Medium Batch Research Articles

Transformer neural network based real-time process monitoring and direct visualization of top-down vat photopolymerization

Top-down vat photopolymerization (TVPP) technology is rapidly developing to all of the industries for new products development and manufacturing due to its low cost, fast speed and high precision. The powerful capability of TVPP for large size, highly customized and medium batch production renders it one of the most popular additive manufacturing techniques today. An effective real-time process monitoring method providing timely feedback for part defects, especially in case of print failure, is highly desirable but still rarely reported for TVPP 3D printing. Large 3D objects are normally segmented into smaller parts to reduce the risk of failure and materials waste, resulting in the complexity of building while sacrificing component integrity. Herein, a transformer neural network based real-time and visualized process monitoring (TransRV) was constructed as an effective method to enhance the manufacturing performance and quality. Upon the challenge of visualizing and capturing the real-time fabricated layer from the around liquid photoresin, a real-time dataset including in-situ standard reference images and real-time mask fabricated layers was initially constructed. Based on the dataset foundation, we then developed a novel neural network model for effective segmentation of captured images by introducing multiple attention mechanisms and adopting the architecture of Swin Transformer. The experimental results showed that the real-time taken images during the printing process could be accurately segmented through our designed neural network model. The mIoU, which is the ratio of mean intersection over union, was considered as the main evaluation index in the test set. And the value of mIoU could achieve as high as 96.14 %. On the basis of this result, we further constructed a multiple quality monitoring indicator for quality assessment and defect detection of TVPP process. It was proved that this indicator enabled real-time accurate recognition and in time feedback. The typical defects such as overall collapse and partial missing of the printed parts that usually occur during TVPP process would be timely detected and subsequently stopped printing. Apparently, the methods developed in this work provide a promising strategy to effectively eliminate the material waste and highly improve the productivity. Most importantly, the presented real-time process monitor holds the great potential for quality control and defect detection of widespread TVPP manufacturing.

P-222 Can embryo morphokinetics act as early warning key performance indicators in relation to consumable batching

Abstract Study question Can morphokinetics be used as an early warning indicator of a batch-related effect of oil currently in use in the laboratory on implantation rate? Summary answer Where morphokinetic timings were slower for a batch of oil, implantation rate was also reduced, suggesting they could be used as an early warning system. What is known already The commercialisation of oil means that there are strict manufacturing guidelines leading to consistency between batches. However, this does not mean that minor differences do not exist. Furthermore, oil can undergo peroxidation if stored incorrectly, causing it to become toxic to embryos. The introduction of timelapse incubation has allowed extensive research into several morphokinetic parameters. This research has established time-frames within which each developmental milestone should occur to indicate the likelihood of implantation. Implantation rate (IR) is often used as a key performance indicator in the laboratory however, potential systemic issues may be identified sooner if morphokinetic parameters were used. Study design, size, duration The following morphokinetic parameters were compared to IR to determine if a batch of oil was affecting embryo development; time of division to two cells (t2), five cells (t5), eight cells (t8), time to start of blastulation (tSB) and cell synchronicity between two and eight cells (CS2-8). Data from January 2019 to October 2019 from a single centre were used, and included data from 2008 embryos and 333 patients. Participants/materials, setting, methods Data was exported from the EmbryoScope + [Vitrolife, Sweden]. Data from RIWitness Laboratory Manager [CooperSurgical, Denmark] was utilised to identify when different batches of oil (Ovoil™, Vitrolife) were used within the specified time period. The data from the EmbryoScope+ was then separated by date to signify when a new batch of oil was open. A Kruskal-Wallis test was then used to identify whether the morphokinetic timings differed between batches of oil. Main results and the role of chance There was no significant difference in patient age (p = 0.178) or the number of oocytes collected (p = 0.097) between batches of oil used. There was no significant difference between the morphokinetic timings for each batch of oil used. However, the morphokinetic timings follow the same trend line as the IR for both t2 and t8; where t2 and t8 are higher, the IR for the corresponding batch of oil is reduced. The trend can also be seen in CS2-8. The batch of oil with the lowest IR (25.56%) also had the highest mean time to t2, t8 and tSB compared to the other batches of oil. This corresponds with previous research that identified a correlation between slower embryo development and reduced IR (Meseguer et al., 2011). A clear difference could be seen between the average time taken to reach each developmental milestone and each batch of oil used, perhaps suggesting oil can have an effect, however small, on embryo development. This study suggests that morphokinetic timings could be used as an early warning indicator that a new batch of oil may be affecting development allowing a rapid response by the laboratory team and possible cessation of use pending further investigation. Limitations, reasons for caution Different batches of culture medium were also used throughout this time period and were not introduced at the same time as oil batches. Therefore, the results of this investigation cannot be associated entirely to the introduction of a different batch of oil. Wider implications of the findings This information could be incorporated into an early warning algorithm that could be assessed after a batch of oil was introduced. The use of the batch could then be ceased immediately without waiting for a decrease in IR by which time it would have been used for many more embryos. Trial registration number Not applicable

Improved therapeutic consistency and efficacy of CD317+ MSCs through stabilizing TSG6 by PTX3

BackgroundPreviously, we have demonstrated that the batch variations of human platelet lysate (conventional MSC expansion medium) induce MSC heterogeneity and therapeutic inconsistency. On the other hand, the MSCs expanded with chemical defined medium have improved therapeutic consistency.MethodsIn the current study, we studied the MSC subpopulation composition and variation in different types and batches of MSC expansion medium with scRNA-seq analysis.ResultsMSCs expanded with different batches of media have higher levels of heterogeneity from the perspective of cell subpopulation composition at transcriptome levels and therapeutic inconsistency. The CD317+ subpopulation has enhanced immune suppression activities. And the percentage of CD317+ MSCs within MSCs is tightly correlated with its immune suppression activities, and also contributes to the heterogeneity and therapeutic inconsistency of MSCs. the CD317+ MSCs have increased expression levels of PTX3, which might stabilize the TSG6 protein and improve the therapeutic effectsConclusionsThus, purifying CD317+ MSCs is one efficient strategy to reduce MSC heterogeneity and increase the therapeutic consistency of MSCs.

Vision-based seam tracking for GMAW fillet welding based on keypoint detection deep learning model

Pre-programmed welding robots significantly improved the efficiency and quality of the welds in large batch production. In small and medium batch production, the robots need appropriate sensors to perform well and adapt to the changes and uncertainties in a noisy welding environment. Vision-based sensors enabled by machine learning are making it possible to sense in process previously not measurable. One challenge is developing artificial intelligent models capable of real-time seam tracking, particularly in fillet joints where visual analysis is hindered by non-perpendicular camera angles and arc reflections. In this paper, we propose a vision system that enables automated seam tracking with a collaborative robot. The vision-based deep learning classification model detects the tacks, where the seam is not visible. It is based on a keypoint detection deep learning model that addresses the challenges in distorted and noisy images of fillet joints between the pipes and flanges during the real-time Gas Metal Arc Welding to track the location of the seam in non tack images. The system is optimized for real time seam tracking by proposing the appropriate input image size. Multiple images and multiple points are also considered to provide a controllable signal of the location of the seam with less errors and outliers. Our proposed model can track the seam with more than 80 percent accuracy for errors less than 0.3 mm in fillet joints. The high accuracy of the proposed method would result in fewer flaws and defects and reduced rework, resulting in significant cost saving in manufacturing. The real-time monitoring also enables the adaptability to slight variations in gap.

Experimental investigation of design parameters on geometrical accuracy of selective laser sintered parts

Selective Laser Sintering (SLS) is becoming a popular choice for the fabrication of polymer parts of medium batch sizes. Understanding the effect of various factors influencing the geometrical accuracy of parts fabricated with selective laser sintering is key to ensuring consistent quality. This study attempts to evaluate the effects of different design parameters on a part-to-part variation in the geometrical accuracy of fabricated parts within the same build. A three-level Box-Behnken response surface methodology was adopted with the part orientation, part thickness, build position, and feature size as factors to investigate the impact on geometrical accuracy. A specimen comprising various through holes of different thicknesses was fabricated using SLS. The part-to-part variation in dimensional accuracy and circularity was inspected with a video measuring system to evaluate the effect of factors. The part orientation, part thickness, and build position impart a stronger influence on dimensional accuracy while the circularity was highly affected by the part orientation of the specimen. Further, the geometrical accuracy of the fabricated features was optimized separately with different sets of factors and validated experimentally.

Preparation of Nanosized Pharmaceutical Formulations by Dual Centrifugation.

Dual centrifugation (DC) is an innovative in-vial homogenization and in-vial nanomilling technique that has been in use for the preparation of liposomes for more than one decade. Since then, DC has continuously been developed for preparing various liposomes and other lipid nanoparticles including emulsions and solid lipid nanoparticles (SLNs) as well as polymersomes and nanocrystals. Improvements in equipment technology have been achieved over the past decade, so that DC is now on its way to becoming the quasi-standard for the simple, fast, and aseptic production of lipid nanoparticles and nanocrystals in small and medium batch sizes, including the possibility of simple and fast formulation screening or bedside preparations of therapeutic nanoparticles. More than 68 publications in which DC was used to produce nanoparticles have appeared since then, justifying an initial review of the use of DC for pharmaceutical nanotechnology.

A model to account for magnetic permeability changes resulting from edge damage caused by laser cutting in a high performance cobalt-iron alloy

Laser cutting is the mainstay of electrical machine stator core manufacture for prototyping and for high value, small and medium batch sizes. However, it can introduce localized damage into electrical steels, with reduction in magnetic permeability and increase in core loss in regions adjacent to the edge. These phenomena have been studied in Silicon-iron alloys, but there is little published data on Cobalt-iron. This paper presents experimental measurements on magnetic edge damage effect in Cobalt-iron alloys due to laser cutting. The paper then uses magnetic measurements for an increasing number of cuts in test samples to develop a model that represents the deterioration of magnetic permeability with distance from the cut edge, including cumulative damage effects from multiple cuts. The model is suitable for incorporation into finite-element models, either as a continuous function of position or to generate individual magnetization curves for discrete layers in finite-element mesh. The paper concludes by using the model to generate a series of magnetization curves which include the damage effect and in turn uses these to predict the net magnetic behavior of a series of rectangular strips. Good agreement is obtained between these predictions and measurements of samples from the same batch of Cobalt-iron.

Meat extract casein peptone agar – A novel culture medium for the enumeration of Bacillus endospores in commercial products

Here we propose a novel culture medium, Meat Extract Casein Peptone (MECP) agar, to support the enumeration of Bacillus endospores in commercial products. The formulation is the result of screening eight different veterinary, pharmaceutical, and industrial grade peptones for the ability to support the formation of small, well-defined Bacillus colonies on solid culture medium. The impact of agar purity, agar formulation rate, and metal cation additives were examined in prototype medium batches prepared from preferred peptone inputs. A customized plate counting assay based on the resultant MECP agar formulation was compared with standardized pour-plate and spread-plate assays (ISO 4833) and flow cytometry for the ability to accurately enumerate five Bacillus-based biostimulants and biofertilizers. Estimations of Bacillus endospore concentration generated by the customized spread-plate assay were significantly higher than those produced by ISO 4833 pour-plate and spread-plate assays for four out of the five tested products and were in better agreement with flow cytometry values; however, flow cytometry values were numerically higher than values returned by both plating methods. Both flow cytometry and plating assays based on MECP or similar culture media represent potential candidates for standardization and validation through organizations such as ISO and AOAC International for the enumeration of Bacillus-based products.

A Review on Metal Binder Jetting 3D Printing

Binder jetting (BJ) is one of the major metal additive manufacturing (AM) technology used for the production of intricate metal components using a layer-by-layer approach. It belongs to the more general family of processes known as powder bed fusion procedures, in which a bed of metal powder is first selectively fused together with the help of a binder and then sintered in order to produce the final metal component. Binder Jetting is the sole non-fusion-based powder bed additive manufacturing technology; this means that, unlike laser-based AM procedures, the resulting parts are completely free of residual stresses. Small to medium batch production can be cost-effective due to lower tooling and setup expenses. This analysis focuses on the capacity of some of the most important engineering materials, including titanium, Inconel and stainless steel, to produce intricate geometries with a high degree of precision and accuracy. These materials find extensive use across many applications, including defence, industry, biomedical, aerospace, and other fields.

Optimization and prediction of incremental sheet forming parameters of Titanium grade 5 sheet using a response surface methodology and artificial neural network

Single point incremental forming (SPIF) is an advanced, flexible, and cost-effective approach for producing complicated sheet metal objects quickly. Because of its low equipment cost, the process is best suited toward low or medium quantity batch production as the conventional stamping method remains cost-effective only for mass manufacture. During SPIF formation of titanium grade 5 materials, a response surface methodology and artificial neural network (ANN) model was created to optimize and estimate wall angle (Ømax) and average surface roughness ( Ra). The ANN model is developed using feed forward back propagation networks. Various combinations of transfer functions and number of neurons were used to create the ANNs (3- n-1, 3- n-2). The confirmation runs have been used to ensure that the ANN anticipated and practical findings have been in agreement. The generated ANN model (3- n-1) was capable of accurately forecasting the results of the experiment, with an overall R-value and Mean Square Error (MSE) of 0.99987 and 0.010905 for Ra, and 0.99999 and 0.00700 for wall angle. The best 3- n-2 models has an average R-value of 0.99992 and MSE of 0.05532, respectively. As a consequence of rapid ANN modeling technique, it became discovered that technical effort inside the SPIF process could be decreased.

Cost Model Framework for Pieces Additively Manufactured in Fused Deposition Modeling for Low to Medium Batches.

The cost impact of implementing additive manufacturing (AM) in the fabrication process is nowadays an issue. The scope of this research is to establish a cost model framework that can predict the cost of a piece in a low to medium batch considering fused deposition modeling (FDM) printing parameters. Every enterprise wants to increase its internal capabilities for tools, prototypes, and the production of pieces for maintenance purposes. FDM is an AM technology increasingly used in aerospace, automotive, and many other sectors. The research methodology consists of developing a cost model based on the extrusion-type AM process for any given machine characteristics and comparing the cost per piece based on diverse lot sizes and raw materials. Two test cases were simulated to show the usefulness of the cost model, one with a conventional polymer material (acrylonitrile butadiene styrene) and another with a high-performance material (polyetheretherketone); materials with very different costs, machine technical requirements, and energy consumption. The framework could be used to predict the best machine size and material type that could be suitable for a certain situation. The strength of our approach lies in the energy cost calculus, which is dependent on machine capabilities and size.

Tagging and tracking oil-gas mixtures in multiphase pipelines

Pipeline transportation of multiphase products, such as gas and oil mixtures, exhibits complex and varying flow regimes: as a result, analytical approaches or conventional methods cannot accurately describe the composition or the propagation characteristics of the fluid mix inside the transportation system itself. We address such an issue by presenting a methodology, driven by the data and applied to a real case history, where basic pressure transients are used to tag and track, along a pipeline, different batches of a multiphase medium. Several statistical indicators, computed from the pressure data and on different window lengths, are employed to train a machine learning model, which learns to distinguish the characteristic behavior of two different oil-gas slugs: in practice, each different combination of fluid phases (in terms of gas/oil ratio in a given batch of product) and each different sequence of slugs (in terms of gas/oil ratio variability between successive batches) behaves like a coded tag linked to the flowing fluid. The key innovation consists in the possibility of tracking such multiphase slugs along the flowline and at each monitoring station: this allows one to determine in real-time the fluid composition entering/exiting the line, its position, and its movement along the pipe. As such, we obtain also a virtual metering system, able to provide estimates of the flow rate and phases ratio. Moreover, by having several recording stations accurately synchronized, one can also leverage real-time transmission and multichannel processing of the data, enabling the opportunity for online monitoring applications. The results on the test cases and the accuracy scores obtained for the metrics considered validate the tagging and tracking approach.

Development of a technology for the preparation of a dry nutrient medium for anthrax vaccine production

Currently, submerged cultivation of the Bacillus anthracis STI-1 strain for live anthrax vaccine production requires liquid nutrient media, which have disadvantages of a short shelf life (no more than one month) and a narrow range of storage temperatures (2–8 °С). Dry media, in contrast, have a number of indisputable advantages: such media are transportable and easy to use, have a standard capability to retain properties, and can be stored without preservatives at 2–30 °С for 2–5 years. The aim of this work was to develop a technology for the preparation of a dry nutrient medium for anthrax vaccine production. Materials and methods: The study used the Bacillus anthracis STI-1 vaccine strain and a nutrient medium for its cultivation, containing a 70:30 mixture of an enzymatic digest of casein and a pre-processed corn extract solution. Drying of the nutrient medium was carried out on a spray-drying unit. The authors evaluated physicochemical parameters of experimental medium batches. The shelf life was determined by an accelerated stability study. The dry nutrient medium was used to produce a live anthrax vaccine. Quality attributes of the vaccine were assessed for compliance with regulatory requirements. Results: The authors developed the dry media production technology. According to it, the liquid nutrient medium is fed to the drying unit at a rate of 20–25 dm3/h. The spray air pressure is 0.02 MPa. Temperatures at the drying chamber inlet and outlet are 118–122 °С and 85–90 °С, respectively. The technology was used to obtain 3 experimental batches of the dry medium. The study results demonstrate that the technology is reproducible, and the tested quality attributes of experimental medium batches are consistent with the requirements. According to the accelerated stability study, the shelf life of the dry nutrient medium at 2–30 °С is at least 3 years. Experiments demonstrated the possibility of using the dry nutrient medium for live anthrax vaccine production. Critical quality attributes of the vaccine obtained with the medium met regulatory requirements. Conclusions: The developed technology allows for the production of a standard dry nutrient medium with a prolonged shelf life, which is convenient for live anthrax vaccine production.

Impact of Molecular Weight on Molecular Doping Efficiency of Conjugated Polymers and Resulting Thermoelectric Performances

AbstractThe effect of molecular weight of a series of conjugated polymers (CPs) on the doping efficiency, electrical conductivity, and related thermoelectric properties of doped CPs is studied. Low (L), medium (M), and high (H) molecular weight batches of PDFD‐T polymers, based on difluorobenzothiadiazole and dithienosilole moieties, are synthesized and denoted as PDFD‐T(L), PDFD‐T(M), and PDFD‐T(H), respectively. Furthermore, to compare the effects of different donor moieties, donor units of PDFD‐T(L) are structurally modified from thiophene to thienothiophene (TT) and dithienothiophene (DTT), denoted as PDFD‐TT(L) and PDFD‐DTT(L), respectively. After doping the CPs with FeCl3, d‐PDFD‐T(H) exhibits an electrical conductivity of 402.9 S cm−1, which is significantly higher than those of d‐PDFD‐T(L), d‐PDFD‐T(M), d‐PDFD‐TT(L), and d‐PDFD‐DTT(L). The highest power factor of 101.1 µW m−1 K−2 is achieved through organic thermoelectric devices fabricated using PDFD‐T(H). Through various characterizations, it is demonstrated that CPs with a high molecular weight tend to have a high carrier mobility while maintaining their original crystallinity and good charge transport pathways even after doping. Therefore, it is suggested that optimizing the molecular weight of CPs is an essential strategy for maximal power generation from their doped CP films.

Medium and large scale preparation of Nanostructured Lipid Carriers of asenapine maleate: Quality-by-design based optimization, production, characterization and performance evaluation

In the present study, scale-up of preparation of Asenapine maleate (ASPM) loaded Nanostructured lipid carriers (NLCs) to medium as well as the large scale was performed with the aid of Quality-by-Design (QbD) approach. High-pressure homogenization (HPH) was used to scale up the ASPM loaded NLCs to medium (40 mL) and large-scale (300 mL) batches. The statistical experimental design was employed to optimize the HPH parameters and the results of the design showed that the size of ASPM loaded NLCs decreased with the increase in pressure and number of cycles of HPH. Also, increasing the number of cycles resulted in a slight increase in the %drug entrapped. FTIR and DSC were used to assess the compatibility between drug and excipients. The shape and surface morphology of NLCs studied by Transmission Electron Microscope revealed a spherical shape with an approximate size of less than 100 nm. The cytotoxicity of NLCs using MTT assay in Caco2 cells demonstrated the safety of ASPM-NLCs. Further, in vivo pharmacokinetics and efficacy studies strengthened the applicability of ASPM-NLCs produced at a large scale for further in vivo and clinical environments.

A new lubrication approach in the SPIF process: Evaluation of the applicability and tribological performance of MQL

The abrupt changes in the customer demands and the need to achieve versatility in production for satisfying the different needs of consumers have resulted in the development of rapid prototyping processes. Single Point Incremental Forming (SPIF) is a forming method which doesn’t require dies for production and thus enables to greatly reduce the manufacturing costs for low to medium batch productions while enabling versatile manufacturability. One of the major disadvantages of this process is the poor surface quality of formed parts due to friction between tool and sheet interfaces. For this reason, suitable lubrication techniques and the use of lubricants are of great importance in obtaining the desired surface quality. In this study, the Minimum Quantity Lubrication (MQL) technique, which provides significant improvements in metal cutting processes with its effective lubricating feature, has been applied for SPIF process to investigate its effectiveness in SPIF processes. For this purpose, a series of experiments have been carried out by forming 7128 sheet metals with SPIF process in a CNC vertical machining center. In the experiments, SPIF parameters (feed rate, tool stepdown, etc.) have been kept constant and the effects of MQL parameters on surface roughness/topography, thickness distribution, roundness deviation, angular deviation have been focused. Three different pressures (4, 6, and 8 bar), three different flow rates (50, 75, and 100 mL/h) and three different vegetable-based oils with different viscosities have been selected as MQL parameters. In addition, 7128 sheet metal has been formed with the SPIF process by using a paste lubricant for the comparison of paste lubricated and MQL assisted SPIF process. Finally, friction tests have been carried out in a ball-on-disk device to determine the friction coefficients of the oils. Experimental results have shown that the increase in pressure has greatly increased the surface quality and dimensional accuracy, while the increased flow rate level improved the surface quality and dimensional accuracy up to a certain value (75 mL/h). It has been concluded that the surface quality can be improved by 14.60% with the MQL assisted SPIF process over the paste lubricated SPIF process, which has proved the applicability and superiority of MQL technique for SPIF processes.

Digital generating method for cylindrical helical gear based on indexable disk milling cutter

To solve the problem of low efficiency in digital generating machining for producing small or medium batches of helical gears, a method to improve the machining efficiency with an indexable disk milling cutter is presented in this paper. First, the mathematical model of the tooth profile and the indexable disk milling cutter are established. Second, according to the spatial free-form envelope theory, the overall planning scheme of the tool path is given; the relative position and the relative transformation matrix of the tool and tooth profile during digital generating machining using the indexable disk milling cutter are solved, the simulation cutting and actual cutting experiments are conducted, and the cutting efficiency per unit time and cutting simulation time of the two tools under the same deformation conditions is obtained through a finite element analysis experiment. The results show that the cutting efficiency of the indexable disk milling tool was 2–3 times higher than that of the end mill cutter.

Formulation of Measurement Sampling Plan for Small and Medium Batch Products in Supply Chain

The article studies the supply chain of suppliers and manufacturers, considering the overall benefits of the supply chain, the measurement sampling plan is the small batch sampling plan with the smallest amount of sampling and the strongest discriminative ability. If the quality characteristic data is a measurement value, and the inspection workload is large and the inspection cost is high, it is recommended to adopt the measurement sampling plan based on the Laplace distribution. On the premise of ensuring quality, try to reduce the number of inspected samples as much as possible to reduce the workload and cost of inspection.

PRODUCTION OF INDIVIDUALISED MULTI-MATERIAL COMPONENTS USING A ROBOT-BASED PROCESS CHAIN

The production of individual work pieces in small to medium batch sizes requires an adaptation of the manufacturing strategy. Particularly, the manufacturing of multi-material components out of metal and plastic is characterized by high production costs as well as high production times. To resolve this challenge, a new, modular process chain for the production of these structures in a single manufacturing cell was developed. In this cell, a robot manufactures multi-material components with multiple end-effectors in several successive process steps. In the first step, interlocking structures are manufactured on a metal part by a surface structuring tool. Afterwards, an extruder is used to add a thermoplastic onto the structured metal part. Due to mechanical interlocking effects, the applied thermoplastic shows improved adhesion behavior. A study was conducted to analyze the achievable joint strength of the additive material application onto the structured metal samples. Investigations to determine the achievable manufacturing quality of a robot guided milling process for multi-material parts have been carried out. A recently developed suction hood is used to capture the metal and plastic chips. In this paper, the results regarding the efficiency of the individual end-effectors, including the extraction hood, are presented and it is demonstrated how they interact within the robot-based process chain.

Flexible Incremental Roller Flanging process for metal sheets profiles

Metal forming processes usually require high investment due to expensive plants and machinery, and, above all, the need of tailored tooling, which often limits their applicability to medium or large size production batches. Such economic issues become even more critical as the shape complexity or the parts dimensions rise, due to increased costs for material and equipment. As a consequence, to play in the metalforming market companies have to be capital intensive, which means that they have a high financial exposition and are heavily exposed to changes in market demands. In such scenario, made even more complex by the Covid-19 pandemic, flexibility and cost reductions have become fundamental, especially because the short demand is pushing the production towards small batches and highly personalized products. With regard to metal sheet parts, incremental forming appears particularly suitable to accomplish the new market trends, thanks to the use of simpler and cheaper tools to obtain even complex shapes thought multiple passes deformations. The paper presents a novel incremental forming machine to manufacture metal sheets long profiles, which uses one or more couples of rollers controlled by a numerical control. The innovative forming machine is presented together with the numerical model used to assess the influence of the main process parameters. Finally, a case study is evaluated to quantify the economic benefits of the proposed process and machine.