to reduce physical and mental stress of operators, enable increased productivity and quality performance. This paper analyses assembly time and quality trends as a function of assembly complexity in intelligent collaborative assembly and makes a holistic comparison between a manual assembly and two different collaborative assemblies, focusing on assembly times and in-process errors. The assembly of products with different levels of complexity is used as a case study.

Collaborative Planning in a Two-Stage Supply Chain: Transparent Coordination, Distributed Response, Integrated Optimization

In the competitive global market, large manufacturing enterprises are striving to achieve a competitive edge through constructing a transparent collaborative supply chain. One of the important and effective ways is to cooperate with distributed response from suppliers in the operation of the supply chain, such as production planning. This article proposes a new collaborative planning mode in a two-stage supply chain considering the supplier part production and product assembly simultaneously. In this context, a mathematical model is formulated and the integrated optimization method is proposed. To reduce the complexity of the problem, the part production decisions of suppliers are first addressed by some lemmas. Then, the transformation process of the mathematical model is described as the decision variables gradually decrease. On this basis, we further propose a LIMA-GVNDS (less is more approach-general variable neighborhood decomposition search) algorithm to solve the integrated supply chain planning problem for the assembly manufacturing enterprise. The objective is to minimize the total supply chain costs. A new neighborhood structure is designed according to the problem characteristics and a series of variable neighborhood descent (VND) variants are proposed. Some computational experiments are carried out, and the results show that the proposed LIMA-GVNDS algorithm has obtained an average 3.69%, 13.07%, 2.47%, and 2.99% improvement of objective value against the other four meta-heuristic algorithms. The model transformation and the integrated optimization method proposed in this article can provide a reference for large manufacturing enterprises to formulate collaborative planning in a transparent supply chain network.

ОРГАНИЗАЦИЯ ПРОЕКТНОЙ ДЕЯТЕЛЬНОСТИ СТУДЕНТОВ МАШИНОСТРОИТЕЛЬНОГО ПРОФИЛЯ

This article describes various aspects of organization of engineering activities of students of mechanical profile at technical university. It also discusses personal needs of students and general methodological principles leading to effective training of engineering and graphic disciplines in a computerized teaching environment. Theoretical provisions are illustrated by examples from the students' engineering activities carried out in the process of project-oriented study of engineering and computer graphics. Various innovative forms of work on educational material in modules motivate students to in-depth study and creative processing of the acquired knowledge, formation of professional skills and engineering culture. In result of project activities students acquire skills to present their developments to potential consumers and employers, learn how to pass interview with manager, get acquainted with structure of professional activity. This helps to increase their competitiveness in job market in the future and motivation for educational activities in the present. The developed engineering cases contain professionally directed references and theoretical materials for all educational modules. They describe the basic principles, methods and concepts of mechanical engineering, basic skills in the field of computer-aided design. Certain technical and economic conditions are set in order to develop machine-building parts, assemblies, assembly products, original author's models based on computer technology. The used COMPASS-3D computer program has effective reference support for all modules studied in the field of computer-aided design. At any stage of their work students can also turn to a fairly extensive list of Internet links on the interested issues. All this contributes to creation of situation of success for a student, formation of integrative personality traits necessary in further professional activity.

Effect of coat-protein concentration on the self-assembly of bacteriophage MS2 capsids around RNA.

Self-assembly is a vital part of the life cycle of certain icosahedral RNA viruses. Furthermore, the assembly process can be harnessed to make icosahedral virus-like particles (VLPs) from coat protein and RNA in vitro. Although much previous work has explored the effects of RNA-protein interactions on the assembly products, relatively little research has explored the effects of coat-protein concentration. We mix coat protein and RNA from bacteriophage MS2, and we use a combination of gel electrophoresis, dynamic light scattering, and transmission electron microscopy to investigate the assembly products. We show that with increasing coat-protein concentration, the products transition from well-formed MS2 VLPs to "monster" particles consisting of multiple partial capsids to RNA-protein condensates consisting of large networks of RNA and partially assembled capsids. We argue that the transition from well-formed to monster particles arises because the assembly follows a nucleation-and-growth pathway in which the nucleation rate depends sensitively on the coat-protein concentration, such that at high protein concentrations, multiple nuclei can form on each RNA strand. To understand the formation of the condensates, which occurs at even higher coat-protein concentrations, we use Monte Carlo simulations with coarse-grained models of capsomers and RNA. These simulations suggest that the formation of condensates occurs by the adsorption of protein to the RNA followed by the assembly of capsids. Multiple RNA molecules can become trapped when a capsid grows from capsomers attached to two different RNA molecules or when excess protein bridges together growing capsids on different RNA molecules. Our results provide insight into an important biophysical process and could inform design rules for making VLPs for various applications.

Augmented Reality for Quality Inspection, Assembly and Remote Assistance in Manufacturing

In recent years, the manufacturing industry has witnessed the utilization of Augmented Reality (AR) technologies in their daily operations. This paper takes a deep dive into the applications of AR in the manufacturing industry, specifically focusing on quality inspection, assembly, and remote assistance. This research offers valuable insights into the technical architectures using custom and commercial software, as well as the Proof of Concept (PoC) applications for Hand-Held Device (HHD) and Head-Mounted Device (HMD). The custom application for an HHD combines the state-of-the-art You Only Look Once (YOLO) object detection algorithm to enable AR for quality inspection. We used commercial software from Pocket virtuality® to develop assembly and remote assistance applications for an HMD. An applied research approach was adopted, incorporating the collection of both quantitative and qualitative data to assess the various application scenarios. Among the key findings, it is evident that the functionality of the custom-developed app for quality inspection is contingent upon the operating system, software libraries available on the HHD, and the chosen version of the YOLO detection model. Furthermore, through quantitative and qualitative analysis, it becomes apparent that the software and hardware components of the HMD require significant improvements. These findings offer a high potential for improvement and emphasize the need for further research in the field. Moreover, this research emphasizes the fact that AR has the potential to make a huge impact on the manufacturing industry.

Methodology for automated assembly and delivery of products using mivar expert systems

The paper presents an analysis of the task of automating assembly using robots with mivar decision-making systems. The question of the relevance of solving this problem is considered. The trend of robot development and their application in various sectors is also examined: from delivering parcels to customers to industrial warehouses. The use of mivar expert systems allows solving a large number of tasks for planning robot actions. Moreover, solving planning tasks allows us move towards a fully autonomous delivery transport system. The subject area and existing analogs are analyzed. The algorithm for implementing this task is described. In the end, a conclusion is given and the feasibility of this system is evaluated. This work describes part of the architecture of a web application, which is a cloud constructor of mivar expert systems. The created expert systems can have any subject area embedded in them by the architect. The main principles in development were: convenience, maintainability, scalability. Parameters necessary for the operation of expert systems were defined for further object representation: thing, property, relation. Based on the calculated parameters, expert systems make a decision about further actions. This work is intended for engineers involved in the development of autonomous robotic systems related to the delivery of goods.

APLAN: open assembly planning framework in FreeCAD

In the latest decade, the consumer’s desire for personalisation has clearly taken of, challenging manufacturers to diversify their product portfolio while maintaining the same (or near) mass-produced prices. As a result, production is nowadays geared towards low volumes with high variety for which adaptive assembly systems are required. Hence, being able to automatically map out the assembly of complex products yields significant strategic advantages over competing manufacturers. Although a wide range of assembly sequencing algorithms have been developed in the past, researchers and companies still experience intellectual and financial thresholds to applying these software packages themselves. Either the algorithms have to be largely re-engineered from scientific literature, or are offered as part of costly commercial CAD software in the form of plugins and add-ons. However, in some cases, the developed source code is made publicly available via online collaboration platforms though in a variety of programming languages and often requiring the cumbersome installation of additional software libraries.Out of these needs, the proposed APLAN module arose: a software framework allowing developers to share their (dis)assembly planning algorithms in a centralised, uniform manner through the open-source 3D parametric modelling software FreeCAD. As impetus, several in-house developed algorithms for determining topological and geometrical (dis)assembly constraints are included as well as an academic (dis)assembly planner. Previously, such algorithms had to be executed via the terminal, after which the extensive liaison, blocking, and AND/OR graphs were outputted as text or static images. Through APLAN, users are now able to inspect and edit these graphs interactively and dynamically. To conclude, this manuscript finally reports on the benchmarking of the aforementioned connection and obstruction detectors, and their academic and industrial application for human-robot collaboration.

An optimization approach for assembly job shop order release based on clearing functions

As an integral part of production planning control, order release management is critical to enhance the competitiveness and production efficiency of companies. Previous literature shows limited application of optimization-based models in assembly job shops, primarily due to the intricate nature of product structures and assembly operations. Therefore, based on the idea of the allocated clearing function (ACF) model, we introduce material flow constraints and complex assembly structure constraints during the assembly stage, proposing the assembly job shop allocated clearing function (AACF) model. The performance of the AACF model and the rule-based mechanisms in terms of cost and timing measures are compared through experiments containing 6 factors and 96 scenarios. The results show that the AACF model performs better in terms of cost management, service level and order due date deviation. In addition, a sensitivity analysis of the objective function parameters is performed to confirm the robustness of the AACF model. Finally, a case application in a real assembly shop illustrates the feasibility and validity of the proposed AACF model.

A Human Digital Twin of Disabled Workers for Production Planning

Including disabled workers in value-creating work processes is a fundamental and guaranteed human right and is, therefore, an essential goal of society. In Germany, sheltered workshops create the conditions for this inclusion since they are essential to companies' value chains. A central challenge is the inclusion of disabled workers in the value-creation processes, such as in manufacturing or assembly areas. The skills of disabled workers vary since they have individual impairments. Therefore, this paper presents a digital human model, a Human Digital Twin (HDT), for disabled workers. The model maps their skills and supports the production planning and assembly processes.