Small Batch Production Research Articles

Cold spray forming: a novel approach in cold spray additive manufacturing of complex parts using 3D-printed polymer molds

The solid-state additive manufacturing (AM) process cold spraying (CS) offers advantageous properties such as melt-free near-net-shape part fabrication and high deposition rates. Compared to other metal-based AM processes such as the powder bed fusion of metals (PBF-LB/M) or directed energy deposition (DED) processes such as laser metal deposition (DED-LB), CS features lower part resolution. One solution to increase the achievable level of detail is spraying onto removable molds. No study exists that investigates the general feasibility and manufacturing boundaries, from which design guidelines could be derived. In this paper, the applicability of material extruded and thermally bonded polymer (MEX-TRB/P) shapes, which is especially suitable for flexible low-cost production of small batches, as molds for cold spray additive manufacturing (CSAM) is investigated. For this purpose, material extruded thermoplastics are examined regarding their suitability for the CS process. Furthermore, geometrical and thus constructive restrictions of this new approach “Cold Spray Forming” (CSF) are analyzed using an industry-relevant use case. It was shown that the feasibility of this approach could be determined by the material value hardness of the sprayed polymer substrates.

Adaptation of a CAD System for Technological Process Formation for Part Manufacturing in Small-Series and Single Production

The task of automating the system of technological preparation of production, including the stage of technological process design, is currently gaining special relevance. Implementation of re-engineering programs within the framework of solving the problems of ensuring technological independence and safety implies rapid deployment of production capacities and effective development of new production facilities. As a consequence, reliable and correct for application in various forms of production enterprises automation systems are required. The existing systems of automated design of technological processes remain poorly adapted for single and small batch productions, so they are practically not applicable for multi-nomenclature productions of small or medium-sized enterprises. Functioning of modern domestic systems of computer-aided design of technological process is based on algorithms adapted and applied in conditions of large series, when production has greater stability of production of products. Consequently, it is necessary to adapt the algorithms of technological process design to work at a small-scale enterprise. The general scheme of technological process design for serial systems of automated technological process design is considered, the possibilities of its unification and subsequent adaptation for single and small batch productions are shown and evaluated. On the basis of the analysis of the obtained unified functional scheme the adaptation of the algorithm of formation of the technological process of part manufacturing is carried out. Taking into account the existing limitations and requirements to the peculiarities of functioning of the systems of computer-aided design of technological process in single and small batch production, a new functionality of the subsystem of initial information preparation is formed and proposed. The proposed algorithm of forming the technological process of part manufacturing includes three fundamental blocks: preparation of initial information, construction of the technological model of the part and its analysis, formation and issuance of technological documentation. Thus, the proposed adapted algorithm of technological process formation in the conditions of single and small batch production of products has a simpler form, understandable structure.

Possibility Assessment of Automatic Formation of Technological Processes in Small Batch Production

The work is devoted to urgent problem solution of lack of convenient tools with functional capabilities of the system of route technological process automated design, adapted to small-scale production. The estimation of potential possibility of automatic small-scale production formation by means of estimation of efficiency and expediency technological processes of automation of key stages of design of production technological preparation, such as equipment selection, selection of cutting modes, workpiece, cutting and measuring tools and tooling selection is given. The key stages of technological process development are considered and characterized, such as selection of technological bases, type of workpiece and equipment, formation of route technological process, calculation of cutting modes, selection of allowances and so on. The paper shows both the relevance and necessity of analyzing approaches to automation and their correct adaptation to production needs to achieve maximum efficiency and resource savings for small batch production, and the high relevance for small-batch production of the automatic formation of route technological processes. At the same time, the paper shows the lack of automated systems adapted to the specifics of small-batch production. The existing approaches to the formation of stages are analyzed, as well as the possible methods of automation of stages and the existing limitations of these methods are considered, the efficiency of the considered approaches is evaluated. The methods of automation of separate stages of technological preparation of production are analyzed and the efficiency of the considered approaches is evaluated. The original concept of solving the problem of automation for small-scale production by using a combination of a limited number of standard solutions, represented as a set of technological parameters or knowledge base, with individual solutions, adapted to the specifics of enterprises and industry, is proposed and the potential effectiveness of this approach is shown.

Augmented reality and indoor positioning based mobile production monitoring system to support workers with human-in-the-loop

With the increasing demand for product customization, the exponential increase in large-scale and small-batch production orders has yielded new challenges for the capacity of traditional production lines. Due to the information redundancy and complex production process on the production site of the factory, the traditional monitoring system is incapable of meeting the information interaction requirements between the factory management level and the executive level. Meanwhile, the traditional augmented reality (AR) based on image recognition is not suitable in the complex industrial environments. To address the gap, we propose a novel mobile production monitoring system (AIMPMs) with human-in-the-loop control by leveraging the cutting-edge AR and indoor positioning technique. In the proposed system, Ultra-wideband (UWB) and Inertial Measurement Unit (IMU) fusion indoor positioning technology is proposed, which provides accurate indoor positioning information for the production factors in the factory. Subsequently, we build the lightweight indoor map for positioning that can serve as the location reference and path planning, and a nearest-neighbor decision algorithm with double rejection decision (NN-DRD) is proposed to match the positioning features to trigger virtual monitoring information. Finally, the AIMPMs is applied in a hydraulic cylinder factory to verify its enforceability and effectiveness, and the human factors evaluation model and index system are constructed to evaluate two systems, (1) the mobile monitoring system based on positioning information, and (2) the mobile monitoring system based on image recognition, respectively. The experimental results indicate that after the application of AIMPMs, the physiological and mental fatigue of the production personnel is immensely decreased. Therefore, the system realizes a smarter and highly humanized human-machine interaction mode with human-in-the-loop control.

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

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

3D free-assembly modular microfluidics inspired by movable type printing

Reconfigurable modular microfluidics presents an opportunity for flexibly constructing prototypes of advanced microfluidic systems. Nevertheless, the strategy of directly integrating modules cannot easily fulfill the requirements of common applications, e.g., the incorporation of materials with biochemical compatibility and optical transparency and the execution of small batch production of disposable chips for laboratory trials and initial tests. Here, we propose a manufacturing scheme inspired by the movable type printing technique to realize 3D free-assembly modular microfluidics. Double-layer 3D microfluidic structures can be produced by replicating the assembled molds. A library of modularized molds is presented for flow control, droplet generation and manipulation and cell trapping and coculture. In addition, a variety of modularized attachments, including valves, light sources and microscopic cameras, have been developed with the capability to be mounted onto chips on demand. Microfluidic systems, including those for concentration gradient generation, droplet-based microfluidics, cell trapping and drug screening, are demonstrated. This scheme enables rapid prototyping of microfluidic systems and construction of on-chip research platforms, with the intent of achieving high efficiency of proof-of-concept tests and small batch manufacturing.

Liquid Phase Graphene Exfoliation with a Vibration-Based Acoustofluidic Effector.

Liquid phase exfoliation (LPE) has emerged as a promising method for the industrial-scale production of graphene. However, one of its critical steps, namely sonication, has faced challenges due to high power consumption and low efficiency, leading to limited applicability in industrial settings. This study introduces a novel, cost-effective microfluidic sonication device designed to significantly reduce power consumption while efficiently assisting the LPE process for graphene production. By coupling a capillary with a buzzer and applying an appropriate electric signal, simulation and particle tracing experiments reveal the generation of robust shear forces resulting from acoustic streaming and cavitation when the capillary end is immersed in the liquid. For the first time, the capillary-based sonication device was effectively utilized for graphene exfoliation in a DMF (N,N-Dimethylformamide) + NaOH liquid phase system. The SEM (Scanning Electron Microscope) and Raman characterization results corroborate the successful exfoliation of 100 nm with thicknesses below 10 nm graphene sheets from graphite flakes using this pioneering device. The values of I2D/IG increase after processing, which suggests the exfoliation of graphite flakes into thinner graphene sheets. The vibration-based acoustofluidic effector represents a versatile and scalable miniature device, capable of being employed individually for small-batch production, thereby optimizing the utilization of raw 2D materials, particularly in experimental scenarios. Alternatively, it holds the potential for large-scale manufacturing through extensive parallelization, offering distinct advantages in terms of cost-efficiency and minimal power consumption.

Computer-aided process planning system for laser forming: from CAD to part

Laser forming is a highly flexible and iterative contactless thermomechanical forming process that utilises a defocused laser beam to induce material shortening and bending. There is a high potential for the use of laser forming in rapid prototyping, small and unique batch production; however, to achieve that potential a certain level of automation is required. The presented work seeks to address this need of automation by proposing an end-to-end sheet-metal manufacturing system utilising laser forming and cutting, where the input for the system is a 3D CAD model and the output is a manufactured product. The contribution of the presented work is interconnected laser forming and cutting framework. The presented framework consists of subsystems for automatic extraction of geometrical information from a CAD model, process planning and generation of manufacturing information, scheduling of tasks and a feedback control loop for laser forming. The framework is experimentally validated and has shown consistent forming and cutting behaviour on two types of parts with variation in cutting features, bend angle and lengths of the bend's free edge.

An Intelligent Approach to the Unit Nesting Problem of Coil Material

With the popularization of small batch production, the main cutting method for sheet metal parts has changed. Laser cutting has become the main production method for coil material cutting. Developing an irregular part nesting method for the continuous cutting of coil material is urgent. Based on the coil material cutting process, this paper proposes an intelligent approach for the unit nesting problem of coil material. Firstly, a unit nesting model of coil material was constructed. Secondly, an intelligent approach using an improved marine predator algorithm was used to solve this model. In solving the model, the minimum nesting unit was continuously updated by changing the position, angle, and quantity of the nesting parts. Thirdly, the geometric characteristics of this minimum nesting unit were extracted. Finally, the nesting units for production were obtained using a single row or opposite row of the minimum nesting unit. The computational results and comparison prove that the presented approach is feasible and effective in improving material utilization, reducing production costs, and meeting the requirements of the production site.

Aluminium deep drawing with additive manufacturing polymer punches: analysis of performance in small batch production

In this research the authors tested the performance of polymer punches, filled with short carbon fibres, produced with fused filament fabrication technology for aluminium sheet deep drawing. An experimental campaign was designed to investigate the geometry accuracy of 99th produced cup and the punches wear mechanism. Results demonstrated that polymer punches are subjected to elastic and plastic deformation that affects cup radius and depth. However, the tolerance comparison with cup produced by conventional steel tools is in a range of tenth of micron; consequently, these punches can withstand the small batch or customised production of one hundred parts.

Detection of Anomalies in Additively Manufactured Metal Parts Using CNN and LSTM Networks

The process of metal additive manufacturing (AM) involves creating strong, complex components by using fine metal powders. Extensive use of AM methods is expected in near future for the production of small and medium-sized batches of end-use products and tools. The ability to detect loads and defects would enable AM components to be used in critical applications and improve their value. In this study, the Surface Response to Excitation (SuRE) method was used to investigate wave propagation characteristics and load detection on AM metallic specimens. With completely solid infills and the same geometry, three stainless steel test bars are produced: one conventionally and two additively. To investigate the effect of infills, four bars with the same geometries are 3D printed with triangular and gyroid infills with either 0.5 mm or 1 mm skin thickness. Two piezoelectric disks are attached to each end of the test specimens to excite the parts with guided waves from one end and monitor the dynamic response to excitation at the other end. The response to excitation was recorded when bars were in a relaxed condition and when compressive loads were applied at five levels in the middle of them. For converting time-domain signals into 2D time-frequency images, the Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were implemented. To distinguish the data based on fabrication characteristics and level of loading, two deep learning models (Long Short-term Memory algorithm (LSTM) and Convolutional Neural Networks (2D CNN)) were utilized. Time-frequency images were used to train 2D CNN, while raw signal data was used to train LSTM. It was found that both LSTM and 2D CNN could estimate solid parts' loading level with an accuracy of more than 90%. In parts with infills, CNN outperformed LSTM for the classification of over five classes (internal geometry and loading level simultaneously).

Design of a Multi-Mode Hybrid Micro-Gripper for Surface Mount Technology Component Assembly.

In the last few decades, industrial sectors such as smart manufacturing and aerospace have rapidly developed, contributing to the increase in production of more complex electronic boards based on SMT (Surface Mount Technology). The assembly phases in manufacturing these electronic products require the availability of technological solutions able to deal with many heterogeneous products and components. The small batch production and pre-production are often executed manually or with semi-automated stations. The commercial automated machines currently available offer high performance, but they are highly rigid. Therefore, a great effort is needed to obtain machines and devices with improved reconfigurability and flexibility for minimizing the set-up time and processing the high heterogeneity of components. These high-level objectives can be achieved acting in different ways. Indeed, a work station can be seen as a set of devices able to interact and cooperate to perform a specific task. Therefore, the reconfigurability of a work station can be achieved through reconfigurable and flexible devices and their hardware and software integration and control For this reason, significant efforts should be focused on the conception and development of innovative devices to cope with the continuous downscaling and increasing variety of the products in this growing field. In this context, this paper presents the design and development of a multi-mode hybrid micro-gripper devoted to manipulate and assemble a wide range of micro- and meso-SMT components with different dimensions and proprieties. It exploits two different handling technologies: the vacuum and friction.

Hierarchical-clustering-based joint optimization of spare part provision and maintenance scheduling for serial-parallel multi-station manufacturing systems

Both the spare part provision and the maintenance scheduling are important in ensuring the production of the Serial-Parallel Multi-Station System (SPMMS). In the multi-specification and small-batch production, the production plan, which renews batch by batch, leads to variable and uncertain working conditions. The existing Dynamic Opportunistic Maintenance (DOM), which separately optimizes each cycle, ignores the aftereffects of both the spare part provision and the Preventive Maintenance (PM) on the following PM scheduling. This paper studies the dynamic joint optimization of spare part provision and maintenance scheduling for the SPMMS, where the aftereffects of the information are especially investigated. During the failure rate modelling, the aftereffect of the historical working conditions is described with the accelerated failure-time model. In the system-level maintenance modelling, a Hierarchical-Clustering-Based Opportunistic Maintenance (HCBOM) policy, which uses a non-parametrical clustering, is introduced to incorporate the aftereffects of the PM. The case study and the policy comparisons verify the above-mentioned aftereffects. The proposed HCBOM is more cost-effective than the tradition Opportunistic Maintenance (OM) frame, the DOM, the group maintenance and the station-level maintenance. From the perspective of clustering, this work provides an innovative OM policy, which can guide practitioners to formulate cost-effective PM scheme without time-expensive calculations.

Multi-variety and small-batch production quality forecasting by novel data-driven grey Weibull model

With the coming of intelligent manufacturing, multi-variety and small-batch production mode has gradually become popular. Aiming at the characteristics of high dimensional information and limited samples in this mode, a novel data-driven grey Weibull model is established for product quality prediction. Firstly, a high-dimensional information from the production process is integrated as the process variation using a data-driven method. Then, the quality prediction function is deducted by considering that process variation follows Weibull distribution-based mechanism, the Hausdorff difference scheme is adopted to weaken the error from the difference to the differential, heuristic algorithm is selected to optimize the distribution parameters of the model. Finally, an experimental analysis is designed using the dataset from some personalized customization manufacturer in China. Results show that the proposed model is not only superior to the other eight models in terms of stability and prediction accuracy, but also boasts the features of amalgamation of data-driven and mechanism-driven methods, which can simultaneously process high-dimensional information and limited samples in multi-variety and small-batch production system.

Nanomaterials Reinforced Polymer Filament for Fused Deposition Modeling: A State-of-the-Art Review.

For the past years, fused deposition modeling (FDM) technology has received increased attention in the applications of industrial manufacturing fields, particularly for rapid prototyping, small batch production and highly customized products, owing to the merits of low-cost, user-friendliness and high design freedom. To further expand the application potential and promote the performance of the as-manufactured products, many efforts have been spent on the development of suitable materials for FDM applications. In recent years, the involvement of nanomaterials in the FDM-based polymer matrix, which has been demonstrated with great opportunities to enhance the performance and versatility of FDM printed objects, has attracted more and more research interest and the trend is expected to be more pronounced in the next few years. This paper attempts to provide a timely review regarding the current research advances in the use of nanomaterials to reinforce polymer filaments for the FDM technique. Polymer composite filaments based on nanomaterials such as carbon nanotubes, nanoclay, carbon fibers, graphene, metal nanoparticles and oxides are discussed in detail regarding their properties and applications. We also summarized the current research challenges and outlooked the future research trends in this field. This paper aims at providing a useful reference and guidance for skilled researchers and also beginners in related fields. Hopefully, more research advances can be stimulated in the coming years.

Business Growth Strategy of Personal Care Brand using VMOSA and Three Horizon Model (A Case of Evening)

Evening, a mindful living personal care brand, seeks to overcome challenges in product innovation following the success of their Aromatherapy Eye Pillow. Despite having a loyal customer base, recent introductions like Scented Candles and Soap Bar have failed to gain significant traction. To address concerns about the product life cycle and ensure sustained growth and profitability, Evening conducted research using various analytical tools including RBV, Value Chain, PESTLE, and Porter 5 Forces. The findings were analyzed through the VMOSA framework to develop a vision and mission statement, and the Three Horizon Model was utilized to align objectives, strategy, and action plans. This integration allows Evening to balance current operations with future growth, fostering innovation, resource optimization, and alignment with long-term objectives. Analysis of Evening’s current state indicates the need to explore new business opportunities as the current model becomes less effective. To attract customers seeking research-backed offerings and overcome competition in the oversaturated skincare industry, Evening must venture beyond small-batch products. The key areas for innovation identified are: 1) creating products and experiences catering to shared wellness activities and embracing slow beauty and slow living, 2) incorporating multisensory integration to enhance consumer well-being outcomes, and 3) embracing personalization and technology by leveraging AI-driven solutions. To implement this growth strategy, Evening should consider recruiting a business partner, collaborating with a marketing agency, and creating a portfolio of new business ideas.

TECHNICAL-ECONOMIC CALCULATION OF CONVENTIONAL AND INCREMENTAL FORMING

"Recent developments in incremental forming have given rise to novel manufacturing methods that are very flexible and have the potential to be profitable for small-batch production and rapid prototyping. The manufacture of various parts using the same tooling system is made possible by the incremental shaping of sheets, which also results in significant material and energy savings. Although incremental forming offers greater flexibility, lower costs, and shorter lead times, a more thorough sustainability assessment is lacking. The research on the technical-economic calculation differences between conventional and incremental forming is presented in this paper in order to provide a summary of the research progress on the sustainability evaluation of incremental forming and to further to explore its potential application. Key words: incremental forming, mould cost, conventional forming."

Feasibility of an acoustophoresis-based system for a high-throughput cell washing: application to bioproduction

Background aimsThese last decades have seen the emergence and development of cell-based therapies, notably those based on mesenchymal stromal cells (MSCs). The advancement of these promising treatments requires increasing the throughput of processed cell for industrialization in order to reduce production costs. Among the various bioproduction challenges, downstream processing, including medium exchange, cell washing, cell harvesting and volume reduction, remains a critical step for which improvements are needed. Typically, these processes are performed by centrifugation. However, this approach limits the automation, especially in small batch productions where it is performed manually in open system. MethodsAn acoustophoresis-based system was developed for cell washing. The cells were transferred from one stream to another via the acoustic forces and were collected in a different medium. The optimal flow rates of the different streams were assessed using red blood cells suspended in an albumin solution. Finally, the impact of acoustic washing on adipose tissue-derived MSCs (AD-MSCs) transcriptome was investigated by RNA-sequencing. ResultsWith a single passage through the acoustic device at input flow rate of 45 mL/h, the albumin removal was up to 90% while recovering 99% of RBCs. To further increase the protein removal, a loop washing in two steps was performed and has allowed an albumin removal ≥99% and a red blood cell/AD-MSCs recovery of 99%. After loop washing of AD-MSCs, only two genes, HES4 and MIR-3648-1, were differently expressed compared with the input. ConclusionsIn this study, we developed a continuous cell-washing system based on acoustophoresis. The process allows a theoretically high cell throughput while inducing little gene expression changes. These results indicate that cell washing based on acoustophoresis is a relevant and promising solution for numerous applications in cell manufacturing.

Influence of parameters of molding by the selective laser melting method on product quality

Purpose. The development and application of additive technologies, which have a high rate of material utilization and significant production flexibility in the case of single and small-scale production, are relevant for solving various types of engineering problems. The final mechanical, technological and operational characteristics of products obtained by additive technologies are affected by a large number of initial parameters that can be varied in order to obtain the necessary properties of the material. The purpose of this work is to study the influence of the parameters of shape formation by the method of selective laser melting, in particular the scanning plan, on the quality of the material and the productivity of production. The methods. To achieve the goal, studies of the microstructure of products obtained by different scanning plans were carried out using optical microscopy, during which the shape of a single track, as well as the structure of the material in different directions of the laser beam, were analyzed. Findings. The effect of particle size, the mechanism of formation of a metal product during selective laser melting is analyzed. The influence of the scanning plan on the porosity, strength, and productivity of manufacturing by the method of selective laser melting is shown. The correct choice of technological parameters, such as the power and speed of the laser beam, the thickness of the metal powder layer, the scanning step between two adjacent single tracks, ensures the minimization of the number and size of defects (pores, cracks, shells) in the product material. The originality. The process of metal powder melting in the process of shaping products by the method of selective laser melting is analyzed. The scheme of formation of a single track is obtained in the case of choosing different scanning schemes. A list of technological parameters, the variation of which affects the properties and quality of the product, has been formed. Practical implementation. The use of additive technologies for the molding of products in single and small-batch production allows to reduce the time of production preparation and reduce the amount of waste. When choosing technological parameters, one should understand their dependence on the final properties of the finished product, because the method of selective laser melting allows to obtain products of different porosity, strength and other properties.

Automatic Gripper-Finger Design, Production, and Application: Toward Fast and Cost-Effective Small-Batch Production

Tactile robot-based assembly line adaptation of new products is still limited by the manual redesign, manufacturing, and exchange of the end-effector setup since the gripper fingers must often be adapted to the geometry of the product components to ensure a successful assembly process. In this article we present an automatic finger design, production, and evaluation pipeline, developed to improve this adaptation process. Two different form-closure–based design principles have been implemented to automatically generate the fingertip geometry: a projected surface representation-based approach as well as a Bézier surface fitting strategy. The resulting fingertips are printed via an automatic production unit and experimentally evaluated based on pick and insertion tasks for three different manipulation objects. To illustrate the potential usage of the introduced design methods for machine learning-based fingertip design approaches, we set up the training and testing process for a neural network-based design method. The proposed automatic fingertip design, production, and application framework represent a step further toward small-batch–size production, since the assembly adaptation effort, flexibility, and scalability are significantly improved.