Manufacturing Control Research Articles

Tailoring chiral optical properties by femtosecond laser direct writing in silica

An object that possesses chirality, that is, having its mirror image not overlayed on itself by rotation and translation, can provide a different optical response to a left- or right-handed circular polarized light. Chiral nanostructures may exhibit polarization-selective optical properties that can be controlled for micro-to-nano optical element engineering. An attractive way to induce such complex nanostructures in three-dimension in glass is femtosecond laser direct writing. However, the mechanism of femtosecond laser induced chirality remains to be unveiled due to complex physical and chemical processes occurring during the ultrashort light-matter interaction. Here, a phenomenological model is proposed and is built on two-layers phase shifters to account for this laser-induced optical chirality in an initially achiral material (silica glass). This model is based on the observation that femtosecond laser induced nanogratings own two principal contributions to its aggregate birefringent response: a form and a stress-related one. By refining this formalism, a multilayer approach is developed to imprint on demand optical rotation. Values up to +/-60° at 550 nm within an optimal 80 μm thickness in silica glass are possible, corresponding to the highest value in a glass to date. These results provide new insights of circular-optical control in micro-nano optical manufacturing and open new opportunities for photonics applications.

Implementation of HACCP in the production of Egyptian cheeses: A review

AbstractSignificant difficulties about the function of Hazard Analysis and Critical Control Points (HACCP) in manufacture of three genuine varieties of Egyptian cheese, namely Domiati, Karish, and Ras's cheeses, are covered in this review. Benefits of implementing HACCP include complementing other quality management systems, improving food safety, making better use of resources, boosting productivity and quality, providing better security and lowering inspection rates, responding to issues quickly and effectively, and fostering international trade cooperation. The setting is important for the manufacturing, security, and quality control of cheese. A common household item across the world that is fermented dairy‐based and high in protein, calcium, amino acids, vitamins, phosphorus, and fat is cheese. Egypt consumes more cheese than any other country in North Africa, which is helped by the wide selection of cheeses on offer, includes soft, brined, salted, semi‐soft, and hard cheeses. Three illustrated graphics explain the manufacturing flow of each cheese with reference to critical control points determination were created using text that was obtained from the references that were accessible. As lists of dangers, important control limits, monitoring, and corrective measures for cheese manufacturing, three exemplary tables were equally given. These provide readers with a more thorough summary of all results.

Control-Centric Data Classification Technique for Emission Control in Industrial Manufacturing

Artificial intelligence-based hardware devices are deployed in manufacturing units and industries for emission gas monitoring and control. The data obtained from the intelligent hardware are analyzed at different stages for standard emissions and carbon control. This research article proposes a control-centric data classification technique (CDCT) for analyzing as well as controlling pollution-causing emissions from manufacturing units. The gas and emission monitoring AI hardware observe the intensity, emission rate, and composition in different manufacturing intervals. The observed data are used for classifying its adverse impact on the environment, and as a result industry-adhered control regulations are recommended. The classifications are performed using deep neural network analysis over the observed data. The deep learning network classifies the data according to the environmental effect and harmful intensity factor. The learning process is segregated into classifications and analysis, where the analysis is performed using previous emission regulations and manufacturing guidelines. The intensity and hazardous components levels in the emissions are updated after the learning process for recommending severe lookups over the varying manufacturing intervals.

Machine learning based fault detection approach to enhance quality control in smart manufacturing

In recent days the quickly changing manufacturing environment has pushed organizations to accomplish more consumer satisfaction by improving item quality, lessening production cost, and acknowledging maintainability. Anomaly recognition impacts the nature of items and it is typically directed through visual quality assessment. The visual quality review of an item can be performed either physically or naturally. This research proposes a novel technique in manufacturing industry-based fault detection and control management using machine learning technique. Here the input data has been collected as manufacturing fault historical data by IoT (internet of things) module. This data has been processed for noise removal, normalization, and smoothening. The processed data features have been extracted by using kernel principal vector component analysis. Gaussian quadratic Kernelized Generative Adversarial Network has been used to manage the control of extracted features. The experimental analysis has been done in terms of RMSE, MAP, AUC, F-1 score, recall, accuracy, and precision. Upon reviewing our procedures after our research and testing, we discovered that Auto-Encoder Neural Network is the best effective algorithm for identifying a production line failure. One-Class SVM gives the highest accurate findings in our machine-based investigations.

Minimizing total completion time in large-sized pharmaceutical quality control scheduling

This paper proposes an algorithm for the effective scheduling of analytical chemistry tests in the context of quality control for pharmaceutical manufacturing. The problem is formulated as an extension of a dual resource constrained flexible job shop scheduling problem for the allocation of both machines and analysts resources for analytical laboratory work of real dimensions. The formulation is novel and custom made to fit real quality control laboratory. The novelty comes from allowing multiple analyst interventions for each machine allocation while minimising the total completion time, formulated as a mixed integer linear programming model. A three-level dynamic heuristic is proposed to solve the problem efficiently for instances representative of real world schedules. The CPLEX solver and a Tabu Search algorithm are used for comparison. Results show that the heuristic is competitive with the other strategies for medium-sized instances while outperforming them for large-sized instances. The dynamic heuristic runs in a very short amount of time, making it suitable for real world environments. This work is valuable for the development of laboratory management solutions for quality control as it presents a way to provide automatic scheduling of resources.

Holistic Nanowire Laser Characterization as a Route to Optimal Design

AbstractNanowire lasers are sought for near‐field and on‐chip photonic applications as they provide integrable, coherent, and monochromatic radiation: the functional performance (threshold and wavelength) is dependent on both the opto‐electronic and crystallographic properties of each nanowire. However, scalable bottom‐up manufacturing techniques often suffer from inter‐nanowire variation, leading to differences in yield and performance between individual nanowires. Establishing the relationship between manufacturing controls, geometric and material properties, and the lasing performance is a crucial step toward optimisation; however, this is challenging to achieve due to the interdependance of such properties. Here, a high‐throughput correlative approach is presented to characterise over 5000 individual GaAsP/GaAs multiple quantum well nanowire lasers. Fitting the spontaneous emission provides the threshold carrier density, while coherence length measurements determine the end‐facet reflectivity. The performance is intrinsically related to the width of a single quantum well due to quantum confinement and bandfilling effects. Unexpectedly, there is no strong relationship between the properties of the lasing cavity and the threshold: instead the threshold is negatively correlated with the non‐radiative recombination lifetime of the carriers. This approach therefore provides an optimisation strategy that is not accessible through small‐scale studies.

Parametric study of melt pool geometry in hybrid plasma arc-laser melting process for additive manufacturing application

Wire-based hybrid arc-laser additive manufacturing is suitable for producing large metallic parts (metres in scale) with high deposition rates and near-net-shape. In this process, the surface quality and dimensional accuracy of the deposited parts are determined by the melt pool geometry. However, how to control the melt pool in the hybrid process is complex due to the multiple parameters that can be used. In this study, control of melt pool geometry by investigating different process parameters, including laser power, travel direction, arc-laser separation distance, laser beam size, and arc current in the hybrid plasma transferred arc (PTA)-laser process, was studied systematically. It was found that a larger melt pool was achieved with the PTA-leading configuration compared to that with the laser-leading configuration due to a higher laser absorption occurred with the former configuration. The melt pool was enlarged by either increasing the laser power or arc current due to the increased energy input. However, if the laser power density is high enough to determine the melt pool depth, the increasing arc current has very little effect on melt pool depth but only increases the melt pool width. In addition, the melt pool became shallower and wider when using a larger laser beam. The arc-laser separation distance had a minor effect on the melt pool geometry due to the fixed energy input used in the studied cases. The results of this study provide a reference for melt pool control in wire-based hybrid arc-laser additive manufacturing.

Influence of oxygen on performance of multi-principal element alloy as braze filler for Ni-base alloys

In manufacturing of multi-principal element alloys (MPEAs), the casting process is often a primary point of oxygen introduction to the material system, which was demonstrated by the laboratory scale button arc-melting process. Oxygen introduction raises concerns for the mechanical performance of these alloys if employed as structural materials alone or in engineering applications, such as serving as filler materials to enable joining of similar or dissimilar alloy pairs that are conventionally considered difficult to join. In this work, oxide inclusions in an as-cast off-equiatomic MnFeCoNiCu MPEA and Ni-base alloy braze joints made with this MPEA were evaluated by synchrotron x-ray diffraction mapping and electron microscopy. MnO was found to be prevalent throughout the cast MPEA and was chemically reduced during brazing by trace Al from the base material, Ni-base Alloy 600. Incomplete reaction of the MnO with Al, and some alternative reaction with Cr, left a mixture of MnO, Al2O3, and Cr2O3 in the as-brazed joint, with the oxides concentrated near the braze centerline due to directional solidification. In the braze joints, the non-oxide constituent phases detected were an FCC matrix and particles of Cr23C6, Cr7C3, and TiN which are all native to Alloy 600. The evolution of oxides within the brazed joints at elevated service temperatures of 600–800 °C was also evaluated. While MnO and Al2O3 were stable during high-temperature service, Cr2O3 particles grew to several hundred microns, with dissolved oxygen in the MPEA providing a significant source for oxide growth. Comparing tensile performance of the as-brazed condition with post-service conditions showed that the evolution of oxide particles contributed to an increase in strength and decrease in ductility of the brazed joints. Evaluating particle morphologies among fracture surfaces of individual specimens demonstrated that large Cr2O3 particles and continuous cluster networks of Al2O3 were the features most detrimental to total elongation. Hence, unmitigated evolution of oxygen-containing species during brazing and service conditions is detrimental to the ductility of the brazed joints, which highlights the importance of oxygen control in initial manufacturing of MPEAs for engineering applications.

Protective effects of conditioned media of immortalized stem cells from human exfoliated deciduous teeth on pressure ulcer formation.

Pressure ulcers (PUs) are increasing with aging worldwide, but there is no effective causal therapy. Although mesenchymal stem cells (MSCs) promote cutaneous wound healing, the effects of the conditioned medium (CM) of MSCs on cutaneous PU formation induced by ischemia-reperfusion injury have been poorly investigated. To address this issue, herein, we first established an immortalized stem cell line from human exfoliated deciduous teeth (SHED). This cell line was revealed to have superior characteristics in that it grows infinitely and vigorously, and stably and consistently secretes a variety of cytokines. Using the CM obtained from the immortalized SHED cell line, we investigated the therapeutic potential on a cutaneous ischemia-reperfusion mouse model for PU formation using two magnetic plates. This is the first study to show that CM from immortalized SHEDs exerts therapeutic effects on PU formation by promoting angiogenesis and oxidative stress resistance through vascular endothelial growth factor and hepatocyte growth factor. Thus, the CM of MSCs has potent therapeutic effects, whereas these therapies have not been implemented in human medicine. To try to meet the regulatory requirements for manufacturing and quality control as much as possible, it is necessary to produce CM that is consistently safe and effective. The immortalization of stem cells could be one of the breakthroughs to meet the regulatory requirements and consequently open up a novel avenue to create a novel type of cell-free regenerative medicine, although further investigation into the quality control is warranted.

Image Analysis Based Evaluation of Print Quality for Inkjet Printed Structures

Inkjet printing for printed electronics is a growing market due to its advantages, including scalability, various usable materials and its digital, pixel based layout design. An important quality factor is the wetting of the ink on the substrate. This article proposes a workflow to evaluate the print quality of specific layouts by means of image analysis. A self-developed image analysis software, which compares a mask with the actual layout, enables a pixel-based analysis of the wetting behavior by the implementation of two parameters called over- and underwetting rate. A comparison of actual and targeted track widths can be performed for the evaluation of different parameters, such as the tested plasma treatment, drop spacing (DS) and substrate temperature. To prove the functionality of the image analyses tool, the print quality of Au structures inkjet printed on cyclic olefin copolymer (COC) substrates was studied experimentally by varying the three previously mentioned parameters. The experimental results showed that the wetting behavior of Au ink deposited on COC substrates influences various line widths differently, leading to higher spreading for smaller line widths. The proposed workflow is suitable for identifying and evaluating multiple tested parameter variations and might be easily adopted for printers for in-process print quality control in industrial manufacturing.

The promotion and application of green remanufacturing: a case study in a machine tool plant.

Low parts utilization, high resource consumption, and low profit margins have become the main factors hindering the development of machine tool remanufacturing in China. A machine tool manufacturing company was taken as a case to investigate the improvement of the remanufacturing production line. The remanufacturing workshop and production line of the case enterprise have been completely re-planned, adding remaining life assessment, additive manufacturing, quality monitoring, and reassembly quality control. After applying the new production line, the energy consumption and water consumption of each remanufacturing machine tool were reduced by 29.87 kgce and 0.042 m3, respectively, and the pollutants generated were reduced by 4.352kg. With the increase in remanufactured machine tool capacity, the part reutilization has increased by 26.9%. Despite satisfactory results, machine remanufacturing still faces many difficulties in China. Combined with case enterprises, the current situation of machine tool remanufacturing in China was discussed, and several suggestions for promoting remanufacturing in Chinese manufacturing companies were put forward.

Layer width control in robotic pulsed gas tungsten arc additive manufacturing through composite sensing of vision and arc

ABSTRACT Monitoring and control of layer geometry in robotic-pulsed gas tungsten arc additive manufacturing (GTA AM) are essential and challenging issues. This study attempts to realize controllable layer width via imposing a closed-loop controller based on a composite sensing of vision and arc. A vision sensor is utilized to monitor the layer width, and an arc voltage sensor capable of characterizing the arc length is introduced to calibrate the vision sensor. The image acquisition time for layer width is determined via analyzing the features of successive molten pool images, i.e. 80 ms after the rising edge from the base current to the peak current. Image processing procedures are developed to determine the layer width. A parameter self-adjusting Fuzzy (PSA-Fuzzy) controller is designed to control the layer width by adjusting the peak current. Closed-loop tests confirm that the PSA-Fuzzy controller can significantly increase the layer width consistency in robotic pulsed GTA AM.

Development of a virtual quality gate concept based on high-potential tests for lithium-ion battery cell manufacturing

Lithium-ion batteries (LIB) are considered a prominent energy storage technology, especially in the field of electromobility. In this sense, early quality control of battery cell manufacturing is crucial as it can increase energy and material efficiency by stopping further production of critical cells. This paper proposes a virtual quality gate (VQG) concept for inline quality control of battery cell manufacturing. Based on that, only the cells that meet the predefined quality requirements can proceed to the next process steps. For quality control, the VQG includes high-potential tests (HiPot), a measurement method to characterize the electrical insulation properties of separator layers under a defined electrical voltage. As a use case, the Effects of the lamination process of electrodes and separators on cell quality are investigated using the VQG. Data-driven modeling is implemented to predict and classify cell quality concerning the process parameters of lamination. As a result, early-failure detection and better decision-making for battery cell manufacturing are achieved, increasing efficiency from both economic and environmental perspectives.

Redesigning industrial composite production planning and control for energy awareness

The European Union's requirement for eliminating greenhouse gas emissions from all value chains by 2050 affects most of the manufacturing activities all over the continent. The industrial production of composite parts, favored for new designs throughout the aerospace industry, does not constitute an exemption. For securing global competitiveness, CFRP manufacturers need to adapt to increasing fluctuations in energy supply and prices, induced by a growing share of renewable energy sources. Besides employing more efficient production technologies, decoupling of labor and energy intensive tasks will play a key part. Thereby, energy intensive tasks can be performed while general energy supply is high and demand is low, leading to comparatively lower prices. The perspective of energy supply and price becomes a crucial part in the design of modern production planning and control systems, not only for smokestack businesses, but for small and medium load energy consumers as well. In this contribution, a mathematical representation for modeling industrial scale composite manufacturing is proposed. Beside manufacturing's fundamental production planning and control constraints, CRFP manufacturing's very own peculiarities are outlined and considered as well. It is shown how the virtual mathematical representation of a CFRP manufacturing environment can assist in its energy aware redesign and optimization.

Thermoelectric Printhead Cooler for a Stable Process and Curing Control in RTV-2 Silicone Additive Manufacturing by Direct Ink Writing

The direct additive manufacturing, such as Direct Ink Writing (DIW), of silicone parts holds cost and complexity advantages. However, for extruding strands of low viscosity heat curing silicone rubbers, a build plate temperature of up to 90°C is used, which comes with the challenge of early vulcanization inside the printhead. Thus, this paper presents a thermoelectric cooler for universal printheads. At a build plate temperature of 90°C it prolongates vulcanization by 198.5 % (∆tpot life = 508.8 s), which allows a reduction of print speed for higher quality. Additionally, the influence of external temperature is reduced and the viscosity can be controlled.

Stability in Reinforcement Learning Process Control for Additive Manufacturing

Reinforcement Learning (RL), as a machine learning paradigm, receives increasing attention in both academia and industry, in particular for process control. Its trial-and-error concept, along with its data-driven nature, make RL suitable for process control in complex tasks, where the control task and framework can be formulated flexibly. However, there are still challenges that need to be addressed in order for RL to be introduced into the control mainstream, in particular for critical processes. A major challenge in RL is that there is no guarantee for robust, stable RL process control. This is a key impediment to RL implementation on tasks for which stability is an important requirement. Additive Manufacturing (AM) is an example of such process control task, since the very high complexity of the manufacturing process makes it suitable for RL process control, while stable performance is a necessity. However, one has to firstly understand performance and stability as a key requirement. In this paper, we reflect on stability approaches in RL and we investigate the stability requirements for AM. Our AM case study provides intuition and encourages further research for stable RL that would unlock potential for adoption and implementation of RL in AM applications. Research in the proposed direction would also have the potential for impacts to other process control sectors, in critical applications, where appropriate utilisation of stable RL control could bring significant advantages.

Ex vivo 3D scanning and specimen mapping in anatomic pathology

Structured light three-dimensional (3D) scanning is a ubiquitous mainstay of object inspection and quality control in industrial manufacturing, and has recently been integrated into various medical disciplines. Photorealistic 3D scans can readily be acquired from fresh or formalin-fixed tissue and have potential for use within anatomic pathology (AP) in a variety of scenarios, ranging from direct clinical care to documentation and education. Methods for scanning and post-processing of fresh surgical specimens rely on relatively low-cost and technically simple procedures. Here, we demonstrate potential use of 3D scanning in surgical pathology in the form of a mixed media pathology report with a novel post-scan virtual inking and marking technique to precisely demarcate areas of tissue sectioning and details of final tumor and margin status. We display a sample mixed-media pathology report (3D specimen map) which integrates 3D and conventional pathology reporting methods. Finally, we describe the potential utility of 3D specimen modeling in both didactic and experiential teaching of gross pathology lab procedures.

Assessment Of Bacterial And Fungal Contamination In Common Pharmaceuticals And Their Public Health Implications

Pharmaceutical contamination by microorganisms, including bacteria and fungi, poses significant public health risks, as contaminated drugs can lead to severe infections, treatment failures, and compromised patient safety. This study investigates microbial contamination in a range of commonly used pharmaceutical products. For bacterial contamination, Troycaine, Synim, Methdilazine, and Vericose Vein were analyzed using nutrient agar. The results indicated the presence of Gram-positive bacteria in all samples: Troycaine was contaminated with Gram-positive cocci, while Synim and Methdilazine were found to contain Gram-positive rods. The study further extended to fungal contamination in pharmaceuticals, including Troycaine, Methdilazine, Vericose Vein, Ambroxl Kufril, Montair, Dextromethorphan, and Mefenamic Acid + Paracetamol. Troycaine tested positive for fungal contamination, with Rhizopus stolonifer and Aspergillus niger being identified as contaminants. These fungal species are known for their potential to cause serious infections, particularly in immunocompromised individuals. The presence of microbial contamination in pharmaceuticals not only compromises the therapeutic efficacy of the drugs but also presents a significant public health threat, increasing the risk of drug-resistant infections, allergic reactions, and other complications. These findings emphasize the critical need for stringent microbial quality control in pharmaceutical manufacturing, storage, and distribution to mitigate these risks and ensure patient safety.

Hybrid dynamic optimal tracking control of hydraulic cylinder speed in injection molding industry process

<p style='text-indent:20px;'>Injection speed control is one of the most essential components in the injection molding process. It is critical to implement fast and reliable injection speed optimization control for the effective manufacturing of injection molding products. In this paper, the speed tracking control problem of the hydraulic cylinder of an injection molding machine driven by a typical servo motor is studied. An efficient two-stage optimization framework that leverages the ideas of both control parameterization (CP) and particle swarm optimization (PSO) is proposed for generating the optimal signal input to achieve the required injection speed tracking over a certain time. To this end, the dynamic model of the hydraulic system in the injection molding equipment is firstly established and the optimal controller design problem is transformed into sequential optimal parameter decision problems, and the explicit expressions of the gradient information of the objective function as well as the constraint on the parameters of the decision variables are derived. Then, the PSO combined with the CP and gradient-based algorithm is utilized to to solve the parameters of the controller efficiently. The two-stage optimization framework proposed in this paper can improve the convergence speed of the CP method and the precision of the PSO and easy-to-implement in engineering and industrial deployment. Finally, the feasibility and effectiveness of the proposed design method are verified by experimental simulations.</p>

IWAAM: An automated system for monitoring and control of wire-arc additive manufacturing

In this work, a wire-arc additive manufacturing (WAAM) automated system named iWAAM is presented. iWAAM is an automated system for monitoring and control of WAAM depositions. The communication framework is based on ROS (Robot Operating System) and kuka_experimental package which allow the execution of predefined trajectories (ros_control) or online trajectory correction during the deposition. The power source control and configuration, and the deposition sequence are also embedded in the proposed framework. A Graphical User Interface (GUI), based on Qt, is used to monitor process variables, such as arc current, voltage, wire feed speed and travel speed. Furthermore, iWAAM controls the fabrication process of parts designed by external planners or by simple depositions using primitive trajectories (raster, zigzag, circular). In addition, a web interface is presented, allowing the users to monitor the process remotely. Experimental results of actual WAAM depositions illustrate the functionalities of the proposed automated system.