Control Of Process Parameters Research Articles

Development of the quality and safety control system in the technology of producing a protein-carbohydrate composite

The analysis of information sources of HACCP system used in the food industry for assessment of quality and microbiological safety of products is presented. The applicability of the principles of the HACCP system in the technology of producing a protein-carbohydrate composite as a feed product for cattle is analyzed. The research was conducted in 2018–2019 in Novosibirsk region. A brief description of the technology for producing a protein-carbohydrate composite in raw or dried form is given. The technology based on the HACCP principles comprised the control of raw materials, intermediate products, the final product and the operating modes of equipment that implement the technological process. The feed additive was obtained from wheat grains, cheese whey and wheat bran. The methods and results of the study of hazardous factors in individual operations of the technological process, actions to prevent their occurrence, and critical control points in the development of the technology are presented. A list of biological, physical and chemical potential hazards was compiled. Critical control points were established in the technological process. According to the HACCP plan, hazardous factors were monitored for each operation, indicating what corrective actions should be taken to maintain the limits of the controlled process parameters. The actions listed hereabove are aimed at developing a plan of measures to prevent potential hazards. The quality and safety control system developed on the principles of HACCP in the technology for producing a protein-carbohydrate composite enables one to control the quality and safety of the product during all stages of its production.

Study on taper reduction of high aspect ratio micro-shafts fabricated by twin-mirroring-wire tangential feed electrical discharge grinding (TMTF-WEDG)

• New method, named TMTF-WEDG, was proposed for manufacturing micro-shaft. • The main reasons for the taper of micro-shaft are the deformation of the micro-shaft and the wear of wire electrodes. • According to the experimental results, the parameters were selected to control the discharge energy to minimize the taper. • The feed strategy was improved to avoid the effect of wire electrode wear on taper. • High-precision micro-shaft with small diameter and large aspect ratio was successfully prepared. Efficiently fabricating large-aspect-ratio micro-shaft with small diameter and high accuracy is a significant technology in micro-manufacturing. In this paper, based on the newly proposed method, named twin-mirroring-wire tangential feed electrical discharge grinding (TMTF-WEDG), we developed the micro-shaft fabrication system to improve the efficiency by twin-mirroring-wire and accuracy by tangential feed. Besides, the narrow slit formed by twin-mirroring-wire constrains the diameter of micro-shaft, which allows improving the repeatability of micro-shaft diameter by controlling the tangential feed distance and narrow slit width. But during the TMTF-WEDG, we found that the micro-shafts with small diameter and large-aspect-ratio tend to have processing taper. The reasons for the tapered micro-shaft are the wire electrode wear due to non-running during finishing and the deformation of micro-shaft with low stiffness due to the small diameter and large aspect ratio. The heat generated by the discharge causes the deformation and its conduction inside the micro-shaft. Discharge energy needs to be controlled during the finishing of TMTF-WEDG, which was achieved by controlling processing parameters. By studying the effects of parameters on the processing taper, optimized parameters minimized the taper of the micro-shaft. The feed strategy was improved so that the micro-shaft always discharges with new wire electrodes. In this way, we successfully fabricated a tungsten micro-shaft with a diameter of 8.5 μm and a length of 400 μm, and the diameter variation is less than 2 μm. The aspect ratio of another micro-shaft with a diameter of 39.38 μm is larger than 50, with the diameter variation within ± 2 μm. By using such micro-shaft, we performed micro-holes processing by micro-EDM on a 304 stainless steel sheet, and the accuracy of 49 micro holes was controlled within 1 μm.

Experimental and numerical investigations of optimum process window for friction stir welding using flat faced tool pin

Background/Objectives: In friction stir welding, tools with flat faced pin delivers better weld quality than cylindrical pin. In flat faced pin, improper selection of process parameters often results premature tool failure. Being easily controllable process parameters, proper selection of tool rotation speed with respect to the tool advancing speed not only avoids unwanted weld defects but also enhances tool life. Methods: An integrated experimental and numerical comparative study is made between air and water cooled processes to understand the effects of heat dissipation through the boundaries on temperature distribution. Findings: Optimum range of Pseudo Heat Index (PHI) is achieved by comparing the obtained temperature distribution with material softening temperature. Optimum range of weld speed with respect to the tool rotation speed is derived through the optimum Pseudo heat index. Experimental study on the joint strength validates the proposed optimal process parameter ranges. Novelty : This study outlines a novel approach to develop an optimum process window based on PHI for air and water cooled friction stir welding using tools with flat faced pin. Keywords: Optimization; friction stir welding; thermomechanical; pseudo heat index; experimentation; numerical modeling

Multiresponse Parameter Optimization for the Composite Tape Winding Process Based on GRA and RSM

Composite tape winding is an important forming process of composite materials, which can ensure good performance of composite products. Selection and control of key process parameters in the winding process have a great influence on the properties of products, such as void content and residual stress of products. Through experimental analysis, the residual stress and void content of the composite products are not the minimum when the prepreg winding process is carried out by using the empirical process parameters. To solve this multiobjective optimization problem, experiments were conducted using the Box–Behnken design. The multiobjective optimization problem is converted to a single-objective problem using grey relational analysis (GRA). Principal component analysis (PCA) is used to quantify the relative contributions of residual stress and void content. Regression analysis of grey relational grade (GRG) based on the experimental data was used to develop a second-order GRG prediction model. The winding process parameters were optimized with response surface methodology (RSM), and the winding experiments were carried out with these parameters. The experimental results show that the best combination of process parameters yields the best GRG results with better void content and residual stress.

Instability Regions in Flexural-Torsional Vibrations of Plates

The paper is devoted to study of the parametric resonance of torsional vibrations caused by large-amplitude flexural vibrations of cantilevered plates. In this study we considered the first two resonant modes of flexural vibrations. The analytical study of the original problem which is reduced to Hill equation, is based on the WKB approximation. According to the obtained results, we built a map of instability gaps in the plane of the two process control parameters. The conclusions are made about the possibility of experimentally detection the studied effect in real systems.

Quality Factor of Forced Oscillations of a Linear Fractional Oscillator

Analytical formulas for the amplitude–frequency and phase–frequency characteristics, as well as forced oscillations, of a fractional oscillator have been derived using the harmonic balance method. It has been found that these characteristics depend on the dissipative properties of a medium—memory effects, which are described by fractional-order derivatives. It has been shown that fractional orders of derivatives influence the decay of the oscillatory process and are related to its Q factor. Analytical curves of forced oscillation characteristics for a linear fractional oscillator give the idea that fractional orders can be considered as control parameters for an oscillatory process in a dissipative medium.

A simple process optimization route to fabricate curved bionic compound eye array

In this paper, a complete and simple process optimization route for the curved bionic compound eye (BCE) array fabrication is presented based on digital micromirror device (DMD) maskless lithography. Firstly, based on the study of edge bulge effect in the thermal reflow process, a proper curved BCE structure is designed. Then, through the optimization of multilayer coating process it can obtain a better uniformity of different photoresist layer and accurate thickness. Next, combined the DMD maskless lithography technology with the Poor Man’s dissolution rate monitor (DRM) approach, well-preformed hierarchical cylindrical structure can be simply fabricated. Lastly, the curved BCE structure can be obtained precisely by choosing the reasonable process control parameters, which depended on the study of two-step thermal reflow processes. This process optimization route makes it very easy to realize the curved BCE array structures with different ommatidium shapes. Experimental results showed the effectiveness of our process optimization method. The presented method is expected to provide a fast, economic and simple strategy for curved BCE array fabrication.

Optimal control of earth pressure balance of shield tunneling machine based on dual‐heuristic dynamic programming

SummaryEarth pressure balance (EPB) shield tunneling machine has been widely used in underground construction. To avoid the catastrophic accidents caused by earth pressure imbalance, the earth pressure on excavation face must be controlled balance to that in chamber. To solve this problem better, a multi‐variable data‐driven optimal control method for shield machine based on dual‐heuristic programming (DHP) is proposed. The DHP controller is constructed with action network, model network, and critic network based on back‐propagation neural networks (BPNNs). Following Bellman's principle of optimality, a cost function of DHP controller for the chamber's earth pressure is presented, which simplifies a multi‐level optimization to a single‐level optimization. To minimize the cost function, the action network utilizes the critic network's error to achieve multi‐variable optimization, and the optimal control parameters for the tunneling process are obtained at last. The simulation results show that the method can effectively control the earth pressure balance. Even in case of disturbance, the system has strong anti‐interference ability and the control process is also quicker and steadier.

Melt pool morphology and surface roughness relationship for direct metal laser solidification of Hastelloy X

PurposeLimited research has attempted to reveal the different modes of the melt pool formation in additive manufacturing. This paper aims to study the mechanisms of surface roughness formation, especially on the aspect of melt pool formation which determine the surface profile and consequently significantly influence the surface roughness.Design/methodology/approachIn this study, the conditions under which different modes of melt pool formation (conduction mode and keyhole mode) occur for the case of as-fabricated Hastelloy X using direct metal laser solidification (DMLS) are derived and validated experimentally. Top surfaces of uni-directionally built samples under various processing conditions are cut, grinded, polished and etched to reveal their individual melt pool morphologies. Similarly, up-skin (slope angle < 90°) and down-skin (slope angle > 90°) melt pool morphologies are also investigated to compare the differences. Surface tension gradients and resultant Marangoni flow, which dominate the melt flow in the melt pool, is also calculated to help better evaluate the melt pool shape forming.FindingsTwo types of melt pool formation modes are dominating in DMLS: conduction mode and keyhole mode. Melt pool formed by conduction mode generally has an aspect ratio of 1:2 (depth vs width) and is in elliptical shape. Appropriate selection of scanning laser power and speed are required to maintain a low characteristic length and width ratio to prevent ballings. Melt pool formed by keyhole mode has an aspect ratio of 1:1 or less. High-energy contour promotes formation of key-hole-shaped melt pool which fills the gaps between layers and smoothens the up-skin surface roughness. Low-energy contour scan is necessary for down-skin surface to form small melt pool profiles and achieve low Ra.Originality/valueThis paper provides valuable insight into the origins of surface quality problem of DMLS, which is a very critical issue for upgrading the process for manufacturing real components. This paper helps promote the understanding of the attributes and capabilities of this rapidly evolving three-dimensional printing technology and allow appropriate control of processing parameters for successful fabrication of components with sound surface quality.

Machine Learning Approach to Predict Dielectric Permittivity of PE/TiO&lt;sub&gt;2&lt;/sub&gt; Nanocomposites

Controlling process parameters has significant influence in designing and developing nanocomposites materials with tailored dielectric properties. In the present study, polyethylene/TiO2 nanocomposites were fabricated using ball milling technique. The effects of TiO2 nanoparticles on the final dielectric properties of the nanocomposites in frequency domain were investigated. The dielectric spectroscopy measurements revealed that relative dielectric permittivity of the nanocompsoites was increased with TiO2 content. Besides, machine learning approach based on artificial neural networks (ANNs) algorithm was used to predict the dielectric permittivity of the nanocomposites materials. Modeling results showed clearly that the predicted data of the proposed artificial model are in good agreement with the experimental values. Moreover, the present study proved that ANNs can be used as successful tool to predict the dielectric properties of nanocomposites materials.

Experimental and empirical model analysis of microsurface texturing on 316 L press-fit joints fabricated by selective laser melting

In this study, selective laser melting (SLM) was investigated for the manufacturing of 316L stainless steel press-fit joints. The accuracy of selective laser melting technique in fabrication of texture profile in shape, pitch and height of microsurface texturing was examined. The resulting insertion and removal forces achieved from the produced textured pins for cold-formed high-end fixation applications were studied. The experimental results showed that the shape, pitch and height of the texture, as well as the resultant bonding strength of the joints, can be effectively set via control of the SLM processing parameters. While trapezoidal and triangular shapes of the texture lead to stronger bonding compared with oval-shaped texture profiles, the texture height was found to have a predominant effect on bond strength. To a much lower extent, larger pitch distances also resulted in higher bond strengths. A combination of abrasive and adhesive wear mechanisms was detected via examination of the inner surface of the hub into which the press fit was inserted. Along with a process map of design of the microsurface texture geometry of metal interference fit joints, this paper also presents the underlying mechanics for their bonding. The SLM process is shown to present a useful one-step method for the manufacturing of knurl metallic interference fit pins of customisable and definable texture and ensuing bond strength.

Precipitation printing towards diverse materials, mechanical tailoring and functional devices

Additive manufacturing allows for the fabrication of complex structures which are hard to achieve through conventional machining, extrusion, injection molding or blow molding processes. Current additive manufacturing methods for polymers, such as vat photopolymerization, powder bed fusion, material extrusion and binder jetting, still have limitations on the types of polymers that can be 3D printed. Recently, a novel solution-based polymer additive manufacturing method, termed precipitation printing, is developed which is based on the solubility of the polymer being printed in two mutually miscible solvents. In this work, the precipitation printing technique is further developed to expand the range of applicable materials, towards different thermoplastics (poly(vinylidene fluoride) (PVDF) and poly(methyl methacrylate) (PMMA)), thermoset rubber (acrylonitrile butadiene rubber (NBR)) and polymer nanocomposites (multiwalled carbon nanotubes (MWCNTs)-PVDF). The printing process is rapid and enables the realization of large structures with complex geometries as well as printing at a higher resolution than the material extrusion method, while also allowing the fabrication of micro-scale structures with greater than 100 μm resolution. Porosity and mechanical property tailoring of the precipitation printed materials are achievable through the control of process parameters, such as solvent/non-solvent pair selection, salinity of the non-solvent and printing temperature. In addition, the successful demonstrations of a directly 3D printed NBR check valve and a MWCNTs-PVDF strain gauge indicate the great potential for precipitation printing as a promising one-step process for the production of functional devices.

A Reliable Automated Sampling System for On-Line and Real-Time Monitoring of CHO Cultures

Timely monitoring and control of critical process parameters and product attributes are still the basic tasks in bioprocess development. The current trend of automation and digitization in bioprocess technology targets an improvement of these tasks by reducing human error and increasing through-put. The gaps in such automation procedures are still the sampling procedure, sample preparation, sample transfer to analyzers, and the alignment of process and sample data. In this study, an automated sampling system and the respective data management software were evaluated for system performance; applicability with HPLC for measurement of vitamins, product and amino acids; and applicability with a biochemical analyzer. The focus was especially directed towards the adaptation and assessment of an appropriate amino acid method, as these substances are critical in cell culture processes. Application of automated sampling in a CHO fed-batch revealed its potential with regard to data evaluation. The higher sampling frequency compared to manual sampling increases the generated information content, which allows easier interpretation of the metabolism, extraction of e.g., ks values, application of smoothing algorithms, and more accurate detection of process events. A comparison with sensor technology shows the advantages and disadvantages in terms of measurement errors and measurement frequency.

Self-adaptive learning for hybrid genetic algorithms

Local search can be introduced into genetic algorithms to create a hybrid, but any improvement in performance is dependent on the learning mechanism. In the Lamarckian model, a candidate solution is replaced by a fitter neighbour if one is found by local search. In the Baldwinian model, the original solution is retained but with an upgraded fitness if a fitter solution is found in the local search space. The effectiveness of using either model or a variable proportion of the two within a hybrid genetic algorithm is affected by the topology of the fitness function and the details of the hybrid algorithm. This paper investigates an intelligent adaptive approach to decide on the learning mechanism to be used by an individual over the course of the search. Evolution is used to self-adapt both the frequency of a steepest-descent local search and the relative proportions of Lamarckian and Baldwinian inheritance. Experiments have shown that this form of adaptive learning can improve the ability to find high-quality solutions and can accelerate the hybrid search without the need to find optimal control parameters for the learning process.

Fabrications of spherical alumina particles by controlling process parameters in a transferred arc plasma system

Aerosol processing is gaining much interest in fabricating particles for various applications due to its easy application and good control of particle characteristics. In this study, spherical alumina particles were prepared using a transferred arc plasma aerosol system with argon shield gas and nitrogen carrier gas. The operating conditions for spheroidization were controlled by comparing the particle heating and particle residence times in plasma to obtain the calculated critical particle size. Nitrogen fractions (10%–63%) and plasma powers (1–2.5 kW) were used as control parameters to verify the process design for the average injected particle sizes of 10 μm and 100 μm. The spherical particle sizes were examined by using field-emission scanning electron microscopy. Results showed that the particle size limits for melting(dP,LM) and vaporization (dP,LV) increased with increasing plasma power. Higher plasma power is required to fabricate spherical shapes from larger injected particles at nitrogen fractions of 10% and 63% because of the longer residence time needed to reach the melting state of the raw materials.

Spectra selection methods: A novel optimization way for treating dynamic spectra and in-line near infrared modeling

Near infrared (NIR) spectroscopy is now widely used in fluidized bed granulation. However, there are still some demerits that should be overcome in practice. Valid spectra selection during modeling process is now a hard nut to crack. In this study, a novel NIR sensor and a cosine distance method were introduced to solve this problem in order to make the fluidized process into “visualization”. A NIR sensor was fixed on the side of the expansion chamber to acquire the NIR spectra. Then valid spectra were selected based on a cosine distance method to reduce the influence of dynamic disturbances. Finally, spectral pretreatment and wavelength selection methods were investigated to establish partial least squares (PLS) models to monitor the moisture content. The results showed that the root mean square error of prediction (RMSEP) was 0.124% for moisture content model, which was much lower than that without valid spectra selection treatment. All results demonstrated that with the help of valid spectra selection treatment, NIR sensor could be used for real-time determination of critical quality attributes (CQAs) more accurately. It makes the manufacturing easier to understand than the process parameter control.

Prediction of control parameters corresponding to in-flight particles in atmospheric plasma spray employing convolutional neural networks

Optimization of control parameters for plasma spraying process is of great importance in thermal spray technology development. Engineers may limit themselves to local optimal solution by considering countable potential design solutions when selecting the plasma spray parameters in practice. This work proposes one decision support model by employing convolutional neural network (CNN) to explore the suitability of preliminary design. The approach aims to help engineers select global optimal solution with short time and low labor cost by invoking the models' capability of extracting potential features of in-flight particle characteristics. Simulation results make it possible to analyze new spraying process and train the designed model under the condition of insufficient experience and data. Firstly, the distributions of particle status obtained from simulation results act as the input and the control parameters are the output. Secondly, the projections between the in-flight particles and the control parameters are built implicitly and analyzed through CNN models. Thirdly, we validate the statistical information of particle state distributions through visualizing the feature maps and filters. Finally, the trained CNN models are verified by the fitted Gaussian distributions with basically consistent results. By building projections of in-flight particles and control parameters, new entrants and apprentices are capable of deducing the control parameters with the help of the pre-trained CNN model, thus cutting down the threshold for new practitioners.

Controlled fabrication of polyfluoroimide microspheres by electrospray technique

Bowl-like polymer microspheres (BPMs) of polyfluoroimide (PIF) with a single cave and interior porosity are successfully prepared in this work by using one-step electrospray (ES) technique. The effects of polymer solution and process control parameters on the surface appearance and sizes of resulting microspheres are investigated. The experimental results indicate that the cyclopentanone (CPT) is used as the solvent, polymer microspheres with porous structure, tailed and elongated, single-cave and beaded fibers can be prepared respectively. Compared to the cyclopentanone, the N, N-dimethylacetamide (DMAC) solvent contributes to the formation of microspheres with spherical and rough surface structure. The diameters of BPMs and single-cave can be regulated by varying the PIF solution concentration, applied voltage and flow rate during the electrospray process. The diameter ranges for the obtained PIF microspheres are 2.75-5.03 μm with single-cave at 1.11-2.72 μm respectively. The sizes of both the single-cave and microspheres tend to reduce with the decrease of flow rate or increase of applied voltage. These BPMs with interior porosity have a broad application prospect in microreactor, catalyst supports, drug carrier and captures for cells due to its large effective surface area and strong absorption capacity.

Direct Copper Patterning at High Deposition Rate By Using Environmentally Compatible Electroplating Process

Electroplating has been an important process to produce electronic devices, automotive parts, decorative materials and so on. In contrast to that, plating is endowed with environmental issues originated from exhaust fluids and acid mists. Therefore, it is limited to construct new production line in spite of necessity of plating. Moreover, it is difficult to improve productivity drastically due to completely established plating technology in 21th century. To break down demerits of conventional electroplating, we focus on the fundamental issue regarding with the plating process that can be performed in electrolyte bath. Recently, we have developed novel electroplating process named solid electrodeposition (SED), which is characterized by metal ion electrophoresis through solid electrolyte membrane1). This process has unique deposition behavior that the metal deposition on substrate proceeds only on contact area with the membrane, like a stamping process. The SED has a merit of reducing amount of exhaust fluids as well as direct patterned deposition reflecting the membrane shape. Therefore, we believe that SED is highly promising process to metallize the substrate instead of the conventional electroplating. In this study, we report on copper deposition mechanism and direct fine pattering process by applying SED.We evaluate the limitation of copper deposition rate under controlled process parameters. As a result of that, the maximum deposition rate reaches over 0.63A/dm2 (14μm/min), which should be relatively higher than conventional one. The impressive value is originated from metal transfer mechanism into membrane as well as the device configuration. The metal deposition proceeds on solid-solid interface between membrane and substrate so that no diffusion layer exist near the substrate2). Moreover, the distance between anode and cathode can be shorten because the membrane preserves electrolyte solution. The copper film deposited from electrolyte solution without additives exhibits relatively smooth and minute surface morphology. This may be because membrane contacted on substrate restricts abnormal Cu growth due to contact pressure.SED has a merit for direct patterned deposition reflecting membrane shape, but it is not easy to fabricate fine patterns without masking. Therefore, it is limited to apply high-end parts such as printed circuit boards and sensor devices. To overcome this problem, we have developed direct fine patterning process by combining SED with dry coating and etching technologies. Figure 1 shows schematic diagram and photographs of each step. Firstly, the metal thin layer is formed on substrate by means of sputtering (electrode layer). Secondary, silver nanoparticles are printed as fine circuit patterns and sintered at optimal temperature (seed layer). Thirdly, copper was selectively deposited on seed layer by means of SED, which utilizes the potential difference between electrode and seed layers. The SED proceeds through isotropic growth along vertical direction because the deposition occurs on the surface of seed layer contacted with the membrane. Therefore, SED can produce relative thick and fine patterns following line width of seed layers. Finally, the bear electrode layer is etched away by plasma exposure. We believe that this approach is highly promising process to fabricate circuit pattern in terms of cost (simple step) and environmental (no exhaust fluids) point of view. 1. H. Yanagimoto, R. Mori, K. Okamoto and J. Murai, F01-994, 236nd ECS Meeting.2. Y. Narui, Y. Hoshi, I. Shitanda, M. Itagaki, H. Yanagimoto, M. Hiraoka and H. Iisaka, E01-920, 232nd ECS Meeting. Figure 1

Cell manufacturing innovation facility: use of GMP-compliant space to accelerate advances in therapeutic cell production

Background & Aim Production space for cell therapy products is in high demand, with the recent FDA approvals of the first cell therapy products in the U.S. Hospitals are expanding their qualified production spaces to support the growing number of cell and gene therapy clinical trials. Simultaneously, a pronounced need to improve engineering and controlled manufacturing principles has been made clear. Initiatives have emerged to accelerate cell therapy manufacturing innovations at academic institutions, including the NSF Engineering Research Center for Cell Manufacturing Technologies (CMaT) and the Marcus Center for Therapeutic Cell Characterization and Manufacturing (MC3M). In order for researchers, particularly in engineering and manufacturing disciplines, to have an understanding of restrictions placed on therapeutic cell production, exposure to compliant environments without disrupting production is necessary. The MC3M facility at Georgia Tech provides the community access to facilities operating under GMP-compliant conditions and the ability to develop next generation technologies. Methods, Results & Conclusion The MC3M facility contains two isolated ISO 7/GMP suites for viral and viral-free work, and a large ISO 8 research lab. GMP rooms are adjacent to analytical suites, with pass-thrus to enable real-time analytics and feedback control. MC3M houses various bioreactors, including hollow fiber, vertical wheel, and stirred batch systems, as well as analytics equipment to enable at-line and in-line monitoring within minutes from sampling directly from culture vessels. Additionally, automation technologies that measure and control process parameters such as glucose and lactate are being developed and employed. Faculty, students, and industry can pilot new process technologies for cell manufacturing needs. Users learn proper gowning procedures and operational requirements like material quarantine and environmental monitoring. These experiences serve to better inform researchers in the practical applications of their early technology or culture process improvements, and advance the translation of discoveries to products. The facility is utilized for training purposes beyond the university's community to inform and equip the future workforce of the growing cell manufacturing industry. Facilities like MC3M are imperative to meet the demands of the cell manufacturing industry, and ensure clinically and industry relevant, impactful research is conducted, even at the earliest stages of discovery.