Batch Manufacturing Research Articles

Scheduling and Logistics Optimization for Batch Manufacturing Processes With Temperature Constraints and Alternative Thermal Devices

Scheduling and Logistics Optimization for Batch Manufacturing Processes With Temperature Constraints and Alternative Thermal Devices

Dynamic modeling and real-time performance analysis of multi-product batch manufacturing systems with perishable products

Production lines handling perishable goods in industries such as petrochemical and food processing demand meticulous precision in timing. These systems are governed by stringent timeframes, where products must strictly adhere to defined residence times. Exceeding these time constraints leads to product scrapping, posing a significant threat to overall productivity. Modeling such intricate systems presents a formidable challenge, and success hinges upon a deep understanding of the complex interplay between production and batch scrapping dynamics. In response to this challenge, this paper presents a novel model for a multiproduct batch production line with perishable products. Furthermore, the real-time performance metric of Permanent Production Loss (PPL) is extended to this system using a method of PPL back-adjustment in time. To validate the fidelity of the proposed mathematical model, numerical case studies are conducted, comparing the developed model to a discrete event simulation. The results demonstrate that the model accurately represents the system at hand. The expressions for PPL evaluation and attribution are also validated using case studies.

Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects

Acoustic metamaterials are a subject of increasing study and utility. Through designed combinations of geometries with material properties, acoustic metamaterials can be built to arbitrarily manipulate acoustic waves for various applications. Despite the theoretical advances in this field, however, acoustic metamaterials have seen limited penetration into industry and commercial use. This is largely due to the difficulty of manufacturing the intricate geometries that are integral to their function and the sensitivity of metamaterial designs to material batch variability and manufacturing defects. Capturing the effects of stochastic material properties and geometric defects requires empirical testing of manufactured samples, but this can quickly become prohibitively expensive with higher precision requirements or with an increasing number of input variables. This paper demonstrates how uncertainty quantification techniques, and more specifically the use of polynomial chaos expansions and spectral projections, can be used to greatly reduce sampling needs for characterizing acoustic metamaterial dispersion curves. With a novel method of encoding geometric defects in a 1D, interpretable, resolution-independent way, our uncertainty quantification approach allows for both stochastic material properties and geometric defects to be considered simultaneously. Two to three orders of magnitude sampling reductions down to ∼100 and ∼101 were achieved in 1D and 7D input space scenarios, respectively. Remarkably, this reduction in sampling was possible while preserving accurate output probability distributions of the metamaterial performance characteristics (bandgap size and location).

A novel UHMWPE composite with low friction coefficient for long-term ice sliding

Low friction ice sliding interfaces were critical for ski performance optimization. Traditional fluorinated ski waxes have attracted considerable attention for enhancing the hydrophobicity, anti-wearing, and oxidation resistance of ski-ice base. However, the toxicity and complexity of the waxing process limited batch manufacturing of low-cost and non-toxic ski-ice base, what is more, the wax covering on the base wore and failed during skiing due to the friction between ski and ice. Herein, we demonstrated a novel ultra-high molecular weight polyethylene (UHMWPE) composite that could maintain a low coefficient of friction (COF) with about 0.026 for at least 160 min when skiing on the ice. Microcapsule (MS) could release liquid (liquid paraffin (LP)). The released LP further enhanced the hydrophobicity of UHMWPE’s surfaces when friction occurred, which would maintain the stability and durability of the water film, and achieved superior and long-lasting friction resistance. Compared with other microcapsules with lower hydrophobic core, microcapsules with LP performed the best in reducing the friction of ski base from 0.126 to 0.024. Meanwhile, the COF of the surface kept at about 0.02 even after 12 rapid temperature changes. The presented UHMWPE composite of encapsulated liquids showed great potential and broad application owing to its simplicity and efficiency in winter sports.

High-Yield Production of High-κ/Metal Gate Nanopattern Array for 2D Devices via Oxidation-Assisted Etching Approach.

2D materials with atomically thin nature are promising to develop scaled transistors and enable the extreme miniaturization of electronic components. However, batch manufacturing of top-gate 2D transistors remains a challenge since gate dielectrics or gate electrodes transferred from 2D material easily peel away as gate pitch decreases to the nanometer scale during lift-off processes. In this study, an oxidation-assisted etching technique is developed for batch manufacturing of nanopatterned high-κ/metal gate (HKMG) stacks on 2D materials. This strategy produces nano-pitch self-oxidized Al2O3/Al patterns with a resolution of 150nm on 2D channel material, including graphene, MoS2, and WS2 without introducing any additional damage. Through a gate-first technology in which the Al2O3/Al gate stacks are used as a mask for the formation of source and drain, a short-channel HKMG MoS2 transistor with a nearly ideal subthreshold swing (SS) of 61mVdec-1, and HKMG graphene transistor with a cut-off frequency of 150GHz are achieved. Moreover, both graphene and MoS2 HKMG transistor arrays exhibit high uniformity. The study may bring the potential for the massive production of large-scale integrated circuits using 2D materials.

High-speed wafer surface defect detection with edge enhancement via optical spatial filtering in serial time-encoded imaging

With the rapid development of the chip and metasurface industries, high-speed defect detection of wafer during semiconductor batch manufacturing has become increasingly important for yield control. Here, we propose a high-speed, macro-scale wafer surface defect detection method with enhanced image edges, via optical spatial filtering in serial time-encoded imaging. By using blazed gratings to spatially project different wavelength components of pulsed light into a one-dimensional line, together with dispersive Fourier time stretching technology, a high-speed serial time-encoded imaging system based on a single pixel detector is constructed for testing the wafer surface defects, and optical spatial filtering is introduced to improve the imaging quality. Experiments show high-pass spatial filtering effectively restrains environmental interference and enhances image edge detection. Small target detection is achieved without a complex image algorithm. Our solution extends optical spatial filtering to serial time-encoded imaging, not only permitting wafer macro scale defect detection with edge enhancement, but also having potential significance for imaging lidar, imaging spectrometers, ghost imaging technology, and more.

Design and Characterization of a Continuous Melt Milling Process Tailoring Submicron Drug Particles

Solid crystalline suspensions (SCSs) containing submicron particles were introduced as a competitive solution to increase dissolution rates and the bioavailability of poorly water-soluble drugs. In an SCS, poorly water-soluble drug crystals are finely dispersed in a hydrophilic matrix. Lately, melt milling as an adapted wet milling process at elevated temperatures has been introduced as a suitable batch manufacturing process for such a formulation. In this work, the transfer from batch operation to a two-step continuous process is demonstrated to highlight the potential of this technology as an alternative to other dissolution-enhancing methods. In the first step, a powder mixture of a model drug (griseofulvin) and a carrier (xylitol) is fed to an extruder, where a uniform suspension is obtained. In the second step, the suspension is transferred to a custom-built annular gap mill, where comminution down to the submicron region takes place. The prototype’s design was based on batch grinding results and a narrow residence time distribution, intended to deliver large quantities of submicron particles in the SCS. The throughput of the mill was found to be limited by grinding media compression. By inclining the mill at an angle, the grinding media position was manipulated, such that compression was avoided. Different states of the grinding media in the grinding chamber were identified under surrogate conditions. This strategy allows the maintenance of an energy-optimized comminution without adaption of the associated process parameters, even at high throughputs. Using this new process, the production of an SCS with 80–90 % submicron particles in a single passthrough was demonstrated.

Measurement of stress characteristics in flexible multi-thin-film substrates using tomography common optical path interferometry

Flexible displays are lightweight, thin, flexible, and impact-resistant, making them a major trend in the display industry. However, their short lifespan is a significant challenge. Thus, improving process parameters and extending product life through advanced measurement technology is crucial. Therefore, this study proposes using tomography common optical path interferometry (TCOPI) to measure and analyze the tomography stress characteristics of multi-thin-film flexible substrates in the folding direction. For polyethylene terephthalate (PET) and polyimide (PI), three thicknesses of indium tin oxide (ITO) were coated on the PET, graphene/PET, and graphene/PI flexible film substrates, and an automatic sliding-folding test platform was used to fold each flexible film substrate. Moreover, this study used TCOPI to measure and analyze the change in residual stress and the sheet resistance of the samples before and after folding. Additionally, this study conducted inward and outward folding tests on graphene/PET/graphene and graphene/PI/graphene substrates to analyze tomographic stress and sheet resistance in the folding direction. After 11,000 folding tests, the graphene/PET/graphene sample exhibited smaller stress and sheet resistance change rates compared to the graphene/PI/graphene sample, as measured by TCOPI. Consequently, the graphene/PET/graphene sample demonstrated better resistance to folding stress in this batch manufacturing process. Specifically, for the graphene layer of the graphene/PET/graphene sample, the minimum absolute value of the stress change rate before and after folding reached 5%. At the same time, the minimum sheet resistance value change rate was 8%. Based on the tomography stress measurements, suggestions for fine-tuning process parameters are provided to improve the flexible film substrate’s folding endurance.

Preparation of brittle ITO microstructures using Laser-Induced forward transfer technology

The performance of transparent conductive microstructures plays a significant role in determining the device efficiency. The fabrication of ITO microstructures on the flexible optoelectronic devices remains challenging because of the high-temperature processing requirements and brittleness of the ceramic material. This paper highlights a three-dimensional microfabrication technique that combines sacrificial layer etching and laser-induced transfer. By studying the donor material thickness and the laser energy density, control of the sacrificial layer transfer thrust was achieved to yield an optimal microstructure performance. Different shapes of ITO transparent conductive microstructures were fabricated on polydimethylsiloxane (PDMS) surfaces, demonstrating structural integrity, visible light transmittances > 90 %, and resistivities of ≤ 8 × 10−4 Ω·cm. Finite element analysis was employed to simulate the impact transfer of the donor material onto the receiving substrate, thereby elucidating the energy-absorbing protective role of the flexible PDMS layer. Effective control of the transfer force was identified as a crucial factor in achieving the successful transfer of brittle films. This high-precision and rapid array processing approach meets the demands of automated batch manufacturing, indicating its potential for use in patterned processing on flexible substrates, as an alternative to lithographic techniques. This technique could be applied in the preparation of electronic skins and flexible devices. Additionally, for the first time, a 3 × 3 pixel resistive array sensor was integrated on a Ag nanowires/PDMS surface, demonstrating array pressure-sensing capabilities at pressures of 0–80 kPa. This study represents a significant step towards the development of multifunctional flexible optoelectronic devices.

Improved scheduling model for a multistage biopharmaceutical process in a multiproduct facility

This study critically evaluates deterministic and stochastic/evolutionary strategies for long-term scheduling of multiproduct facilities in batch and continuous biopharmaceutical manufacturing, as reported in existing literature using discrete-time and continuous-time models. It identifies key limitations in literature model/algorithm, including (i) real-time storage violation, (ii) real-time violation of shelf-life due to its calculation over a single event, (iii) minimum campaign length calculated over single events leading to suboptimal use of resources, and (iv) early product deliveries. To overcome these limitations, a deterministic mathematical model is proposed extending the existing unit-specific event-based model(s) with additional features including (i) modified material balances, (ii) new minimum campaign length constraints captured over multiple events, (iii) new shelf-life constraints captured over multiple events, (iv) new setup constraints based on product sequencing, (v) updated tightening constraints, (vi) updated sales and penalty constraints for late deliveries, (vii) updated bounds, and (viii) updated objective function. These improved features lead to better modeling in terms of handling intermediate and final product storage without real-time violations of storage and shelf-life, handling of initial setup in production tasks, and timely delivery of final products. The proposed improved model yields up to 36 % increase in profit when applied on four literature examples.

Potentials of Polyacrylonitrile Substitution by Lignin for Continuous Manufactured Lignin/Polyacrylonitrile-Blend-Based Carbon Fibers

While carbon fibers (CFs) are still the most attractive reinforcement material for lightweight structures, they are mostly manufactured using crude oil-based process chains. To achieve a higher eco-efficiency, the partial substitution of polyacrylonitrile (PAN) by renewable materials, such as lignin, is investigated. So far, this investigation has only been carried out for batch manufacturing studies, neglecting the transfer and validation to continuous CF manufacturing. Therefore, this work is the first to investigate the possibility of partial substituting lignin for PAN in a continuous process. Lignin/PAN-blended CFs with up to 15 wt.-% lignin were able to attain mechanical properties comparable to unmodified PAN-based carbon fibers, achieving tensile strengths of up to 2466 MPa and a Young’s Modulus of 200 Pa. In summary, this study provides the basis for continuous Lignin/PAN-blended CF manufacturing.

A Novel image processing technique for weighted particle size distribution assessment

The objective of the study was to create a reliable method that could be used to evaluate the particle size distribution of samples and pre-mixes in real-world situations, particularly those consisting of typical formulation blends. The goal was to use this method to assess the uniformity of the samples and ensure that they met the required quality standards. The researchers aimed to create a method that could be easily incorporated into the manufacturing process, providing a practical and efficient solution. This study demonstrates the use of ImageJ software to analyze the particle size distribution (PSD) of powders. The technique produces qualitative data from microscopy images and quantitative data from analysis of parameters including average diameter, D 10, D 50 , D 90, and standard deviation. The method was tested with various treatments, showing differentiating outcomes in all cases. The alternate technique provides a rapid and cost-effective method for PSD analysis, surpassing the limitations of sieve analysis. Extensive testing of the method, using a variety of sample types, including typical formulation blends, was performed. The results suggest that the method can effectively assess the morphology of changing materials during batch manufacturing and characterize uniformity in blends. The methodology has the capability to identify attributes related to PSD that are typically required to be monitored during manufacturing. The technique allows for accurate and reliable quantification of the attributes through image capture technology. The technique has future potential and has important implications for material science, powder rheology, pharmaceutical formulation development, and continual process monitoring.

Energy and exergo-environmental performance analysis of a Stirling micro-fridge with imperfect regenerator

In search of very small and ecological refrigeration machines, Stirling chillers are studied on a micro-scale. This article analyzes the performance of a Stirling microcooler using a new modeling approach. This micro-cooler consists of a pillar network as regenerator, a compression and expansion chamber suitable for batch manufacturing, Alpha configuration with helium as working fluid. The Schmidt model with imperfect regeneration is used with consideration of work losses due to gas spring hysteresis. The equations solved analytically using the laws of thermodynamics are used to evaluate the energy and exergy performance of the microcooler. The parameters like height and internal width of the regenerator, phase angle, temperature ratio, swept volume ratio, cooling pressure, dead volume ratio are studied. A numerical code is developed in Matlab. Results show that optimal parameters develop a cooling capacity of 18.99 mW at a phase angle of 45°, a coefficient of performance of 1.104 at an internal height of the regenerator of 0.85 mm, an ecological coefficient of performance of 10.9 mW, an exergy yield of 6.13%, a destroyed exergy of 0.66 mW. The comparison between the present work and those in the literature shows that the current micro-cooler explores a COP improvement of 35%.

Surface reconstruction and thickness error calculation of optical components with a complex curved surface

The increasing demand for free-form irregular optical components in both military and civilian sectors has made the inspection of such unique shapes a central challenge that hinders their production and use. In particular, the shape and thickness errors of low- and medium-precision components thermally pressed from flat optical materials are greater than those of hard brittle optical components fabricated by subtractive manufacturing, and the resulting impact on human vision is more severe. Reasonable, convenient, efficient, and accurate 3D scanning and data processing for surface reconstruction that combines application scenarios and batch manufacturing needs are urgently needed. Based on the principles of optical ray tracing and triangulation processing, the sampling and calculation of optical path thickness proposed in this paper effectively establish a theoretical model for macroscopic distortion, providing a reasonable solution for distortion correction, batch manufacturing of free-form surface pressing formed components, and defect repair.

Fabrication and properties of SiC-based accident-tolerant fuel with precisely-regulated TRISO particles dispersion

The ceramic-based coated particle dispersed fuel (CDF) has arrested worldwide attention as a kind of promising accident-tolerant fuel since the Fukushima-Daiichi accident in 2011. To improve safety and in-pile performance, regularly-distributed CDF was formulated. A novel fabrication method was developed to accurately target TRistructural-ISOtropic (TRISO) particles to preset positions in the SiC matrix via a self-developed precise TRISO-controlled moulding equipment. After sintering, the samples were observed by SEM and X-μCT, which showed that the TRISO particles were uniformly and regularly arranged in the SiC matrix, and were almost intact with little extrusion and breakage. The density, thermal conductivity, and thermal shock performance of the prepared samples were examined and proved to be consistent with those of the pellets with randomly-distributed TRISO particles, which could satisfy the safety requirements. Small batch manufacturing was realized and production efficiency was enhanced. This new technology offers a promising pathway to produce high-reliability ceramic-based CDF with precisely-located TRISO particles, which promote the development of advanced accident-tolerant fuels.

1,2,3-Triazole Synthesis: Development of Safe and Effective Batch and Continuous Manufacturing Processes

1,2,3-Triazole Synthesis: Development of Safe and Effective Batch and Continuous Manufacturing Processes

Quality by Design Framework Applied to GMMA Purification

In recent years, Generalized Modules for Membrane Antigens (GMMA) have received increased attention as an innovative vaccine platform against bacterial pathogens, particularly attractive for low- and middle-income countries because of manufacturing simplicity. The assessment of critical quality attributes (CQAs), product-process interactions, identification of appropriate in process analytical methods, and process modeling is part of a robust quality by design (QbD) framework to support further development and control of manufacturing processes. QbD implementation in the context of the GMMA platform will ensure robust manufacturing of batches with desired characteristics, facilitating technical transfer to local manufacturers, regulatory approval, and commercialization of vaccines based on this technology. Here, we summarize the methodology suggested, applied to a first step of GMMA manufacturing process.Graphical

Epitaxial Growth of Large-Scale 2D CrTe2 Films on Amorphous Silicon Wafers With Low Thermal Budget.

2D van der Waals (vdW) magnets open landmark horizons in the development of innovative spintronic device architectures. However, their fabrication with large scale poses challenges due to high synthesis temperatures (>500 °C) and difficulties in integrating them with standard complementary metal-oxide semiconductor (CMOS) technology on amorphous substrates such as silicon oxide (SiO2) and silicon nitride (SiNx). Here, a seeded growth technique for crystallizing CrTe2 films on amorphous SiNx/Si and SiO2/Si substrates with a low thermal budget is presented. This fabrication process optimizes large-scale, granular atomic layers on amorphous substrates, yielding a substantial coercivity of 11.5 kilo-oersted, attributed to weak intergranular exchange coupling. Field-driven Néel-type stripe domain dynamics explain the amplified coercivity. Moreover, the granular CrTe2 devices on Si wafers display significantly enhanced magnetoresistance, more than doubling that of single-crystalline counterparts. Current-assisted magnetization switching, enabled by a substantial spin-orbit torque with a large spin Hall angle (85) and spin Hall conductivity (1.02 × 107 ℏ/2e Ω⁻¹ m⁻¹), is also demonstrated. These observations underscore the proficiency in manipulating crystallinity within integrated 2D magnetic films on Si wafers, paving the way for large-scale batch manufacturing of practical magnetoelectronic and spintronic devices, heralding a new era of technological innovation.

A Bayesian Approach for Lifetime Modeling and Prediction with Multi-Type Group-Shared Missing Covariates

In the field of reliability engineering, covariate information shared among product units within a specific group (e.g., a manufacturing batch, an operating region), such as operating conditions and design settings, exerts substantial influence on product lifetime prediction. The covariates shared within each group may be missing due to sensing limitations and data privacy issues. The missing covariates shared within the same group commonly encompass a variety of attribute types, such as discrete types, continuous types, or mixed types. Existing studies have mainly considered single-type missing covariates at the individual level, and they have failed to thoroughly investigate the influence of multi-type group-shared missing covariates. Ignoring the multi-type group-shared missing covariates may result in biased estimates and inaccurate predictions of product lifetime, subsequently leading to suboptimal maintenance decisions with increased costs. To account for the influence of the group-shared missing covariates with different structures, a new flexible lifetime model with multi-type group-shared latent heterogeneity is proposed. We further develop a Bayesian estimation algorithm with data augmentation that jointly quantifies the influence of both observed and multi-type group-shared missing covariates on lifetime prediction. A tripartite method is then developed to examine the existence, identify the correct type, and quantify the influence of group-shared missing covariates. To demonstrate the effectiveness of the proposed approach, a comprehensive simulation study is carried out. A real case study involving tensile testing of molding material units is conducted to validate the proposed approach and demonstrate its practical applicability.

Studies of Labware Contamination during Lipid Extraction in Mass Spectrometry-Based Lipidome Analysis.

In lipidomic analysis, plasticware is increasingly being used for lipid extraction and other sample processing procedures over glassware. However, a systematic investigation of the consequences of plasticware use on mass spectrometry (MS)-based lipidome analysis is lacking. In this work, we present an analytical approach for detecting and comparing solvent and labware contaminants encountered in lipidomic workflows. It is shown that the contaminant profiles varied widely between microcentrifuge tubes from different manufacturers. The most suitable polypropylene tubes tested introduced 847 labware-originating contaminant m/z's when three different manufacturing batches were tested for Folch lipid extractions. Of particular concern is that 21 primary amide and fatty acid surfactants were introduced that were identical to biological endogenous lipids, 16 of which had not been previously reported as leachables from polypropylene materials. Alternatively, the use of borosilicate glassware and PTFE-lined screw caps introduced 98 different contaminant m/z's across three manufacturing batches tested for Folch extractions. Despite the overwhelming number of labware contaminants introduced, current databases and literature only facilitated the identification of 32 contaminants. To address the dearth of publicly available contaminant information, we provide a comprehensive labware contamination repository containing high-resolution m/z values, adductation information, retention times, and MS/MS spectra. This resource should prove to be valuable for researchers in detecting and distinguishing contaminants from analytes of interest. A companion paper presents a detailed study of how labware contamination can lead to ion-suppression effects on coeluting lipids and interference in the analysis of endogenous lipids, such as those from human sera.