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Demand shocks and fluctuations underscore the need for new approaches to coordinate collaboration between firms to scale up production. This paper proposes an approach to formalise product and process requirements via a collaboration ontology and applies semantic reasoning techniques for process formation. Our approach contributes to production research by providing flexibility in coordinating firms engaged in demand-driven collaboration. The proposed approach has four core dimensions: (1) The Collaboration ontology builds on a set of product assembly requirements, process steps, their input/output resources and semantic rules; (2) the ontology reasoner derives resource dependencies between the steps; (3) the java tool interprets resource dependencies as possible transitions in Business Process Management Notation (BPMN); (4) a workflow engine executes the generated product assembly process. The approach and the ontology were validated in an industrial aerospace tendering scenario demonstrating its practical relevance for firms seeking demand-driven collaborations to react to production changes. Finally, we position and explain our contributions to the body of knowledge in collaborative production engineering. [ABSTRACT FROM AUTHOR]

The concept of sustainable development is driving shell biorefineries to develop a cost-effective and environmentally benign approach to transform chitin into high-value products. This study describes a green, simple, and flexible shell biorefinery process for producing two kinds of nanochitins (NCh), chitin solid residues (ChSRs) and chitin nanocrystals (ChNCs), by using p-toluenesulfonic acid-assisted hydrothermal treatment. The ChSR is a bundled nanocrystal with a long length ranging from 100 nm to 450 nm and a width ranging from 10 nm to 30 nm. It has an excellent interfacial behavior between the water and oil phases due to its amphiphilic nature; thus, a foodstuff-related emulsion has been successfully fabricated from soybean oil and a ChSR suspension without the addition of any synthetic surfactants. The further hydrolysed ChNC with a length and width range of 25–225 nm and 15–30 nm, respectively, and a high zeta potential of 41 mV exists as an individual nanocrystal. Owing to the abundance of positively charged groups distributed on its surface, ChNC enables self-assembly to a highly ordered hierarchical structure. Hence, ChNCs show promising results in fabricating large-area photonic films, e.g. for application in bright and vivid automobile painting. Altogether, we provide a novel approach to produce NCh materials from crustacean shell waste and bridge the gap from process engineering to high-value product development. [ABSTRACT FROM AUTHOR]

Automotive glass is one of the key components in manufacturing engineering, and the inspection of defects is essentially an important item of quality evaluation. Deep learning has become a promising technology and is very suitable for defect detection. However, a unified method to detect all kinds of defects is very difficult due to the few publicly available image datasets of automotive glass, and it is a challenge to deploy high-precision models in resource-constrained edge devices. Focusing on these problems, defect detection in automotive glass based on modified YOLOv5 with pseudo-tagging and dual lightweight strategy is developed in this paper. First, aiming at the problem that the defect samples are extremely lacking, combined pseudo-labeling and traditional data expansion methods have been explored to effectively increase the number of samples for meeting the requirement of deep learning model training, thus improving the performance of the detection model. Second, double lightweight modules, MobileNetV3, and Ghost module are introduced into the backbone and the neck network of the YOLOv5 model, respectively, for reducing the complexity of the model. In addition, a multi-scale feature fusion (M-SFF) module, which riches the semantic and spatial information of feature maps, is added to the output of the backbone to further improve the detection accuracy of the model. The effectiveness of each innovation module was verified through ablation experiment and horizontal comparative experimentally. Experimental results show that the complexity and deployment difficulty of the improved YOLOv5 model are significantly reduced, the floating-point operations per second (FLOPs) values and weight sizes are significantly smaller than those of other models, and the detection performance is also improved based on the original YOLOv5, an average accuracy increase of 3.9 % on average, precision slightly decreased, and recall rates increased by 7.6 % . The method is appropriate for applications in the defect inspection of automotive glass. [ABSTRACT FROM AUTHOR]

A fluid mechanics course in process engineering designed according to the students' wishes mixes lecture and exercise in co‐teaching and flipped‐classroom elements with gamification. The effectiveness increases as the number of points achieved in the exam increases by 31.9 % compared to the average of the four previous years. The withdrawal rate drops from 54.8 % to 17.4 % and the failure rate from 38.7 % to 23.7 %, which enhances efficiency. The students' self‐report shows a better preparation to the course sessions, but they do not feel stressed much additionally. About 80 % of the initially attending students participate at the end of the course. [ABSTRACT FROM AUTHOR]

Aqueous two-phase systems (ATPS), also known as Aqueous Biphasic Systems (ABS), have been extensively studied as platforms for the separation and purification of biomolecules and other valuable compounds. These liquid–liquid extraction (LLE) systems have been a tool for biotechnology since its origin (Albertsson, 1950's), recently expanding to exciting fields such as health, biomedicine and material sciences. Due to their biocompatibility, amenability, flexibility, and versatility, ATPS have been applied across various research areas, addressing many challenges associated with conventional methodologies. In this feature article, we first discuss the fundamentals of ATPS and the molecular mechanisms that govern their formation and are crucial for their application. We then explore the most prominent and innovative applications of these systems in downstream processing. Additionally, we provide insights into the design of in situ upstream–downstream integrated platforms, and their use as pre-treatment and analytical tools. The latest advancements in ATPS applications within disruptive bioengineering and biotechnology fields are presented, along with their pioneering use in emerging scientific areas, such as the formation of all-aqueous (water-in-water) emulsions, microfluidic systems, and membrane-free batteries. Overall, this work underscores the transformative potential of ATPS in various branches of science, pinpointing directions for future research to fully explore and maximize ATPS capabilities, overcome existing hurdles, and drive innovation forward. [ABSTRACT FROM AUTHOR]

In the past five years, the number of articles related to ultrasonic mineral flotation has increased by about 50 per year, and the overall trend is on the rise. The most recent developments in ultrasonics for flotation process intensification are reviewed herein, including effects of ultrasound treatment on an aqueous slurry, improvement in flotation methods and technological processes, device development tracking, and application effects in mineral process engineering. At this point in time, there are pilot-scale flotation tests to evaluate the feasibility of ultrasonic pretreatment technology for industrial use to enhance residue flotation separation, and the results showed that the recovery rate of concentrate is increased by about 10%. Four aspects of ultrasonic flotation process improvement are summarized, namely, changing the ultrasonic parameters, the synergistic effect of ultrasound and reagents, the ultrasonic effect of particles with different-sized fractions, and application to new systems. In addition, the effect of ultrasonic flotation mechanisms is explored through a quadratic model and numerical simulation. The combination of ultrasonic flotation with other fields, such as magnetic fields, to enhance the separation efficiency and recovery of minerals is also a future trend. It is also proposed that ultrasonic flotation technology will be used with big data, industrial Internet of Things, and automatic control technology to achieve deep bundling, optimizing the flotation process by implementing remote monitoring and control of the flotation process. [ABSTRACT FROM AUTHOR]

According to survey data released by the National Bureau of Statistics, from 2011 to 2022, the total output value of China's construction industry showed an increasing trend year by year. From 2018 to 2021, infrastructure investment has always maintained a positive growth, indicating that the current construction industry is in a rapid development stage. In order to improve the development quality of the construction industry as much as possible, it is of great significance to develop the whole Process engineering consulting service model. The quality evaluation of whole process engineering consulting service modes is MAGDM. The single-valued neutrosophic sets (SVNSs) is useful tool to cope with uncertain information during the quality evaluation of whole process engineering consulting service modes. In this paper, the single-valued neutrosophic number combined TOPSIS (SVNN-CTOPSIS) model based on single-valued neutrosophic number Hamming distances (SVNNHD) and single-valued neutrosophic number Euclidean distance (SVNNED) is formed to cope with the MAGDM. The CRITIC model is utilized to obtain the weight numbers in light with the SVNNHD and SVNNED under SVNSs. Finally, numerical example and comparative analysis for quality evaluation of whole process engineering consulting service modes is utilized to verify SVNN-CTOPSIS model. The main contributions of this study are formed: (1) the CRITIC model is formed to obtain the weight numbers in light with SVNNHD and SVNNED; (2) the SVNN-CTOPSIS model is formed in light with SVNNHD and SVNNED under SVNNs; (3) Finally, numerical example and comparative analysis for quality evaluation of whole process engineering consulting service modes is employed to verify SVNN-CTOPSIS model. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to integrate the Sustainable Development Goals (SDGs) in the outlines of a Master's Degree in Industrial Engineering using active learning methodologies. The main objective of this integration is to favor sustainable human education and to increase students' awareness and responsibility towards future generations from the chemical engineering point of view. Within the process engineering course, the students must design a chemical process using technical, economic, social and environmental criteria. Active learning methodologies were gradually introduced in different academic courses (Project-Based Learning, Collaborative Work and Flipped Classroom) and finally SDGs were implemented in the 2020–21 academic course. A synergetic effect with the active learning methodologies was observed, increasing the motivation of the students and the academics, and the complexity of the projects performed by students. The introduction of the SDGs improved academic results, which was reflected in the absence of failures and a decrease in the percentage of students passing with the lowest grade from 16 % to 10 %. Moreover, students report that this project significantly enhanced their knowledge of the SDGs related to energy and climate change; students having low or very low knowledge about SDGs were reduced to 7 % as compared to the initial 45 %. • Active learning methodologies are a successful tool for the integration of SDGs in engineering courses. • The SDGs integation in the chemical processes design improves the quality, increasing the best marks from 83.9 % to 90.0 %. • The use of SDGs opens the door to introduce the development of new transversal Competences. • Face-to-face sessions are crucial for an effective learning when flipped classrooms are Implemented. • The introduction of SDGs in one PBL using flipped classroom has a very motivating effect on students. [ABSTRACT FROM AUTHOR]

Copyright of Revista Fatec Zona Sul (REFAS) is the property of Revista Fatec Zona Sul (REFAS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For reservoir fluids with strong volatile tendencies, such as gas condensate and volatile oil, the determination of the characteristic parameters of the equation of state has a great influence on the fluid phase behavior and subsequent reservoir engineering, production engineering, and surface facilities design calculations. However, the process of characterizing reservoir fluid lacks a unified and standardized procedure, and the methods are largely empirical and rather complicated. In this paper, three main stages are defined for the characterization of the equation of state parameters for these volatile reservoir fluids, including (1) determining the C7+ distribution, (2) calculating the equation of state parameters for the C7+ single-carbon component, and (3) lump components. The typical calculation methods in each step and their effects on the fluid phase behavior calculations are quantitatively analyzed and compared. Finally, the workflow and the suitable characterization methods for gas condensate and volatile oil phase behavior calculations are selected. The results show that C7+ distribution and C7+ single carbon component properties have a greater influence on the phase behavior prediction of condensate gas and volatile oil, while the lumping of C7+ single carbon component has relatively little influence. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the article was to develop a QLCA framework model dedicated to the design and improvement of products, taking into account their quality (Q) and environmental impact in the life cycle (LCA). Design/methodology/approach: A review of the literature on the subject was conducted on studies from the Web of Science database. The thematic scope included the design and improvement of products, taking into account quality and environmental impact during the life cycle (LCA). Bibliometric and frequency techniques were used, including keyword analysis and citation of studies. Based on conclusions from the literature, approaches and methods for quality improvement, as well as the LCA methodology presented in the ISO 14040 standard, a QLCA framework model was developed. The model supports the prospective assessment of the quality and life cycle of the product and its prototypes in terms of sustainable development. Findings: It has been shown that there are no solutions that present the links between product life cycle assessment and product quality assessment, including preparing these assessments for product prototypes at the design and prototyping stage. Research limitations/implications: A QLCA framework model is presented, the proper form of which will be provided by future research. The framework conditions of the QLCA model were improved and expanded in order to find the most advantageous approach to achieving the highest quality product quality with the lowest possible negative environmental impact of this product in LCA in terms of its sustainable development. Practical implications: The QLCA framework model is the result of conceptual generalisation, and its assumptions were prepared for designers and R&D departments. The assumptions of the QLCA methodology can be used by management staff to make decisions about product improvement at the prototyping stage. Originality/value: A novelty is the QLCA framework model, which presents an original approach to product improvement at the prototyping stage, taking into account customer expectations regarding their quality and at the same time assessing the life cycle of these prototypes [ABSTRACT FROM AUTHOR]

Imaging the internal architecture of fast-vibrating structures at micrometer scale and kilohertz frequencies poses great challenges for numerous applications, including the study of biological oscillators, mechanical testing of materials, and process engineering. Over the past decade, X-ray microtomography with retrospective gating has shown very promising advances in meeting these challenges. However, breakthroughs are still expected in acquisition and reconstruction procedures to keep improving the spatiotemporal resolution, and study the mechanics of fast-vibrating multiscale structures. Thereby, this works aims to improve this imaging technique by minimising streaking and motion blur artefacts through the optimisation of experimental parameters. For that purpose, we have coupled a numerical approach relying on tomography simulation with vibrating particles with known and ideal 3D geometry (micro-spheres or fibres) with experimental campaigns. These were carried out on soft composites, imaged in synchrotron X-ray beamlines while oscillating up to 400 Hz, thanks to a custom-developed vibromechanical device. This approach yields homogeneous angular sampling of projections and gives reliable predictions of image quality degradation due to motion blur. By overcoming several technical and scientific barriers limiting the feasibility and reproducibility of such investigations, we provide guidelines to enhance gated-CT 4D imaging for the analysis of heterogeneous, high-frequency oscillating materials. [ABSTRACT FROM AUTHOR]

Currently, the development of renewable energy products (RES) encourages the search for innovative solutions that take into account key criteria from the point of view of their sustainable development. Despite efforts in this area, there is a lack of approaches and tools to support this process. Therefore, the aim of the research was to develop a decision-making model supporting eco-innovation in products based on the key criteria of sustainable development: quality (customer satisfaction with use), environmental impact in the life cycle (LCA), and the cost of investment incurred in the product development. The functioning of the model was based on the following factors: (i) obtaining the voice of customers (VoC) and processing it into product criteria as part of the development of alternative production solutions (prototypes), (ii) prospective quality assessment and subsequent life cycle assessment of prototypes, (iii) cost analysis taking into account both quality and environmental criteria, (iv) interpretation of results and search for eco-innovative product solutions. Development decision-making is additionally supported by techniques implemented in the model, e.g., the CRITIC method, the LCA method with Ecoinvent database in OpenLCA, the CEA method, and the morphology method. The model was illustrated and tested for photovoltaic (PV) panels, after which a global sensitivity analysis was performed in Statistica. The test results showed that the main factor that influenced the PV development decisions was the investment cost, followed by quality (customer satisfaction) and then environmental impact in LCA. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates the application of a self-coder neural network in oilfield rod pump anomaly detection. Rod pumps are critical equipment in oilfield production engineering, and their stability and reliability are crucial to the production efficiency and economic benefits. However, rod pumps are often affected by anomalies such as wax deposition, leading to increased maintenance costs and production interruptions. Traditional wax deposition detection methods are inefficient and fail to provide early warning capabilities. This paper reviews the research progress in sucker rod pump anomaly detection and autoencoder neural networks, providing a detailed description of the construction and training process of the autoencoder neural network model. Utilizing data from the rod-pumped wells of the Tuha oilfield in China, this study achieves the automatic recognition of various anomalies through data preprocessing and the training of an autoencoder model. This study also includes a comparative analysis of the differences in the anomaly detection performance between the autoencoder and traditional methods and verifies the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Total quality management (TQM) is a strategic philosophy that has adopted kaizen activities which drives the business to carry out activities effectively to yield the best desired output, hence, a profitable organization. The kaizen philosophy acts as a catalyst in productivity rate and integrated management systems (IMS) which results in drastic improvements. When the nonconformity arises within the process, the accuracy of the problem solving determines quality of preventive action, therefore the preventive action should be accompanied by the opportunity of improvement from the raised nonconformance. This research seeks to add more knowledge and upgrade technology of problem-solving models relating to the integrated management systems by examining various troubleshooting models for problem solving and preventive action related to quality nonconformances, safety incidents and engineering breakdowns. Hence, the aim of this research is for troubleshooting model technique enhancement for issues related to process engineering, quality management systems and occupational health and safety by creating a model which analyses kaizen projects from the corrective and preventive action analysis of nonconformances. The proposed troubleshooting model was developed using lean techniques and risk rating tools; it was then applied to the case study company for simulation and the outcomes resulted in the closure of nonconformances and continual improvement of future projects. The proposed model is more advantageous to the manufacturing industries seeking to improve their Corrective Action and Preventive Action (CAPA) systems. [ABSTRACT FROM AUTHOR]

The objective of this investigation was: (i) to develop a model that supports sustainable product development, considering the quality aspect and the environmental impact in the product life cycle, and (ii) to establish a framework to select the proportion of the share of these aspects during product development decisions. This research concentrates on achieving products that meet customer demand and have environmentally friendly life cycles. It also supports the implementation of design activities at an early stage of product development, positioning the share of quality in relation to environmental impact. The model is based on creating hypothetical prototypes of current products, and this approach concentrated on aggregating the quality (customer satisfaction) with life cycle environmental impacts (as in ISO 14040). The model was developed in five main stages, including: (i) defining product prototypes according to the modifications of quality criteria most desired by customers, (ii) assessing the quality of prototypes according to the Q quality index, (iii) prospective assessment of the environmental impacts of the life cycles of prototypes according to the LCA environmental index, (iv) methodical integration of the above-mentioned indicators into one quality and environmental indicator QLCA, and (v) analysis of possible production solutions and setting the direction of product development, taking into account both quality and environmental aspects. This research was extended with a sensitivity analysis of the QLCA indicator, after which a framework for selecting the proportion of the Q and LCA indicator's share in product development decisions was established. The originality of this research is the ability of the developed model to facilitate eco-innovative product design and improvements while also selecting the share of qualitative and environmental aspects needed to develop sustainable products. The results provide a dynamic and effective tool for manufacturing companies; mainly designers and managers during qualitative and environmental prototyping of products commonly used by customers. The model will provide support in predicting a product that will be manufactured that will be satisfactory for customers and environmentally friendly based on LCA. [ABSTRACT FROM AUTHOR]

Currently used machine diagnostic systems are based on very modern solutions based on the acquisition and recording of their operating parameters in real time. Increasingly available and high-tech sensor systems mean that the number of recorded parameters is increasing and their quality is improving. These data are mainly used to assess the technical condition of machines and the processes they perform. In mining, these data can also be used to assess and, at a later stage, improve the safety of the underground mining process. Referring to this issue, the paper presents examples of the use of diagnostic systems for powered roof supports and longwall shearers to assess the safety status of the underground hard coal mining process. In the case of the wall support, the focus was on measuring the pressures in the stands of its individual sections. Temporary changes in the values of these pressures constitute a valuable source of information regarding the interaction of the support with the rock mass. In particular, this concerns the identification of the effects of the informational impact of the rock mass on the longwall excavation protected by the support. The research results presented in the paper, especially in the case of very dangerous dynamic impacts, indicate the possibility of both diagnosing the operating condition of the section and identifying symptoms of exposure to such events. This undoubtedly significantly expands the possibilities of using the measured pressures. Diagnostic signals from a longwall shearer are also widely used. The current intensities drawn by its motors while cutting the rock mass, as well as the advance speed and its position in the wall make it possible to analyze these parameters and their changes before, during and after the occurrence of various types of events. These data enable the assessment of the effects of the rock mass on its operational efficiency and safety status. It also enables the identification of symptoms that precede the occurrence of such events. The presented examples indicate the need for a broader and more holistic approach to the use of diagnostic parameters of mining machines. In particular, this concerns the study of the cooperation between the support and the rock mass and its influence on the efficiency and safety of the rock mass mining process. The subject matter addressed relates to very important and current issues, and the developed methodology and obtained results should be applied in practice as soon as possible.

The sustainability of products remains a challenge, mainly due to the lack of consistent approaches for simultaneously taking into account the key criteria of the concept in the process. This research aims to develop an eco-innovative QLCA method to create new product solutions that integrate quality (customer satisfaction) and environmental impact assessment throughout the product life cycle. The QLCA method includes: (i) product prototyping according to quality and environmental criteria; (ii) prospective assessment of the quality of prototypes, taking into account customer requirements; (iii) prospective life cycle assessment of product prototypes using a cradle-to-grave approach in accordance with ISO 14040; and (iv) setting the direction of product development while taking into account the fulfilment of customer expectations and the need to care for the environment throughout the product life cycle. Owing to the lack of previous research in this area, as well as the popularity of photovoltaic (PV) panels in reducing greenhouse gases, an illustration was obtained and test of the method was carried out on the example of silicon photovoltaic panel modules (Crystalline Si PV Module). In accordance with the adopted assumptions, the results of the QLCA method test showed that the modelled PV prototypes will, in most cases, be satisfactory for customers, but they still require improvement actions to reduce carbon dioxide (CO2) emissions throughout their life cycle. These activities should be consistent so as to achieve quality that satisfies customers. The QLCA method can be used by designers, managers, and decision-makers at the early stages of design, but also during the product maturity phase for its sustainable development. [ABSTRACT FROM AUTHOR]

The development of materials and the products made from them should respond to new challenges posed by market changes and also by climate change. Therefore, the objective of this investigation was to develop a method that supports the sustainable development of materials and the products made from them based on an aggregated indicator of quality and environmental load in the life cycle (QLCA). The testing and illustration of the QLCA method included a passenger car tyre and nine prototypes. These prototypes were described using eight quality criteria: season, class, size of the load index, speed index, rolling, adhesion, and external noise. Then, customer expectations regarding the importance of the criteria and satisfaction with the indicators in the current and modified states were obtained. Based on the customer assessment, the quality indicators of the prototypes were assessed. This assessment was supported by the weighted sum model (WSM) and the entropy method. Then, life cycle assessment for the reference tyre was performed using the Ecoinvent database in the OpenLCA program. LCA indicators were modelled for other prototypes, taking into account quality changes. As a result of the verification of the method, an aggregated QLCA indicator was estimated, based on which it was possible to select the most favourable (qualitatively and environmentally) prototype out of nine. This was the P4 prototype (QLCA = 0.57). The next position in the ranking was taken by P7 (QLCA = 0.43). The QLCA method can be used to determine the direction of development of materials and products in terms of their sustainable development. [ABSTRACT FROM AUTHOR]

Compared to heat pumps established in the building sector, high‐temperature heat pumps (HTHPs) suitable for industrial use still face challenges, not only from a mechanical engineering point of view but also regarding integration into existing processes. They need to supply larger amounts of heat at higher temperatures. The mere replacement of a gas boiler by an HTHP will rarely deliver an energy‐efficient solution. Instead, these units must often be tailored to the application and vice versa, making specifications a complex task. This paper intends to link thermodynamic and economic basics of HTHPs to the process engineering of the actual production process. It also ventures an outlook on the economic and regulatory boundary conditions in the EU as corner stones for a sustainable investment decision. [ABSTRACT FROM AUTHOR]

Researchers have studied Stewart-Gough platforms, also known as Gough-Stewart platforms or hexapod platforms extensively for their inherent fine control characteristics. Their studies led to the potential deployment opportunities of Stewart-Gough platforms in many critical applications such as medical field, engineering machines, space research, electronic chip manufacturing, automobile manufacturing, etc. Some of these applications need micro- and nano-level movement control in 3D space for the motions to be precise, complicated, and repeatable; a Stewart-Gough platform fulfills these challenges smartly. For this, the platform must be more accurate than the specified application accuracy level and thus proper calibration for a parallel robot is crucial. Forward kinematics-based calibration for these hexapod machines becomes unnecessarily complex and inverse kinematics complete this task with much ease. To experiment with different calibration techniques, various calibration approaches were implemented by using external instruments, constraining one or more motions of the system, and using extra sensors for auto or self-calibration. This survey paid attention to those key methodologies, their outcome, and important details related to inverse kinematic-based parallel robot calibrations. It was observed during this study that the researchers focused on improving the accuracy of the platform position and orientation considering the errors contributed by one source or multiple sources. The error sources considered are mainly kinematic and structural, in some cases, environmental factors also are reviewed; however, those calibrations are done under no-load conditions. This study aims to review the present state of the art in this field and highlight the processes and errors considered for the calibration of Stewart-Gough platforms. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Petroleum Geology & Oilfield Development in Daqing is the property of Editorial Department of Petroleum Geology & Oilfield Development in Daqing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hydrocracking is a vital process in the refining industry that converts heavy crude oil into high-value products such as gasoline, jet fuel and diesel. The optimization of hydrocracking units is crucial for improving the efficiency and profitability of these units. Optimization techniques have emerged as a powerful tool in process engineering to address conflicting objectives such as maximizing product yield while minimizing energy consumption. A refinery in Africa started commercial production in 2019. Using Aspen HYSYS V.14, Industrial hydrocracking unit was simulated and survey was done to find opportunities for optimization. In this paper, it presents case studies on the optimization of an industrial hydrocracking unit using Aspen HYSYS. it begins with a brief overview of the hydrocracking process and its typical outputs then introduces some techniques of energy optimization. The case study description and methodology, including the specific objectives and simulation setup, are presented. it discusses the results and analysis of the optimization process, including the impact on the unit's performance and trade-offs between different optimization objectives. The case studies handled in the paper are optimization of reactor effluent air cooler (REAC) with saving of 5.4 MMKcal/hr of its duty, optimization of fractionator feed heater duty with saving of 12.75 MMKcal/hr of its duty and optimization of unit's downtime required for catalyst change over with saving of 5 days downtime. Finally, it explores the implementation and implications of the results for industrial practice and the potential benefits and challenges of applying optimization in hydrocracking unit. [ABSTRACT FROM AUTHOR]

Modelling real processes often results in several suitable models. In order to be able to distinguish, or discriminate, which model best represents a phenomenon, one is interested, e.g., in so-called T-optimal designs. These consist of the (design) points from a generally continuous design space at which the models deviate most from each other under the condition that they are best fitted to those points. Thus, the T-criterion represents a bi-level optimization problem, which can be transferred into a semi-infinite one but whose solution is very unstable or time consuming for non-linear models and non-convex lower- and upper-level problems. If one considers only a finite number of possible design points, a numerically well tractable linear semi-infinite optimization problem arises. Since this is only an approximation of the original model discrimination problem, we propose an algorithm which alternately and adaptively refines discretizations of the parameter as well as of the design space and, thus, solves a sequence of linear semi-infinite programs. We prove convergence of our method and its subroutine and show on the basis of discrimination tasks from process engineering that our approach is stable and can outperform the known methods. [ABSTRACT FROM AUTHOR]

Process engineering education requires a comprehensive foundation and practical application. To bridge the gap between theoretical education and market requirements, a "Project Planning Course" has been offered since 2018 as part of the MSc specialization in Chemical Engineering at the FHNW School of Life Sciences. The course didactics combines the principles of an "agile" teaching mindset and problem-based learning, which optimally support the experience of this module. Students had to work on unresolved real-world problems, make decisions based on incomplete information, and present their work in a board meeting role play with board members from industry. These situations represent typical real-world challenges for future chemical engineers. The results show that most of the students learned to cope with the unconventional teaching methodology. The students' evaluations of the module have been very positive, especially the fact that the active participation of the students triggers the actual learning process - which means that the essential learning goal has been achieved. • Develop 21st century skills with team learning, critical thinking and communication. • Learn to deal with uncertainty using trained reasoning and framework documents. • Simulate real life with Board Meeting role plays ("pitch the concept"). • Agile didactics suit engineering tasks and thus its education. [ABSTRACT FROM AUTHOR]

Agriculture and coffee production are vital to Brazil's economy, generating jobs, driving regional development, and contributing significantly to the trade balance, making Brazil a leading coffee producer and exporter. In this context, this scientific article proposes automating coffee production traceability using QR codes to optimize processes and enhance quality, safety, and sustainability in the supply chain under the Industry 4.0 paradigm. We employ Business Process Model and Notation modeling to delineate coffee production stages, leveraging QR codes for data collection and registration during activities like harvesting, washing, drying, processing, storage, and farm certification validation. QR codes streamline operations, reduce errors, and enhance traceability, involving actors ranging from harvesters to quality personnel, inspectors, and clerks. The study scrutinizes coffee transfer from rural producers to warehouses, optimizing stock and delivery management. The main results obtained were the significant reduction in the number of employees, the reduction of activities and consequently the time, and finally, the assertiveness to complete the process. [ABSTRACT FROM AUTHOR]

Online quality control methods emphasize manufacturing processes to attain maximum conformance with respect to the specifications of the concerned quality characteristics of a product. One key factor that affects the effectiveness of these methods is the diagnosis interval. In this paper, the existing cost model along with its cost components for online quality control methods has been revisited and modified by incorporating new variables like the rate of production, the loss due to false alarm, the loss due to non-detection of process abnormalities, and considering a workable break-up of diagnosis cost for finding the optimal diagnosis interval from the perspective of present-day manufacturing engineering. As already mentioned, the proposed cost model has not ignored the loss due to the generation of defective items as well as the adjustment cost available in the pertinent literature. The modified cost function thus proposed has been appropriately minimized to obtain the corresponding optimal diagnosis interval. The proposed methodology has been compared numerically with other methodologies to establish its effectiveness. The cornerstone of the proposed methodology lies in reinforcing its effectiveness through a real-life case example in manufacturing. Sensitivity analysis has also been carried out for the real-life case example to fortify the proposed methodology. [ABSTRACT FROM AUTHOR]

While there are software tools available for helping to conduct life cycle assessment (LCA), such as OpenLCA, these tools lack integration with process design, simulation, and optimization software. As LCA has a critical role in sustainable product design, this paper presents a platform called EMSO_OLCA, which integrates the LCA provided by OpenLCA into the Environment for Modeling, Simulation, and Optimization (EMSO). EMSO_OLCA incorporates a database of environmental impact assessment methodologies from OpenLCA and aligns with the principles of LCA outlined in ISO 14040 and ISO 14044. Validation tests were conducted to compare the results obtained by the LCA of sugarcane ethanol using OpenLCA and EMSO_OLCA, revealing a high level of agreement. The average relative error was 0.045%, indicating a negligible discrepancy between the tools. Moreover, it took only 0.3 s for the calculation, which is desirable for use with process system engineering tools. A second case study was applied to combined steam and electricity production from the combustion of sugarcane bagasse and straw in a combined heat and power system. The results show the integration of LCA with simulation and sensitivity analysis tools, thus supporting sustainable decision-making processes. EMSO_OLCA bridges the gap between LCA and process engineering, enabling a holistic approach to the sustainability, design, and implementation of environmentally friendly solutions. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Production Engineering / Revista Brasileira de Engenharia de Produção is the property of Brazilian Journal of Production Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The escalating environmental impact of pollution and the imperative to reduce carbon emissions have heightened the significance of developing biobased materials from natural biomass for electronic devices. This study investigates the utilization of biofermentation‐produced recombinant spider silk and animal‐derived hemin to create a novel biobased electret for field‐effect transistor memory. A critical challenge arises from the incompatibility between natural photoresponsive molecules and insulating biomaterials, resulting in severe phase separation that compromises film quality and morphology uniformity. This study systematically examines the effects of various film deposition and manufacturing techniques on the biobased electret's morphology, phase separation, and performance. Different methods demonstrate distinct advantages in terms of molecular aggregation/segregation, morphological homogeneity, and device performance. Phototransistor memory devices fabricated using spin coating and spray coating techniques exhibit robust aggregations and high memory windows of ≈30 V. Conversely, devices produced through solution shearing and electrospinning methods display enhanced smooth morphologies and high photoresponsivity. The phototransistor memory comprising electrospun fibers holds the potential to achieve the highest memory ratio, reaching ≈105. These findings not only highlight the applications of biobased materials through scalable film deposition processes but also underscore the importance of refining their morphology, phase separation, and performance in optoelectronic devices. [ABSTRACT FROM AUTHOR]

As an all-in-one process that blended design, materials, and manufacturing, additive manufacturing (AM) adopted a bottom-up stacking approach, thereby avoiding excessive infrastructure and complex production steps. However, the different process stages of AM were influenced by multi-scale factors such as material characteristics, parameter settings, and process stability, resulting in uncertainty. Therefore, the effective containment and accurate evaluation of automated production processes were crucial. With the rapid development and widespread application of artificial intelligence (AI) technologies in the Industry 4.0 era, computer vision (CV) techniques, as an important component, could achieve multi-level understanding of the real world through traditional machine learning (ML) and efficient deep learning (DL) approaches based on information-dense cross-media data such as images, videos, and three-dimensional models. Hence, the organic integration of CV and AM was of great significance for the virtual simulation, global perception, real-time monitoring, and quality measurement of the machining processes. According to the chronological order and logical relationship of manufacturing engineering, this paper organized and summarized the application of CV techniques in material characteristics perception and stacking process simulation before the implementation of projects, in situ inspection, and law exploration during the manufacturing processes, as well as product evaluation and defect detection after processing, which demonstrated its powerful performance and great potential in the intelligence and integration of AM. [ABSTRACT FROM AUTHOR]

In this research, the levels of safety, health, and environmental risks in a building stone processing company (BSPC) have been identified using the integrated approach of the EFMEA (Environmental Failure Mode and Effects Analysis) and the William Fine method, along with the TOPSIS technique for prioritizing organizational safety layers, examining potential incidents, and enhancing organizational efficiency. To achieve this, data and risk assessment information were first collected and evaluated, and then, with the formation of an expert task force, brainstorming sessions were held to identify and analyze environmental risks in the production process using the EFMEA technique. Additionally, with the assistance of the William Fine method, safety and health risks in the production process were identified and examined. In the next step, the costs of corrective actions were calculated, and the results obtained from the tables of both EFMEA and William Fine techniques were combined, and decisions were made regarding risks with high and very high levels. Subsequently, using TOPSIS, protective layers were prioritized based on two criteria: cost and time. Following the risk assessment using the EFMEA method, four risks were classified as high-risk, nine risks as medium-risk, and two risks as low-risk. Subsequently, employing the William Fine technique, a total of 41 hazards were evaluated across five worksheets. 5% of the hazards were categorized as very high-risk, 19% as high-risk, 27% as medium-risk, and 49% of the evaluated hazards were classified as low-risk. Ultimately, the results obtained from the integration of the William Fine and EFMEA techniques categorized two risks as very high-risk, 12 risks as high-risk, 20 risks as medium-risk, and 22 risks as low-risk. Furthermore, working at heights was selected as one of the risks with high-risk, and protective layers and control measures were proposed and examined. The use of helmets, shoes, harnesses, and the establishment of a safety platform, considering both time and cost criteria, is the first priority for controlling risks in working at heights activity. [ABSTRACT FROM AUTHOR]

The area of data science knowledge responsible for dealing with this new reality is diffuse, including mathematics, statistics, computing, engineering, psychology, and administration, among many other areas that make up a new scenario that is still changing. Different models have emerged over the years to systematize the procedures to be followed. Among them, CRISP-DM (Cross Industry Standard Process for Data Mining) has become one of the most widespread in the industry. However, the lack of detailed instructions means the framework is often incorrectly used. Therefore, this research aims to present a utilitarian and didactic model based on the latest advances in the literature and through the lens of production engineering. In order to achieve this objective, exploratory research was carried out based on a systematic review and subsequent categorization of each of the CRISP-DM steps, detailing the authors' contributions to each stage. In addition, it is proposed that guidelines from the areas of Quality Management and Risk Management be added to the subject, consolidating a useful and didactic model of relevance. [ABSTRACT FROM AUTHOR]

Plastic waste is an environmental challenge, but also presents a biotechnological opportunity as a unique carbon substrate. With modern biotechnological tools, it is possible to enable both recycling and upcycling. To realize a plastics bioeconomy, significant intrinsic barriers must be overcome using a combination of enzyme, strain, and process engineering. This article highlights advances, challenges, and opportunities for a variety of common plastics. The way we generate and treat plastic waste is a key consideration in the transition from a take-make-waste model to a truly circular economy. Here, authors discuss their views on how biotechnology could contribute to solving the plastic problem, and the barriers we need to overcome to make such approaches a reality. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering (17264073) is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Using different interaction channels within open innovation partnerships holds the potential to enhance the chance of success in production sectors. However, our comprehension of how open innovation partnerships are affected by varying combinations of interaction channels, and how this corelates with their level of open innovation output, remains limited. There are discrepancies in the current literature regarding the individual and combined effects of open innovation interaction channels. Our study aims to resolve these inconsistencies by using a configurational perspective, which allows for the identification of multiple successful pathways. Employing fuzzy-set Qualitative Comparative Analysis (fsQCA) to a dataset of European open innovation partnerships in production sectors, we uncover specific combinations of interaction channels that explain high levels of innovation outcomes. Subsequently, we distinguish between two successful pathways. Notably, we observe that the relationship between interaction channels is causally complex, high engagement in open innovation may not guarantee favorable innovation outcomes. This finding highlights the intricate causal dynamics at play. Thus, our study is a significant step toward reconciling the disparate perspectives in the literature concerning the impact of interaction channels on open innovation output. [ABSTRACT FROM AUTHOR]

Equipment integrity is an essential aspect of process engineering. Design guidelines facilitate the design and production of safe-to-operate and economic devices. Thin-walled, slit-shaped modules form a subgroup of process engineering devices made via additive manufacturing (AM). Being subject to internal pressure, they have lacked design guidelines until now. We derived a user-centered calculation model for such modules with regular internal structures. It was validated with Finite Element Analysis (FEA) and practical pressure tests for which the modules were manufactured additively. The performance of the calculation could be confirmed, and a design graph was derived. Slit-shaped modules with appropriate internal structures can withstand high pressure at a minimum wall thickness, and they are efficiently fabricated. These structures, being pins, fins, lattice, or heat transfer enhancing fluid-guiding elements (FGEs), occupied approximately 10% of the modules' internal volume. [ABSTRACT FROM AUTHOR]

Engineering companies, which are concerned with manufacturing activities in forming and welding technologies, consider with such a degree of an automation of the production process that will bring production improvement, lower production time and also economic benefits with return of investment. In the present time, businesses depend on a market economy conditions. Therefore, it is necessary to design production systems as very flexible with easy response to changes in a product range. In forming and welding technologies, which belong mostly to an area of wasteless technologies, an application of systems with a certain level of intelligence means a wide use of robots that replace the physical potential of people. They have a positive effect on a production quality and also on an ecology. [Hasse 2020] [ABSTRACT FROM AUTHOR]

Tracer study is one of the continuous quality improvement tools for curriculum development. The graduates are invited to answer the tracer form to determine their employability. Since the Manufacturing Engineering program in Bulacan State University (BuLSU) is the youngest engineering program, there is minimal data on graduates available, especially on the details of their first jobs, such as the first job related to the program, time taken to land their first job, gross monthly salary, and learning competencies. The demographic profile of the manufacturing engineering graduates from 2015 to 2019 is preserved and remains strictly confidential for the safety of their identification. Correspondingly, the study applied a cross-sectional retrospective survey method. Moreover, 67.41% of manufacturing engineering graduates responded. The employment rate of manufacturing engineering graduates was 93.38%, whereas regular or permanent in their current employment was 84.40%. Furthermore, data show that they are employed within less than a month, 50.97% of responses. Lastly, the primary learning competency that manufacturing engineering graduates consider is critical thinking skills, with a response rate of 86.11%, followed by problem-solving skills, with 81.94% responses, while third was communication skills, with a rate of 78.08%. Ultimately, the recommendations for further curriculum and program improvement are exhibited. [ABSTRACT FROM AUTHOR]

Lithium‐ion batteries inherently suffer from a target conflict between a high energy density and a high power density. The creation of microscopic holes in the electrodes alleviates the trade‐off by facilitating lithium‐ion diffusion. This study presents a novel concept for electrode structuring called structure calendering, combining mechanical embossing (MEC) and calendering. It is compared to the widely investigated laser ablation (LAS) process by structuring graphite anodes and examining their geometrical, mechanical, and electrochemical properties. It is shown that structure calendering results in wider and deeper holes of higher reproducibility than laser structuring. As a consequence of the different hole‐creation mechanisms, laser structuring induces a surface elevation around the holes while clogged pores are observed in the lateral walls of mechanically structured holes. In pull‐off tests, no pronounced impact of electrode structuring on the mechanical electrode properties is discerned. Structuring of electrodes using both methods yields significantly reduced electrode tortuosities and enhanced discharge rate performances. From a production engineering perspective, structure calendering has advantages over laser structuring in terms of material loss, processing rate, and investment costs, while the latter offers higher flexibility, precision, and presumably lower maintenance efforts. In conclusion, structure calendering represents an attractive process alternative to laser structuring. [ABSTRACT FROM AUTHOR]

The CAMX 2024 conference, held in San Diego, celebrated its 10th anniversary and brought together nearly 500 exhibitors and over 6,300 attendees. The event featured a comprehensive program with technical papers, speakers, campfire sessions, education sessions, tutorials, and facility tours, providing insights into the latest innovations and trends in composites manufacturing and advanced materials. The conference kicked off with a keynote address by futurist Maurice Conti, highlighting the role of technology and materials science in shaping the future. The CAMX Exhibit Hall showcased a diverse array of businesses from various industries, and the event concluded with a discussion of key industry trends. CAMX remains a cornerstone for the industry, driving innovation and collaboration. The next conference, CAMX 2025, will be held in Orlando, FL. [Extracted from the article]

Sustainable development has caused companies to try to adapt their activities to changing customer expectations, but also to climate change. This poses a particular challenge for SMEs from developing countries. Therefore, the objective of the investigation was to analyse the qualitative-environmental aspects of the improvement of the products in SMEs from the countries of the Visegrad Group (V4). The results analysed constituted a research sample of 379 companies in the electrical machinery industry (machine processing industry), which were obtained in the period from March to September 2023 through a targeted survey. The area of analysis included, e.g.: (i) environmental issues of selected areas of activity, (ii) measures of environmental activity, and (iii) selected qualitative-environmental aspects. Analyses of the research results were carried out using quantitative and qualitative analyses, including comparative analyses, e.g. regarding the implementation status of ISO 14001, EMAS, and ISO 9001. These techniques were used: word cloud, ANOVA test and Mann Whitney U test at the significance level of α=0.05. It has been shown that SMEs in V4 countries focus their activities on improving products to improve their quality rather than limiting their negative environmental impact. Originality of the research is the identification of significant differences in the qualitative-environmental aspects undertaken when SMEs from V4 countries. Research results may contribute to the development activities more effective and coherent in the V4 countries, to achieve a stable and competitive advantage on the market as part of the qualitative and environmental improvement of the products. The research results and the conclusions drawn from them can be used by scientists and practitioners to shape the target states of enterprises in the period of increasing involvement in proecological ideas.