Product Manufacturing Process Research Articles

Effects of wood meal particle size and polyethylene glycol 400 content on glycol lignin production

Glycol lignin (GL) produced via acidic solvolysis of cedar wood meal with polyethylene glycol (PEG) is a highly functional material. In this study, the effects of wood meal particle size and amount of PEG added on the properties of PEG400-modified GLs (GL400s) were examined. For this purpose, cedar wood meal with four different particle sizes ranging between 0.18 and 2.00 mm and PEG400 at liquid ratios of 5 and 3 with respect to the wood meal were used. Acidic solvolysis at 140 °C successfully decreased the amount of solid residue with increasing GL400 yield and reaction time at both liquid ratios of 5 and 3. Overall, wood meal size remarkably affected the physical properties of GL400s at low PEG400 content (liquid ratio 3). In addition, the glass transition temperature Tg and thermal flow temperature Tf increased with decreasing wood meal size. Consequently, GL400s with varying thermal properties (Tg = 63 to 97 °C, Tf = 109 to 149 °C) were successfully prepared by adjusting the PEG400 liquid ratios and wood meal size. The data will support the development of a stable manufacturing process for the mass production of GL.

Stock of Nuts/Bolts System With A Load Cell Sensor of Digital Scale As An Iot-Based

The passage highlights the importance of having a reliable supply of nuts and bolts for Micro, Small, and Medium Enterprises (MSMEs) involved in the manufacturing of appropriate technology tools. Nuts and bolts are critical components in the production process of such manufacturing. Therefore, it is essential to ensure their constant availability to avoid interruptions in the workflow. Currently, many MSMEs still monitor their stock levels manually. This manual method has its drawbacks, as stock levels can sometimes go unnoticed, leading to stockouts when the components are needed. When stock runs out unexpectedly, it can cause delays, as additional time is required to purchase more supplies from wholesalers. In this study, a digital scale with a load cell sensor was developed as a medium for taking inventory or stocking bolts and nuts. This device features several buttons: a button for selecting the size of bolts or nuts, a button for choosing between stocking or taking items, and a button for displaying stock information of bolts or nuts in the warehouse. The results from this digital scale are sent to a website using the Internet of Things (IoT) system as a communication medium between the digital scale and the monitoring website. The results of this study show that the digital scale has an accuracy of 99.95%, and the accuracy of the counted items or stock is 100%.

Polymorphic crystallization and transformation pathways of 1,2-dipalmitoyl-3-oleoyl-rac-glycerol (PPO) during a liquid–solid-liquid journey

Abstract The polymorphic behavior of triacylglycerol (TAG) crystals formed during the manufacturing process of lipid-based food products relates directly to their textural and melting properties. In this work, we analyzed the polymorphic crystallization and transformation behavior of 1,2-dipalmitoyl-3-oleoyl-rac-glycerol (PPO), a widespread TAG in edible fats and oils, during the application dynamic thermal treatments of cooling and heating. By implementing calorimetric, X-ray diffraction, and microscopy techniques, we mapped the polymorphic occurrence and the polymorphic transformation pathways of PPO as a function of the rate of thermal treatments. The results obtained were later compared to that reported for diverse TAGs in previous studies. Despite the overall crystallization and transformation behavior of PPO following a similar trend to other TAGs close in fatty acid composition, we can highlight the much lower influence of varying cooling and heating conditions on the crystallization properties of this TAG. In more detail, crystalline forms of low stability were generally promoted during crystallization, whereas transformations occurred always through the melt independently of the heating conditions. One may expect this behavior to influence the industrial processing and final properties of food products based on edible fats containing PPO.

A sustainable waveguide-based design strategy for improving the energy efficiency of microwave hybrid heating systems: A combined theoretical and multi-physics simulation approach

The microwave hybrid heating (MHH) based processing has emerged as energy-efficient and productive manufacturing process. The efficiency of MHH depends upon the ability of waveguide system to transmit the electromagnetic radiation with minimal loss. Thus to improve the efficiency of MHH it is of paramount importance to understand the potential of waveguide systems. In the present work, the influence of different waveguide systems, their positioning, and different modes of operation on MHH efficiency were studied via theoretical and simulation investigations followed by experimental validation. Based on the study, the optimum waveguide system was identified as WR430. To assess the efficiency and effectiveness of the waveguide positioning on MHH, 12 different locations were considered, and the optimum location was identified as (+35, −35), with a maximum microwave utilization efficiency of 44.5 %. Subsequently, the simulation model (1049 °C) was validated using experimental data (1017 °C) with an error of less than 10 %. Also, MHH is sensitive to different waveguide operating modes, SiC susceptor positioning and microwave power. A microwave cavity operating with two waveguides on both sides is found to provide optimum results in terms of heating uniformity, electric field distribution, and microwave energy absorption. The SiC susceptor positioned at the centre of the alumina refractory yields maximum heat evolution of 1020 °C. In addition, as the microwave power grows, the temperature differential also increases, implying thermal heterogeneity inside the SiC susceptor. Thus, low microwave power is identified for improved thermal uniformity and energy efficiency, while high power is proven for rapid differential microwave heating.

Correlated multi‐response robust parameter design for different batches of products

AbstractIn the manufacturing process of products, it is common to produce in batches, and such complex products often have many interrelated processes and interdependent components. These lead to mutual correlations among multiple responses, correlations among response observations, and a complex relationship between inputs and responses. If aforementioned relationships cannot be addressed in the robust parameter design of batch products, it will influence the predictive precision of the model, subsequently impacting the reliability of the optimization results. To tackle the above three types of associations in products with batch effects, we propose a new approach, namely, the semiparametric mixed‐effects modeling approach for multi‐response correlation. Specifically, we begin by developing a multi‐response Bayesian semiparametric mixed‐effects model using spline, and then construct a multivariate loss function to obtain the optimal operating conditions, subsequently calculating the value of the entropy‐based weighted satisfaction function. The validity of the suggested method in modeling and optimization is verified through a simulation study and 3D printing example analysis.

Research on optimizing the propagation path search of individualized products with multi-source design changes

Abstract The individualization and diversification of customer requirements are gradually affecting the product design and manufacturing process, and the production mode of enterprises is evolving towards customer-oriented mass individualized customization. The change in customer requirements is inevitable in the process of individualized product design, which is the key factor leading to the change in product design. This paper establishes the standard of individualized product parts and components association relationship through correlation analysis, and constructs the individualized product parts and components association network model based on the complex network theory; on this basis, comprehensively considering the influence of parts nodes and association relationship in the complex network, it calculates the intensity of change propagation through the node importance degree and the probability of change propagation, and carries out the search for multi-source design change propagation paths through the improved ant colony algorithm, and evaluates the influence of the change of customer requirement by taking the change rate of the network as the evaluation index, to help enterprises to decide the request.

Enhancement of Additive Manufacturing Processes for Thin-Walled Part Production Using Gas Metal Arc Welding (GMAW) with Wavelet Transform

Additive manufacturing encompasses technologies that produce three-dimensional computer-aided design (CAD) models through a layer-by-layer production process. Compared to traditional manufacturing methods, additive manufacturing technologies offer significant advantages in producing intricate components with minimal energy consumption, reduced raw material waste, and shortened production timelines. AM methods based on shielded gas welding have recently piqued the interest of researchers due to their high efficiency and cost-effectiveness in manufacturing critical components. However, one of the most formidable challenges in additive manufacturing methods based on shielded gas welding lies in the irregularity of weld bead height at different points, compromising the precision of components produced using these techniques. In this current research, we aimed to achieve uniform weld heights along the welding path by considering the most influential parameters on weld bead geometry and conducting experimental tests. Input parameters of the process, including nozzle angle, welding speed, wire speed, and voltage, were considered. Simultaneously, image processing and wavelet transform were employed to assess the uniformity of weld bead height. These parameters were applied to produce intricate parts after identifying optimal parameters that yielded the smoothest weld lines. According to the results, the appropriate bead for manufacturing the part was extracted. The results show that the smoothest bead line is achieved in 27 V as the highest level of voltage, at a 90° nozzle position and the maximum wire feed rate. Parts manufactured using this method across different layers exhibited no distortions, and the repeatability of production substantiated the high reliability of this approach for component manufacturing.

Impact of surface tension, viscosity, pump settings, and nozzle size on filling process capability and accuracy in high-concentration biopharmaceuticals

Filling is the final critical unit operation in the manufacturing process of liquid biological drug products. This paper thoroughly investigates the influence and mechanisms of peristaltic pump settings, nozzle size, product surface tension and viscosity on the biopharmaceutical filling processes based on the established filling process model of surrogates. Our study highlights the significant role of pump settings in influencing filling process capability indexes, in addition to their primary function of regulating flow rate. Surface tension minimally impacts flow behavior but significantly regulates the final dropʼs behavior, with lower surface tension increasing dripping tendencies. Viscosity proves crucial; higher viscosity intensifies friction and head loss of filling flow in tube/nozzle, causing pressure and flow rate losses, more pronounced dripping, and worse filling accuracy. Furthermore, nozzle size moderates the impact of pump settings, surface tension, and viscosity on filling performance. Larger nozzles help mitigate these effects, contributing to enhanced stability in filling performance under challenging conditions. For high-concentration biopharmaceuticals with elevated viscosity during filling, utilizing larger nozzles and reducing pump speed could achieve enhanced Cpk values and improved filling accuracy. Understanding the complex interactions among these factors is vital for optimizing the biopharmaceutical industry, promoting cost-effective practices, and enhancing production efficiency.

Determination of Citrate Content of Commonly Transfused Blood Products

Abstract Background Citrate is a calcium-chelating anion used as an anticoagulant in the collection and manufacturing of blood products for transfusion. Overwhelming of normal hepatic catabolism of infused citrate, such as in liver failure or in massive transfusion, may cause citrate toxicity. Resultant hypocalcemia, impaired coagulation, and metabolic alkalosis results in increased patient mortality and morbidity. The citrate load per blood product unit is rarely known to the transfusionist, precluding precise calcium repletion. Manufacturing data of citrate content is available, but it is unreliable and often contradictory. The aim of this project is to directly measure the citrate concentrations of common blood products including packed red blood cells (pRBCs), plasma, and apheresis platelets. Methods Blood products (or samples thereof) were obtained, centrifuged, and assayed using a benchtop enzymatic citrate assay (Sigma-Aldrich). This technique generates a chromogenic product detectable via spectrophotometry at 570nm via conversion of citrate to a pyruvate intermediate. Blood products were serially diluted to the assay’s concentration measurement range based on estimations from the product manufacturing processes. Validation studies were performed to verify no significant interference from native pyruvate or from hemolysis at the dilutions used. All samples were run with a paired reference standard. Product type, storage duration, volume, and anticoagulant/preservative solution were recorded. Results Preliminary testing was performed on eleven pRBC units, twelve apheresis platelet units, and four whole blood(WB)-derived plasma. Measured citrate content of AS-1 and AS-5 units ranged from 43.56 - 114.5 mg while that of AS-3 units ranged from 327.23 – 816.82 mg, compared to manufacturing estimates of 188 mg and 883 mg, respectively. Measured citrate content of apheresis platelets ranged from 822-1533 mg compared to manufacturing estimates of 805 mg. Measured citrate content of WB-derived plasma also exceeded the manufacturing estimate of 1201 mg. Interference from pyruvate and hemolysis were insignificant at the dilutions used for testing. Validation of pRBC segment sampling is ongoing. Conclusion Varying guidelines exist for the correction of hypocalcemia during ongoing trauma resuscitation; however, guidance is limited regarding repletion by specific blood product. Our investigation affirms significant heterogeneity in pRBC citrate concentrations by collection method and identifies lower citrate concentrations than expected. This may be due to citrate metabolism by RBCs during storage. Platelet and FFP products contain significantly greater citrate masses by comparison, with a high degree of variation observed due to inherent product volume variability. Further sampling and testing are ongoing to establish reliable expected citrate loads for commonly transfused blood products.

The Concept of Building an Integrated Digital Ecosystem to Improve the Quality of Products and Services of Defense Industry Enterprises

Research and development of systems for managing material, technical, and intellectual resources are key directions for improving manufacturing processes in the modern world. In recent years, the question of integrating various management systems has become particularly relevant due to the widespread adoption of quality management systems and their certification to meet current regulatory requirements. This study attempts to merge the advantages of using product lifecycle information support technologies, such as data and information management, with the concept of digital twins, including virtual design, digital product modeling, and real-time analysis. The analysis covers the constituent elements of the generalized product design and manufacturing process, addressing the construction of an integrated digital ecosystem to enhance the quality of products and services in the defense-industrial complex. This ecosystem is based on the integration of technologies for continuous product information support using their digital twins and an integrated quality management system. It is shown that the approach to evaluating the effectiveness of purposeful processes should be complemented by a risk-oriented model, which includes response scenarios to potential adverse effects of the operation of the purposeful organizational-technical system. A structural scheme and formalized description of a generalized product information support model are presented, allowing for the integration of specific quality indicators into a unified strategic outcome. Ultimately, a concept for building an integrated digital ecosystem for defense-industrial enterprises is proposed, aimed at enhancing the overall quality of products and services.

Metode Pelaksanaan Pembuatan PC Spun Pile dengan Mutu F'c 52 MPa Pada PT. Wijaya Karya Beton Tbk PPB Majalengka

A concrete plant, also known as a batch plant or batching plant or a concrete batching plant, is equipment that combines various ingredients to form concrete. This implementation aims to determine the manufacturing process and quality control of concrete product production. The method used in this implementation is descriptive quantitative. Steps include operational variables to determine the problem and indicators of the cause of the problem. Data collection through observation and documentation. The results of this implementation show that the implementation of manufacturing at PT WIKA Beton Tbk PPB Majalengka aims to make good concrete products, the factors for making PC Spun Pile products are made based on work instructions or standard operational procedures.

Thermal optimization of alloy additive manufacturing process and visual design of metal process products based on edge computing

Alloy additive manufacturing technology has been widely used in aerospace, medical equipment and automobile manufacturing. The purpose of this study is to explore the thermal energy optimization scheme in the process of alloy additive manufacturing based on edge computing technology, and to display the metal process products in an all-round way through visual design, so as to promote the knowledge and practice of thermal energy management in the industry. In this paper, the edge computing platform is used to monitor the heat energy data generated in additive manufacturing process in real time, and the heat energy distribution is analyzed with machine learning algorithm. By establishing thermal energy optimization model, adjusting manufacturing parameters to reduce energy consumption, improve material utilization and product quality. At the same time, using visual design technology, the optimization process and results are graphically represented, which provides intuitive decision basis for engineers. The experimental results show that the thermal energy optimization scheme based on edge computing significantly improves the thermal energy efficiency of the alloy additive manufacturing process, and significantly reduces the thermal energy loss. Through the visual design, relevant personnel can understand the thermal energy distribution and process changes more clearly, and promote the collaboration between multiple departments. This study reveals the application potential of edge computing in alloy additive manufacturing and provides an effective thermal optimization strategy.

Research on Critical Quality Feature Recognition and Quality Prediction Method of Machining Based on Information Entropy and XGBoost Hyperparameter Optimization

To address the problem of predicting machining quality for critical features in the manufacturing process of mechanical products, a method that combines information entropy and XGBoost (version 2.1.1) hyperparameter optimization is proposed. Initially, machining data of mechanical products are analyzed based on information entropy theory to identify critical quality characteristics. Subsequently, a quality prediction model for these critical features is established using the XGBoost machine learning framework. The model’s hyperparameters are then optimized through Bayesian optimization. This method is applied as a case study to a medium-speed marine diesel engine piston. After the critical quality characteristics in the machining process are identified, the machining quality of these vital characteristics is predicted, and the results are compared with those obtained from a machine learning model without hyperparameter optimization. The findings demonstrate that the proposed method effectively predicts the machining quality of mechanical products.

Quality by design for mRNA platform purification based on continuous oligo-dT chromatography

Oligo-deoxythymidine (Oligo-dT) ligand-based affinity chromatography is a robust method for purifying mRNA drug substances within the manufacturing process of mRNA-based products, including vaccines and therapeutics. However, the conventional batch mode of operation for oligo-dT chromatography has certain drawbacks that reduce this process’s productivity. Here, we report a new continuous oligo-dT chromatography process for the purification of in vitro transcribed mRNA, which reduces losses, improves the efficiency of oligo-dT resin use, and intensifies the chromatography process. Furthermore, the quality by design (QbD) framework was used to establish a design space for the newly developed method. The optimisation of process parameters, including salt type, salt concentration, load flow rate and mRNA load concentration both in batch and the continuous mode, achieved >90% yield (mRNA recovery) along with >95% mRNA integrity and >99% purity. The productivity of continuous chromatography was estimated to be 5.75-fold higher, and the operating cost was estimated 15% lower, when compared to batch chromatography. Furthermore, the QbD framework was further used to map the relationship between critical quality attributes (CQAs) and key performance indicators (KPIs) as a function of critical process parameters (CPPs) and critical material attributes (CMAs).

Industry 4.0 and Sustainability: Analysis of Impacts and Proposed Guidelines

Objective: To survey the impacts of implementing new technologies with the Industry 4.0 concept in a large building materials and related products company and propose sustainable guidelines to minimize negative impacts. Theoretical Framework: Industry 4.0 technologies provide improvements in the product manufacturing process and industry performance through the use of data, but it is necessary to consider the integration of business with social, environmental and governance issues. Method: The methodological approach is a single case study, qualitative in nature, applied and exploratory in purpose. In developing the method, a list of impacts caused by the implementation of Industry 4.0 technologies was created from the theoretical framework, which gave rise to a questionnaire applied to the building materials and related products company by means of a field survey. Results and Discussion: 11 impacts were “observed” by the interviewee, 45 impacts, i.e. the majority of them, were classified as “not observed” and 10 impacts were considered to be “not applicable” to existing technologies due to the fact that the company is a retailer. After analyzing the impacts, sustainable guidelines were suggested for each negative impact. Research Implications: It can be concluded that in most of the literature searched, the economic pillar of sustainability was the most commonly found, thus highlighting the lack of analysis focused on environmental and social issues in the implementation of Industry 4.0 technology in the building materials industry. Originality/Value: It was observed that with regard to sustainability, the building materials and related products company has several very important practices, however, no studies applied to other companies were found in the scientific literature, a fact that makes the proposed work very important.

Comparative Analysis of the use of Band Heaters and Infrared Heaters to Save Energy on Injection Molding Machines Type Borche Bi 320T

This study aims to compare the energy efficiency between the use of a heater band and an infrared heater on an injection molding machine type borche bi 320T. The injection molding machine is one of the main pieces of equipment in the manufacturing process of plastic products and plays an important role in shaping various consumer and industrial products. One of the critical aspects of the operation of injection molding machines is the significant energy consumption, especially related to heating. This study was conducted by measuring the energy consumption of both types of heaters under the same operational conditions. The results showed that the energy consumption of using a band heater was 46.9 kW, while the infrared heater was 38.9 kW, significantly more energy efficient by 17.1% compared to the band heater. Although the initial installation cost of the infrared heater is 87% higher than that of the band heater, the energy savings generated from the infrared heater can reduce operating costs by approximately $39 million per year. Higher energy efficiency means lower electricity costs and, thus, more efficient total production costs. The use of infrared heaters also has a positive impact on the environment. Reduced energy consumption means reduced greenhouse gas emissions from power generation. Therefore, besides the economic benefits, the use of infrared heaters is also in line with sustainability and environmentally friendly practices.

Research on the Efficiency Improvement of Human-Machine Collaboration in Manufacturing Production Process

In modern manufacturing, human-computer collaboration has become an important means to improve productivity and product quality. However, the existing human-computer collaboration process and human-computer interaction interface design still has many deficiencies, which affects its efficiency and safety. This paper aims to explore how to improve the efficiency and safety of human-computer collaboration in the production process by optimising the human-computer collaboration process and designing the human-computer interaction interface. It is found that the efficiency and safety of human-computer collaboration can be significantly improved by optimising the collaboration process, improving the working environment and standardising the workflow through the lean manufacturing theory, and adopting a user-friendly interface design with high information visualisation and ease of operation.

MANUFACTURING AND TESTING HIGH VOLTAGE FILTER CAPACITORS

This paper presents the manufacturing and testing methods of 30kV and 33nF high voltage filter capacitors. One of the biggest advantages of small companies is that they are able to produce a high diversity of capacitors in small quantities. One of the prices of this flexibility is a higher level of manual manufacturing process in production. But this higher level of manual manufacturing does not mean lower quality in the final product. For high quality products in the high voltage industry, it is necessary to do routine tests in all of the products. For high voltage capacitors the following three tests must be done to ensure quality: voltage strength test, partial discharge test, capacitance and dissipation factor test. The capacitance and dissipation factor test have to be done at different voltage levels. The voltage strength test has to be done at least 20% higher than the rated voltage. This kind of test gives us information not only about the quality of the product itself, but about distribution of the capacitance for example, or about the strength of the production process, and about the quality management system of the company.

Sustainable Development of an Innovative Spreadable Plant-Based Product of High Added Value through the Valorization of an Agro-Food By-Product

There is an increased demand for healthy foods by the consumer nowadays, while at the same time, circular bio-economy and sustainability in food production represent top priority issues for the food industry. In this context, purslane, a highly nutritious annual plant that grows abundant during the hottest months of the year but is considered a by-product of the agricultural process, was utilized for the development of an innovative, ready-to-eat food product suitable for a vegetarian diet in the form of a bread spread. Following an initial small-scale experimentation for the stabilization of apparent quality attributes, the product’s recipe was finalized on an industrial scale, and the hazard analysis and critical control point (HACCP) for the manufacturing process, the physicochemical (pH, water activity) and sensorial analysis of the end product, together with its nutritional value, shelf-life, and antioxidant capacity, were determined. The results suggested that the acidic (pH 4.3) product had a shelf-life of a minimum of six months to one year and, according to EU legislation, it comprised a source of (dietary) fibers and protein, while being high in poly-unsaturated (e.g., omega-3, omega-6), and mono-unsaturated (e.g., oleic acid) fatty acids. Total phenolic content (TPC) with the Folin–Ciocalteau assay and total antioxidant capacity (TAC) using the Ferric-Reducing Antioxidant Power assay of the product, presented concentrations of 0.95 mg of gallic acid equivalent/g and 0.016 mmol of Fe2+/g of dry weight of sample, respectively. However, the predicted bioavailability for TPC and TAC was 28% and 31%, respectively. The product was evaluated positively by a panel of potential consumers without significant differences compared to conventional familiar products. The potential of using agro-food chain by-products, such as purslane, for the development of novel foods representing a healthy and tasty food choice at any time of the day is a promising opportunity for the food industry to meet growing consumer demands for more sustainable, nutritious, and healthy food products with a reduced environmental footprint compared to the traditional plant-originated products of intensive agriculture.

Pengembangan Media Audio Pop-Up Book Terhadap Unggah-Ungguh Bahasa Jawa Siswa SMP Negeri 2 Pare

Learning Javanese is included in learning ethics or politeness values, so it is very important to teach it in the world of education. As a tool to attract students' attention and want to learn Javanese, namely by developing learning media in the form of audio pop-up books. This research aims to explain: (1) the process of developing audio pop-up book, (2) the quality of audio pop-up book, (3) student responses to audio pop-up book learning media as a learning medium for uploading Javanese language material at SMP Negeri 2 Pare. This research uses research and development (R&D) methods with a four-D (4D) development model. The resulting data is in the form of oral and written. The data collection techniques used were observation, questionnaires and interviews. The instruments used were observation sheets, questionnaire sheets, and interview sheets. The results of this research are the product manufacturing process starting from needs analysis, product manufacturing plans, to the results of product development. to the final product. Validation from experts received a total percentage of 93.4% and total student responses received a percentage of 91.9% which was included in the "very suitable" category for use.