Manufacturing Stage Research Articles

Analysing Impurities and Degradation Products

In the realm of pharmaceutical analysis, the analysis of impurities and degradation products takes centre stage, and its significance cannot be overstated. These undesired substances can profoundly impact the quality, safety and efficacy of pharmaceutical products, necessitating rigorous analytical methods and processes at every stage of drug development and manufacturing. Forced degradation studies are instrumental in identifying and characterizing impurities that may arise within a product, a pivotal source of information for quality control and regulatory compliance. Stability testing is integral to the batch release process, ensuring each product batch meets established stability criteria before entering the market. Stability testing and degradation studies are indispensable constituents of pharmaceutical analysis. They substantially contribute to preserving the quality, safety, and efficacy of pharmaceutical products. Beyond their regulatory mandates, these studies serve as proactive instruments for comprehending and supervising product stability across their life cycles. The insights gleaned from these endeavours inform critical judgments during drug development and manufacturing, ultimately assuring the welfare of patients and compliance with stringent regulatory requisites.

Production quality prediction of multistage manufacturing systems using multi-task joint deep learning

A multistage manufacturing system with multiple manufacturing stages is the key and main production mode for enterprises to achieve lean production. Due to the variation propagation between stages and multiple related quality prediction tasks, it is difficult to accurately predict the quality of multistage manufacturing systems with multiple tasks. Traditional single stage and single task quality prediction methods permit the multi stages and multiple tasks separately, which ignore multi-stage effects or the quality-related relationship between multiple quality output indicators and reduce the efficiency of quality prediction. In this paper, a production quality prediction framework based on multi-task joint deep learning is proposed to simultaneously evaluate the multi-task quality of all stages in a multistage manufacturing system. To be specific, variation propagation cumulative impact between multiple manufacturing stages is innovatively expressed by designing a multi-scale convolutional neural network with control gates (MCNN-CG) to extract and propagate data features. Production quality with multi-tasks at all stages is jointly predicted by designing a multi-layer multi-gate mixture-of-experts multi-task (ML-MMoE) model with reducing multi-task predictive loss simultaneously. The soft parameter-sharing strategy and multi-gate attention strategy are separately designed to ensure information sharing while learning personalized features of tasks to improve quality prediction accuracy of each task. In addition, a loss function based on homoscedastic uncertainty and regularization is designed to automatically learn the weight between multi-stage and multi-task losses. Experiments on multistage assembly test data of an inertial navigation manufacturing system show that the proposed method performs better than traditional models. Compared to the single-stage model, the proposed multistage model has an average improvement of 8.5%, 20.0% and 23.3% in R2, MAE and RMSE respectively in the second stage. Compared with the traditional multi-stage model, the proposed model has an average improvement of 1.7%, 6.2% and 9.8% in R2, MAE and RMSE respectively in the second stage.

Automatic Fruits Freshness Classification Using CNN and Transfer Learning

Fruit Freshness categorization is crucial in the agriculture industry. A system, which precisely assess the fruits’ freshness, is required to save labor costs related to tossing out rotten fruits during the manufacturing stage. A subset of modern machine learning techniques, which are known as Deep Convolution Neural Networks (DCNN), have been used to classify images with success. There have recently been many changed CNN designs that gradually added more layers to achieve better classification accuracy. This study proposes an efficient and accurate fruit freshness classification method. The proposed method has several interconnected steps. After the fruits data is gathered, data is preprocessed using color uniforming, image resizing, augmentation, and image labelling. Later, the AlexNet model is loaded in which we use eight layers, including five convolutional layers and three fully connected layers. Meanwhile, the transfer learning and fine tuning of the CNN is performed. In the final stage, the softmax classifier is used for final classification. Detailed simulations are performed on three publicly available datasets. Our proposed model achieved highly favorable results on all three datasets in which 98.2%, 99.8%, and 99.3%, accuracy is achieved on aforesaid datasets, respectively. In addition, our developed method is also computationally efficient and consumes 8 ms on average to yield the final classification result.

Application and validation of machine vision inspection for efficient in-process monitoring of complex biomechanical device manufacturing

A technique is presented for shifting the manufacturing quality control of complex biomechanical catheters away from destructive testing of finished parts. This technique uses a more efficient real-time in-process monitoring through the application of machine vision inspection of patient critical quality parameters. The approach acknowledges the challenge of this industry operating in a strict regulated environment. The higher standards of built-in quality are achieved by developing automated inspection solutions that are more accurate and repeatable. Machine vision system and associated inspection job tools are developed and used to detect defects at crucial stages of manufacturing. The vision system is then tested for its robustness using a statistical approach to ensure its measurement capability is within the allowable process range and tolerances. The integrated solution developed is proven to be robust and highly precise in maintaining the manufacturing process stable. It enabled the manufacturing process to move away from a destructive double sampling plan with a standard LTPD of 5% to an otherwise real-time 100% non-destructive verification of units. This technique provides an alternative to otherwise cost-inefficient quality control inspections utilized in regulated manufacturing environment. It gives confidence to these conservative industries to move towards adopting digital manufacturing and Industry 4.0 practices.

On the residual stress relaxation in Inconel 718 superalloys at high temperature by real-time neutron diffraction

Residual stresses in nickel-based superalloy engineering structure develop during various manufacturing stages, which can result in component distortion or reduction of performance reliability during high temperature service. Experimental quantification of residual stress built-up and its relaxation at high temperatures provides the time-dependent evolution and model validation for residual stress predictions. Via in situ time-of-flight neutron diffraction, a real-time study of residual stress relaxation is carried out on Inconel 718 (IN 718) blocks with different initial residual states after oil or water quenching and annealing processes. The residual stresses are largely relieved after 14 ∼ 20 h at 718 °C, and multi-stage kinetics of relaxation are observed. The staged feature is correlated to the competing stress relaxation mechanisms in the atomic scale that are clued from the evolution of neutron diffraction data. Although with large initial discrepancy in samples due to different thermal treatments, the final residual stresses tend to be within small variations after the relaxation.

Automated Testing for Early Identification of PD in the Stator Insulation of Low Voltage VFD Motors

Electrical stresses in industrial variable frequency drive (VFD) motors are increasing with the higher voltage and dv/dt levels, and with the advent of wide bandgap power devices. This increases the likelihood of partial discharge (PD) in VFD motors, and is expected to increase the risk of stator insulation failures in low voltage (LV) motors for which the insulation is not resistant to PD. To ensure that PD does not occur during operation, LV VFD motors are qualified for PD-free operation in the design or manufacturing stages. However, the PD inception voltage of qualified LV motors decreases with insulation aging exposing them to the risk of PD-induced insulation failure. In this paper, an automated off-line test method for VFD-embedded PD testing is proposed. The main idea is to perform PD testing whenever the motor is stopped at a voltage higher than the operating voltage to identify PD activity in the insulation before it occurs during operation. A series impulse and common mode voltage tests are proposed for stressing the different components of insulation for early identification of PD in terminal-/neutral-end ground, phase, and turn insulation. Testing on a LV, VFD motor verifies that PD can be identified whenever the motor is stopped to provide early warning of insulation failure.

Design and Optimization of Wheatstone Bridge Adjustment Circuit for Resistive Sensors

A novel Wheatstone bridge adjustment circuit with both rough-tuning and fine-tuning functions is designed for balancing Wheatstone bridge in this paper. Firstly, the parametric circuit structure is constructed to facilitate the design of rough-tuning and fine-tuning sub-circuit parameters; Secondly, the quantitative index of Wheatstone bridge imbalance is defined, and the parameter design flow of the rough-tuning sub-circuit, which consists of two sets of series-parallel-resistor (SPR) structures that are respectively connected in parallel with the two branches of one half-bridge, is given to directly weaken the initial bridge imbalance in the manufacturing stage. Theoretical analysis results show that the SPR structure can effectively approach any expected value and reduce the number of fixed resistor types. Thirdly, parameters of the fine-tuning sub-circuit, which consists of a resistor and a digital-to-analog converter (DAC), are optimized based on any expected adjustable range. By adjusting the DAC input to seek the middle value of an analog-to-digital converter output, indirectly eliminate the additional bridge imbalance caused by mechanical assembly stress, gravity, ambient temperature, and etc. in the application stage. Then the influence of the fine-tuning parameters on linear fitting coefficients of the output vs. input of the Wheatstone bridge is analyzed theoretically. The results show that the DAC output voltage only has a significant linear impact on the intercept coefficient, while its impact on the scale coefficient is negligible. Finally, the effectiveness of the adjustment circuit is verified on a six-axis force/torque sensor that is developed for an Experimental Module Manipulator in the Chinese Space Station.

IMPLEMENTATION PECULIARITIES OF METHOD FOR LITHIUM BATTERIES TECHNICAL STATE MONITORING BASED ON ANALYSIS OF RELAXATION PROCESSES CAUSED BY LOAD VARIATIONS

The paper describes a technique for estimating the parameters of the second-order electrical model of lithium battery (LB), based on the analysis of its response to a step-like load change. The advantage of this approach is the implementation with simple and compact measuring equipment. Taking into account the limitations for the maximum LB load, the solution of a system of nonlinear equations when estimating the model parameters can be reduced to solving a system of linear algebraic equations. This finding makes it possible to implement the approach with inexpensive general-purpose microcontrollers. Thus, the paper proposes a method for reducing computational costs, which consists in sequential fitting of experimental relaxation curves with two single-exponential models instead of using a complex two-exponential model. It provides more than twofold reduction in the time for identifying the parameters of the LB’s electrical model. The experimental studies show that the obtained dependences of the equivalent circuit parameters can be explained by the general properties of physicochemical reactions occurring in LB. From a practical point of view, the proposed method has great advantages. First, it has better time localization compared to electrochemical impedance spectrometry. This advantage is especially important for LB due to the effect of the discharge processes on the results. In addition, the response time of diagnostic systems is significantly reduced. Secondly, the proposed method requires simpler and more inexpensive test equipment, which potentially makes it possible to integrate controls into the LB at the manufacturing and exploitation stages.

An Overview of Carbon Emission Mitigation in the Food Industry: Efforts, Challenges, and Opportunities

The food system plays a significant role in anthropogenic greenhouse gas (GHG) emissions, contributing to over one-third of these emissions. However, there has been limited attention given in the literature on how the food industry can effectively address the carbon issue. This review aims to bridge this research gap through providing a comprehensive overview of anthropogenic GHG emissions and exploring the role of carbon markets in mitigating climate change, with a specific emphasis on the food industry. It delves into the introduction of emission hotspots within the food industry, examines ongoing efforts in GHG emissions mitigation, and addresses the challenges associated with GHG verification and offsetting. Notably, emission hotspots are primarily found in the farm, manufacturing, and post-production stages of the food industry. The emissions from the farm stage, which are often overlooked, make a significant contribution to overall emissions. Carbon verification encounters limitations due to a lack of standardized methodologies, inaccurate data, and insufficient reporting of emissions. Currently, achieving carbon neutrality without relying on carbon offsets presents a significant challenge for the entire food industry. Comprehensive mitigation strategies and collaboration across agricultural producers and the food manufacturing industry are considered potential solutions to achieve genuine sustainability.

Investigation of mechanical properties on agave plant fiber composite by experimental and numerical methods

Natural resources have a crucial role in the production of eco-friendly products, especially in the context of environmental concerns. Polymer composites with synthetic fibers as reinforcements have adverse effects on the environment owing to their non-biodegradability. The decomposition rate of such synthetic fibers takes a long time. As a result, natural fibers derived from plants, animals, and minerals are the best substitute for synthetic fibers. The article mainly focuses on the numerical study of natural fiber composite using experimental data. This research paper describes the mechanical investigation of agave plant fiber composite prepared using agave plant fiber treated with different concentrations (via., 2%, 4%, 6%, 8%) of sodium hydroxide solution. Laminate was fabricated as per ASTM standards by hand layup method and the experimental testing (tensile and flexural tests) was performed. The experimental results were used as input data for numerical validation conducted using ANSYS 19.2 software. Deviations between the experimental results and numerical results were calculated and compared. The error percentage was found to be 3% to 8% only, which indicates that both studies merely yield the same values. This research study helps to predict the failure or stress analysis of a component made by any natural fiber-reinforced composites before the manufacturing stage of a real product or part.

Design of Wind Power Generator for Tambak Houses

Wind Power Generation (WPG) requires specific wind conditions to generate electrical energy. Indonesia's wind potential enables the development of small-scale power plants. Innovations in windmill technology need to be developed to ensure maximum results in low wind speed conditions. This research proposes the design and implementation of WPG using a vertical axis to provide lighting for pond houses. The goal is to benefit pond workers in coastal areas that lack electricity from the National Electric Company. The manufacturing stages include design and testing. Based on the design results, the dimensions of the propeller area are 0.393m, the frame height is 1.5m, and the wind turbine height is 0.75m. The performance test of the WPG yielded the highest turbine power value at 15.30 WITA, with a turbine power output of 25.38 Watts.

Back-End development on Laboratory Information System in Universitas Riau

Laboratories usually have different tools, materials, documents, and a lot of other content. At the University of Riau, especially the Faculty of Engineering, it is filled with many laboratories. Starting with a computer network laboratory and chemical laboratory, machine laboratory, and many more. Currently information about laboratories cannot be found on the internet, and it is still difficult to access information about laboratories. This research focuses on creating a back-end system that can later be implemented in the development of a laboratory information system. This development process uses the V-Shaped model as a reference in the manufacturing stages. The system that has been made will be tested using the unit testing, integration testing, and system testing methods with ISO 25010 as a reference standard in determining the quality of the tests carried out. The results of testing the system obtained very good results with A results on reliability, maintainability, and security testing. In testing the efficiency of the system in getting a response time 80ms average on each page. White box testing also obtained results that all the features and data in the system were functioning and matched as they should.

Long-period gratings for monitoring the resin transfer molding of fiber-reinforced polymer composites.

The spectral characteristics of long-period gratings (LPGs) have been researched over the last two decades, and many sensing applications of LPGs have been proposed due to their spectral sensitivity to many surrounding environmental parameters such as the temperature, pressure, and refractive index. However, this sensitivity to many parameters can also be a curse due to cross-sensitivity and the inability to distinguish which environmental parameter is responsible for the LPG's spectral behavior. For the application proposed here-monitoring the progress of a resin flow front, its velocity, and the permeability of the reinforcement mats during the infusion stage of resin transfer molding-the multi-sensitivity of LPGs is a distinct advantage, as it provides the ability to monitor the mold environment at various stages of manufacturing.

Prototyping an Online Patient Registration Based on a Smartphone App at the Malang Primary Health Care

Currently, the patient registration system at the Primary Health Care (PHC) in Malang City still uses a manual registration system with various existing problems, like the emergence of queues and patients jostling in the waiting room, so it takes longer for health services. This study aimed to design a prototype application for online patient registration at the Malang City Health Center. The method used is Research and Development Prototyping. The manufacturing stages start from (1) the identification of basic needs, (2) developing a working prototype, (3) using a prototype (trial), and (4) revising and improving the prototype. The instrument used in this study was an interview guide conducted with two Heads of PHC (Dinoyo and Rampal Celaket) and nine Registration Officers at two Health Centers to determine the need for designing a prototype online registration application. Observations were made regarding the existing IT systems (Hardware and Software) in both PHC, the facilities and infrastructure that support IT systems (rooms, internet networks, etc.) and the documents supporting the processes. The results of this prototype design were in the form of a list of functional and non-functional requirements, business process flow diagrams, data flow diagrams, Entity Relationship Diagrams, and Interface Design, including programming language and user interface. Based on the results of the online patient registration prototype design, it enters the initial stage of using a system design that is by user needs but has yet to reach the implementation stage. However, this prototype can be used as a reference in developing an integrated online registration system with existing information systems at the PHC.
 Keywords: Prototype, Online Registration, Smartphone, Primary Health Care, Patient

Fabrication of a bamboo-based glulam based on reconstitution unit innovation: Mechanical property investigation and carbon footprint evaluation

The development of high-quality, large format bamboo structural materials is a hot spot. Here, we fabricated a flattened bamboo board (FB) with a large size, which was further laminated and lengthened to prepare FB-based glulam. Two kinds of FBs were fabricated based on different flattening methods: notched-FB and smooth-FB. Compared with the notched-FBs, the modulus of rupture (MOR) and modulus of elastic (MOE) values of smooth-FBs which were previously softened at 175 °C increased by 9.2% and 7.7%, respectively. The FB-based laminated boards whose middle bonding layer is yellow surface to yellow surface show the best mechanical properties among all the three candidates, with dry shear strength, compressive strength parallel to grain, tensile strength parallel to grain, MOR and MOE values of 20.7 MPa, 52.5 MPa, 115.6 MPa, 119.6 MPa and 14.2 GPa, respectively. Finally, two lengthening methods of horizontal and vertical finger connections were introduced to enlarge the size. The results indicate that the FB-based glulam with extension interfaces near to the two terminal points of each laminated boards exhibits better bending resistance with a MOR value as large as 95.9 MPa, being attributed to the corresponding distributed stress and extended the stress transmission distance. The FB-based glulam is proved to be a carbon-neutral product with a carbon footprint value of − 1.12 kg CO2/t. This work is the first time to use FBs as reconstituted units for bamboo glulam. We hope to discuss the effects of changes in process parameters and methods at different manufacturing stages on the physical and mechanical properties of the material, thus providing an experimental and theoretical basis for the application of FBs in the field of large-scale bamboo-based structural materials and also broadening the application field of bamboo with high added value.

Microwave Spectroscopy Investigation of Carasau Bread Doughs: Effects of Composition up to 8.5 GHz.

Carasau bread is a flat bread, typical of Sardinia (Italy). The market of this food product has a large growth potential, and its industry is experiencing a revolution, characterized by digitalization and automation. To monitor the quality of this food product at different manufacturing stages, microwave sensors and devices could be a cost-effective solution. In this framework, knowledge of the microwave response of Carasau dough is required. Thus far, the analysis of the microwave response of Carasau doughs through dielectric spectroscopy has been limited to the dynamics of fermentation. In this work, we aim to perform complex dielectric permittivity measurements up to 8.5 GHz, investigating and modeling the role of water amount, salt and yeast concentrations on the spectra of this food product. A third-order Cole-Cole model was used to interpret the microwave response of the different samples, resulting in a maximum error of 1.58% and 1.60% for the real and imaginary parts of permittivity, respectively. Thermogravimetric analysis was also performed to support the microwave spectroscopy investigation. We found that dielectric properties of Carasau bread doughs strongly depend on the water content. The analysis highlighted that an increase in water quantity tends to increase the bounded water fraction at the expense of the free water fraction. In particular, the free water amount in the dough is not related to the broadening parameter γ2 of the second pole, whereas the bound water weight fraction is more evident in the γ2 and σdc parameters. An increase in electrical conductivity was observed for increasing water content. The microwave spectrum of the real part of the complex permittivity is slightly affected by composition, while large variation in the imaginary part of the complex dielectric permittivity can be identified, especially for frequencies below 4 GHz. The methodology and data proposed and reported in this work can be used to design a microwave sensor for retrieving the composition of Carasau bread doughs through their dielectric signature.

PELATIHAN PEMANFAATAN TEKNOLOGI TEPAT GUNA ALAT DESTILASI BAGI KELOMPOK TANI TANAMAN NILAM DESA PASENAN KECAMATAN STL ULU TERAWAS KABUPATEN MUSI RAWAS

This program aims to help the people of Pasenan Village to be able to make a simple distillation device, which is used by residents to convert patchouli plants into essential oils. Most of the residents of Pasenan have gardens planted with patchouli plants, but local residents have not done the conversion of patchouli plants into essential oil. The limited knowledge of the community about the patchouli distillation process is one of the obstacles faced by the community. Patchouli plants are only dried and sold directly to collectors. The condition of the people of Pasenan Village, STL Ulu Terawas Subdistrict, most of whom do not know the selling value of patchouli if it is processed into essential oil, so it is necessary to update information on science and technology, namely by holding socialization and training on the use of patchouli distillation tools into essential oils. The implementation stages in this PKM are the preparation stage, the training/socialization stage, the design and manufacture stage of the distillation apparatus, the implementation stage, and the evaluation stage. The target in this training is patchouli farmers in Pasenan village. The instrument used in this PKM is a knowledge and skills questionnaire. From the analysis of the results of the knowledge questionnaire, the average value of knowledge was 86, 7 in the "Very Good" category and skills of 82,3 with the "Very Good" category.

The influence of conching time on the sensory profile and consumer acceptance of milk chocolates enriched with freeze-dried blueberry (Vaccinium spp.).

Conching is a processing stage of industrial chocolate manufacture that is essential to the development of the sensory and rheological properties of the finished product. It promotes the physicochemical changes leading to flavor, aroma, and flowability refinement by continuously heating, aerating, shearing, and homogenizing chocolate mass during an extended time length. Conching duration is a key processing parameter that depends on the type of chocolate, the quality of primary ingredients, the conche's configuration, and the desired sensory outcome in the chocolate. Shorter cycles are often beneficial to manufacturers, due to increased productivity and reduced energy consumption, but they may be insufficient to fully develop chocolate's desired sensory properties. The present study aimed to shed light on the trade-off between product quality and process efficiency by assessing if varying conching durations were associated with statistically significant differences in the sensory profile and consumer acceptance of milk chocolates with freeze-dried blueberry. Samples were produced under an alternative method of conching prior to ball mill refining, with times investigated being 6, 12, 24, 36, 48, and 72 h, and were subsequently submitted to Quantitative Descriptive Analysis and consumer acceptance test. No statistically significant differences in either sensory profiles or consumer acceptance ratings of samples were observed, with the exception of hedonic values for aroma, indicating that a 6-h conching cycle was already enough to develop the sensory properties of the milk chocolate with freeze-dried blueberry. The feasibility of shorter conching times suggests a potential for energy saving and increased productivity in the production of milk chocolates following the conching prior to ball mill refining concept.

Islam, Christianity, and the Development of Machine Capitalism: The Weber Hypothesis Revisited

Abstract: Max Weber characterized the values constituted in ascetic Protestantism that resulted in an inner-worldly asceticism. Karl Marx elucidated the first stage of manufacture, a form of capitalism characterized by precapitalist production processes. When these values interpenetrated an economy at the first stage of manufacture, they generated the spirit of capitalism, which resulted in systematic and sustained capital accumulation. My reconceptualization of Protestant religious commitments clarifies how they led to the rationalization of the first stage of manufacture and thus resulted in systematic capital accumulation leading to machine capitalism. My characterization of religious commitment in (Sunni) Islam shows that while the economic preconditions for the development of machine capitalism, the first stage of manufacture, were sometimes present in Islamicate lands, Islamic religious commitments neither rationalized economic production nor created a tendency toward capital accumulation. In consequence, they did not result in machine capitalism.

Pengembangan Modul Elektronik Fisika Berbasis Saintifik menggunakan Software Sigil pada Materi Fluida Statis

This study aims to (1) explain the stages of scientific-based electronic module development using Sigil Software on Static Fluid Material with good criteria, and (2) explain the specifications of the electronic module being developed. This study uses the ADDIE development method which consists of three stages, analysis, design, and development. The data obtained is in the form of qualitative data supported by quantitative data sourced from questionnaires. The data sources consisted of 2 experts, 3 physics teachers, and students. The students consisted of 3 students in the one-to-one trial, 9 students in the small group trial, and 90 students in the field trial. The data analysis technique used is qualitative analysis and quantitative analysis. The conclusions from this study are: (1) The electronic module development stage includes: (a) the preparation stage by compiling the material and determining the application to be used, (b) the electronic module manufacturing stage using the main software, namely Sigil and other supporting applications, (c ) the completion stage is validating the electronic module to experts and revising according to suggestions and input from experts, (d) testing the electronic module to students and making revisions according to suggestions and input from students then publishing the file in the form of a Google Drive link. (2) The developed electronic module presents Static Fluid material. Each sub-material is complemented by student activities, learning video content, materials, sample questions and evaluations, and their discussion. There is also a final evaluation at the very end of the module which includes all learning indicators. The final result of this development research is to obtain a scientific-based electronic module using sigil software on static fluid material that meets the criteria very well and is suitable for use.