Production Engineering Research Articles

Aligning production requirements with product and production maturities: enhancing production preparation during product development

AbstractProduct development is multidisciplinary with high uncertainties necessitating coordinated decision-making between design and production. This paper presents a method to work with production requirements to support production preparation during product development aligned with different product and production maturities. The work was conducted in collaboration with two global manufacturing firms. The method supports identification, definition, and structuring of production requirements and the collaboration between design and production engineers for requirement prioritization and follow-up.

A benchmark dataset with Knowledge Graph generation for Industry 4.0 production lines

Industry 4.0 (I4.0) is a new era in the industrial revolution that emphasizes machine connectivity, automation, and data analytics. The I4.0 pillars such as autonomous robots, cloud computing, horizontal and vertical system integration, and the industrial internet of things have increased the performance and efficiency of production lines in the manufacturing industry. Over the past years, efforts have been made to propose semantic models to represent the manufacturing domain knowledge, one such model is Reference Generalized Ontological Model (RGOM).11 https://w3id.org/rgom However, its adaptability like other models is not ensured due to the lack of manufacturing data. In this paper, we aim to develop a benchmark dataset for knowledge graph generation in Industry 4.0 production lines and to show the benefits of using ontologies and semantic annotations of data to showcase how the I4.0 industry can benefit from KGs and semantic datasets. This work is the result of collaboration with the production line managers, supervisors, and engineers in the football industry to acquire realistic production line data22 https://github.com/MuhammadYahta/ManufacturingProductionLineDataSetGeneration-Football,.33 https://zenodo.org/record/7779522 Knowledge Graphs (KGs) or Knowledge Graph (KG) have emerged as a significant technology to store the semantics of the domain entities. KGs have been used in a variety of industries, including banking, the automobile industry, oil and gas, pharmaceutical and health care, publishing, media, etc. The data is mapped and populated to the RGOM classes and relationships using an automated solution based on JenaAPI, producing an I4.0 KG. It contains more than 2.5 million axioms and about 1 million instances. This KG enables us to demonstrate the adaptability and usefulness of the RGOM. Our research helps the production line staff to take timely decisions by exploiting the information embedded in the KG. In relation to this, the RGOM adaptability is demonstrated with the help of a use case scenario to discover required information such as current temperature at a particular time, the status of the motor, tools deployed on the machine, etc.

Towards a formal ontology of engineering functions, behaviours, and capabilities

In both applied ontology and engineering, functionality is a well-researched topic, since it is through teleological causal reasoning that domain experts build mental models of engineering systems, giving birth to functions. These mental models are important throughout the whole lifecycle of any product, being used from the design phase up to diagnosis activities. Though a vast amount of work to model functions has already been carried out, the literature has not settled on a shared and well-defined approach due to the variety of concepts involved and the modeling tasks that functional descriptions should satisfy. The work in this paper posits the basis and makes some crucial steps towards a rich ontological description of functions and related concepts, such as behaviour, capability, and capacity. A conceptual analysis of such notions is carried out using the top-level ontology DOLCE as a framework, and the ensuing logical theory is formally described in first-order logic and OWL, showing how ontological concepts can model major aspects of engineering products in applications. In particular, it is shown how functions can be distinguished from the implementation methods to realize them, how one can differentiate between capabilities and capacities of a product, and how these are related to engineering functions.

A simplex approach for binary linear programming

This article is a research, design, and development effort, on an algorithm for Binary Linear Programming (BLP). The idea of the algorithm is based on the concepts borrowed from the Simplex method of Linear Programming (LP). The Simplex method has both column selection and row selection logics for generating a pivot. In this article we select both logics of LP to use as only the column selection logic for the BLP. The article provides the complete implementable C-language source code of this version of the BLP algorithm to show all the details of the logics. In addition, it provides a simple software requirement for embedded engineering products based on the laws of nature. It helps to design, modify, and maintain a simpler code for the algorithms. Therefore, the article uses a multidisciplinary approach. It integrates optimization theory, matrix algebra, computer programming, software engineering design requirements, social science, laws of nature, etc. This BLP algorithm will shed some light on the P-NP problem and its solution.

Development of a group II intron-based genetic manipulation tool for Streptomyces.

The availability of an alternative and efficient genetic editing technology is critical for fundamental research and strain improvement engineering of Streptomyces species, which are prolific producers of complex secondary metabolites with significant pharmaceutical activities. The mobile group II introns are retrotransposons that employ activities of catalytic intron RNAs and intron-encoded reverse transcriptase to precisely insert into DNA target sites through a mechanism known as retrohoming. We here developed a group II intron-based gene editing tool to achieve precise chromosomal gene insertion in Streptomyces. Moreover, by repressing the potential competition of RecA-dependent homologous recombination, we enhanced site-specific insertion efficiency of this tool to 2.38%. Subsequently, we demonstrated the application of this tool by screening and characterizing the secondary metabolite biosynthetic gene cluster (BGC) responsible for synthesizing the red pigment in Streptomyces roseosporus. Accompanied with identifying and inactivating this BGC, we observed that the impair of this cluster promoted cell growth and daptomycin production. Additionally, we applied this tool to activate silent jadomycin BGC in Streptomyces venezuelae. Overall, this work demonstrates the potential of this method as an alternative tool for genetic engineering and cryptic natural product mining in Streptomyces species.

DESIGN AND ANALYSIS OF CONNECTING ROD USING ANSYS

Connecting Rod is an important component of an internal combustion engine. It serves as an intermediate link between the piston and the crankshaft. It converts the reciprocating motion of piston into rotary motion of crankshaft. It is responsible for transferring power from piston to crankshaft and from there on to the transmission.The most commonly used materials in the production of Connecting Rod are Steel (for production of engines), Aluminium (ability to absorb high impact at the expense of durability, light in weight), or Titanium (combination of strength and lightness at the expense of affordability).The Objective of this project is to Design and Analyse Connecting Rod using different materials. A parametric model of Connecting Rod is modelled using CATIA V5 Software and Analysis is carried out using ANSYS 14.0 Software. Different materials taken into consideration are 42CrMo4, Al7075-T651, Al6061-1.5%SiC-1.5%B4C, Al7068.Performance parameters like Von-misses stress, Deformation and Factor of safety are analysed using ANSYS. From our work, it was observed that Al7068 has more Stiffness, less Stress and less Weight. Keywords:Al7075-T651,Al6061-1.5%SiC-1.5%B4C, Al7068, Aluminium, Connecting Rod

Cultivation of Bovine Mesenchymal Stem Cells on Plant-Based Scaffolds in a Macrofluidic Single-Use Bioreactor for Cultured Meat.

Reducing production costs, known as scaling, is a significant obstacle in the advancement of cultivated meat. The cultivation process hinges on several key components, e.g., cells, media, scaffolds, and bioreactors. This study demonstrates an innovative approach, departing from traditional stainless steel or glass bioreactors, by integrating food-grade plant-based scaffolds and thermoplastic film bioreactors. While thermoplastic films are commonly used for constructing fluidic systems, conventional welding methods are cost-prohibitive and lack rapid prototyping capabilities, thus inflating research and development expenses. The developed laser welding technique facilitates contamination-free and leakproof sealing of polyethylene films, enabling the efficient fabrication of macrofluidic systems with various designs and dimensions. By incorporating food-grade plant-based scaffolds, such as rice seeded with bovine mesenchymal stem cells, into these bioreactors, this study demonstrates sterile cell proliferation on scaffolds within macrofluidic systems. This approach not only reduces bioreactor prototyping and construction costs but also addresses the need for scalable solutions in both research and industrial settings. Integrating single-use bioreactors with minimal shear forces and incorporating macro carriers such as puffed rice may further enhance biomass production in a scaled-out model. The use of food-grade plant-based scaffolds aligns with sustainable practices in tissue engineering and cultured-meat production, emphasizing its suitability for diverse applications.

Ultraviolet technology application in urban water supply and wastewater treatment in China: Issues, challenges and future directions

This study thoroughly explores the application of Ultraviolet (UV) water treatment technology in urban wastewater treatment and water supply in China, highlighting its crucial role in enhancing water quality safety. UV technology, with its environmentally friendly and low-carbon characteristics, is deemed more in line with the demands of sustainable development compared to traditional chemical disinfection methods. The widespread application of UV technology in urban wastewater treatment in China, particularly in the context of urban sewage treatment, is examined. However, to better promote and apply UV technology, there is a need to deepen the understanding of this technology and its application among a broad base of users and design units. The importance of gaining in-depth knowledge about the performance of UV water treatment equipment, the design calculation basis, and operational considerations, as well as the ongoing development of relevant standards, is underscored to ensure that the equipment used in projects complies with engineering design and production requirements. Furthermore, the positive trend of UV technology in the field of advanced oxidation, indicating a promising trajectory for engineering applications, is pointed out. Regarding the prospects of industrial development, a thorough analysis is conducted in the article, emphasizing the necessity for all stakeholders to collaborate and adopt a multi-level approach to promote the sustainable development and application of UV water treatment technology. This collaborative effort is crucial for providing effective safeguards for China's environment, ecology, and human health.

Systems Metabolic Engineering for Efficient Violaxanthin Production in Yeast.

Violaxanthin is a plant-derived orange xanthophyll with remarkable antioxidant activity that has wide applications in various industries, such as food, agriculture, and cosmetics. In addition, it is the key precursor of important substances such as abscisic acid and fucoxanthin. Saccharomyces cerevisiae, as a GRAS (generally regarded as safe) chassis, provides a good platform for producing violaxanthin production with a yield of 7.3 mg/g DCW, which is far away from commercialization. Herein, an integrated strategy involving zeaxanthin epoxidase (ZEP) source screening, cytosol redox state engineering, and nicotinamide adenine dinucleotide phosphate (NADPH) regeneration was implemented to enhance violaxanthin production in S. cerevisiae. 58aa-truncated ZEP from Vitis vinifera exhibited optimal efficiency in an efficient zeaxanthin-producing strain. The titer of violaxanthin gradually increased by 17.9-fold (up to 119.2 mg/L, 15.19 mg/g DCW) via cytosol redox state engineering and NADPH supplementation. Furthermore, balancing redox homeostasis considerably improved the zeaxanthin concentration by 139.3% (up to 143.9 mg/L, 22.06 mg/g DCW). Thus, the highest reported titers of violaxanthin and zeaxanthin in S. cerevisiae were eventually achieved. This study not only builds an efficient platform for violaxanthin biosynthesis but also serves as a useful reference for the microbial production of xanthophylls.

Development of a Database of Educational Games Applicable to Production Engineering

Discussion over the years regarding the quality of newly graduated engineers in Brazil has concluded that there are gaps between learning and market expectations. Analyzing the current scenario, the Ministry of Education (MEC) has approved new national curriculum guidelines that emphasize skills development and the adoption of active methodologies. The aim is to develop students as protagonists of their own learning. One of these methodologies is game-based learning (GBL), which utilizes games for educational purposes to integrate theory and practice. GBL simulates reality and presents concepts in a playful way, resulting in greater student engagement and interest. However, research shows that a lack of knowledge and difficulty accessing such games are barriers to implementing this methodology. Previous research has focused on the development of serious game metadata (SGM), the establishment of controlled vocabularies, and the identification of educational games targeting production engineering (PE). The authors of the present paper developed a database focused on the disciplines and content covered in production engineering courses. The paper describes the database and its aims to: (a) increase the use of games in the teaching-learning process; (b) make the process more effective; and (c) prepare better professionals.

Peach Fuzz: Conceptual Engineering of Color Categories

This article explores the products of conceptual engineering in contemporary media communication and mass culture. The analysis examines the mechanisms and communicative consequences of intentionally creating color categories. The shade known as peach fuzz, selected by the Pantone Institute as the color of the year 2024, is used as a case study. It is shown that in the case of the color of the year, the transmission of the conceptual idea involves two channels simultaneously (visual and verbal), each in two different forms. The author notes that the visual channel is used to ostensively present the shade with specific chromatic characteristics and to develope a complex visual image on this basis. Special attention is paid to the verbal channel, which is utilized in the form of intentionally constructed color designations and supporting stories (conceptual myths). It is concluded that from the perspective of color communication, verbal and visual texts serve fundamentally different functions. The visual representation shows how the viewer should see the color, while the verbal explanation clarifies why this shade is needed. It is demonstrated that the image embedded in the color name sets the desired connotation, which can transform the perception of the shade by adding necessary meanings to it. The verbal story defines a cognitive “point of view” for introducing a new category into an existing color system.

IDENTIFICATION AND ANALYSIS OF RISKS IN CIVIL ENGINEERING PROJECTS

<p>The main and primary goal of the research in this paper is to analyze the actual current situation in domestic civil engineering, by determining the causes of missing deadlines and exceeding budgets of civil engineering projects. Since the results of this research also indicate the most likely problems that could arise during the construction of a project, the findings and conclusions could be used in risk assessment and drawing up dynamic plans for actual projects, which would improve the situation in domestic civil engineering and increase productivity of this important industry. </p> <p>The results obtained in this paper provide a modern approach to the problem of risk in construction, provide a realistic insight into risk factors on civil engineering projects in the Republic of Serbia and the surrounding area, and facilitate the establishment of a better correlation between theory and practice in project management and risk management.</p> <p> </p>

NOx Emission Predictions in Gas Turbines Through Integrated Data-Driven Machine Learning Approaches

Abstract The reduction of NOx emissions is a paramount endeavor in contemporary engineering and energy production, as these emissions are closely linked to adverse environmental and health impacts. The prediction of NOx emission from gas turbines through several integrated data-driven machine learning methods has been evaluated in study. The study compares the performance of ensemble and conventional machine learning models, demonstrating superior accuracy achieved by the ensemble models. Specifically, the Random Forest model achieved an accuracy rate of 91.68%, XGBoost yielded an accuracy of 91.54%, and CATBoost exhibited the highest accuracy at 92.76%. These findings highlight the capability of data-driven machine learning techniques in enhancing NOx emission predictions in gas turbines. The improved prediction by ensembles can be utilized in the development and implementation of more effective control and mitigation strategies in practical applications. Through the application of these advanced machine learning approaches, the gas turbine industry can play a pivotal role in minimizing its environmental impact while optimizing operational efficiency. This study also provides valuable insights into the effectiveness of ensemble machine learning models, advancing our understanding of their capabilities in addressing the critical issue of NOx emissions from gas turbines.

Control of the parameters of the surface layer of steel parts during their processing applying the material homogeneity criterion

The main goal of the presented research is to assess the technological damageability of the material, which can be used as a criterion for analyzing the technological route of product machining in the "blank-workpiece-final part" technological chain. This technological chain is examined in detail in the most important stages of the life cycles of mechanical engineering products in order to take into account the principles of technological inheritability of their characteristics and quality parameters. The technological inheritability of the properties of the surface layers of machines and mechanisms parts from steel during their machining evaluates and predicts the transformation of the structurally heterogeneous material obtained after the production of blanks into the structurally homogeneous material of the final parts. The procedure for evaluating the homogeneity of the processed material for each technological step by the LM hardness method is presented. The developed methodology was implemented and proven during the manufacturing process of the conveyor belt drive drum shaft.

A machine learning based method for parametric environmental impact model for electric vehicles

Environmental managers attempt to increasingly incorporate precautionary principles into decision making. The literature lacks Machine Learning -based approaches for forewarning lifecycle environmental impacts. This paper proposes a method to support electric vehicle design. The main innovation of the work lays in merging Life Cycle Assessment (LCA) and Machine Learning foundations to provide support and awareness to designers. The present approach overcomes the present literature because it provides a method for the design phase, is based on a well-established methodology (LCA) and provides quantitative results from little inputs. The approach exploits machine Learning Methods to develop models with the design features of a generic electric vehicle (such as vehicle mass and distance traveled) in six phases (Problem definition; Data collection; Data Preparation; Modeling; Model evaluation; Model interpretation). Differently from existing environmental analyses, all stages of the product life cycle have been considered in building the database; moreover, the model provides quantitative results. Regression models and supervised algorithms were used. The obtained model can be used by product engineers, as well as those not experts on LCA. Moreover, the model guarantees the database and hypothesis's uniqueness, ensuring the results coherence and comparability. The level of accuracy obtained in the case study (error or 17%) is comparable with studies handling full environmental analysis (that should be more accurate), and outstanding, as the present case is for the design phase. Future works will focus on additional significative indicators, similar electric vehicle design and integration with prospective LCA approaches.

Box-Behnken modeling to optimize the engineering response and the energy expenditure in material extrusion additive manufacturing of short carbon fiber reinforced polyamide 6

The field of production engineering is constantly attempting to be distinguished for promoting sustainability, energy efficiency, cost-effectiveness, and prudent material consumption. In this study, three control parameters (3D printing settings), namely nozzle temperature, travel speed, and layer height (LH) are being investigated on polyamide 6/carbon fiber (15 wt%) tensile specimens. The aim is the optimum combination of energy efficiency and mechanical performance of the specimens. For the analysis of the results, the Box-Behnken design-of-experiment was applied along with the analysis of variance. The statistical analysis conducted based on the experimental results, indicated the importance of the LH control setting, as to affecting the mechanical strength. In particular, the best tensile strength value (σB = 83.52 MPa) came from the 0.1 mm LH. The same LH, whereas caused the highest energy consumption in 3D printing (EPC = 0.252 MJ) and printing time (PT = 2272 s). The lowest energy consumption (EPC = 0.036 MJ) and printing time (PT = 330 s) were found at 0.3 mm LH. Scanning electron microscopy was employed as a part of the manufactured specimens’ 3D printing quality evaluation, while Thermogravimetric analysis was also conducted. The modeling approach led to the formation of equations for the prediction of critical metrics related to energy consumption and the mechanical performance of composite parts built with the MEX 3D printing method. These equations proved their reliability through a confirmation run, which showed that they can safely be applied, within specific boundaries, in real-life applications.Graphical abstract

Combinatorial biosynthesis for the engineering of novel fungal natural products.

Natural products are small molecules synthesized by fungi, bacteria and plants, which historically have had a profound effect on human health and quality of life. These natural products have evolved over millions of years resulting in specific biological functions that may be of interest for pharmaceutical, agricultural, or nutraceutical use. Often natural products need to be structurally modified to make them suitable for specific applications. Combinatorial biosynthesis is a method to alter the composition of enzymes needed to synthesize a specific natural product resulting in structurally diversified molecules. In this review we discuss different approaches for combinatorial biosynthesis of natural products via engineering fungal enzymes and biosynthetic pathways. We highlight the biosynthetic knowledge gained from these studies and provide examples of new-to-nature bioactive molecules, including molecules synthesized using combinations of fungal and non-fungal enzymes.

Thermo-mechanical aging of carbon-black reinforced styrene-butadiene rubber under cyclic-loading

PurposeThe research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.Design/methodology/approachThis study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.FindingsThis study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.Originality/valueThis research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

Application of Cas12j for Streptomyces Editing.

In recent years, CRISPR-Cas toolboxes for Streptomyces editing have rapidly accelerated natural product discovery and engineering. However, Cas efficiencies are oftentimes strain-dependent, and the commonly used Streptococcus pyogenes Cas9 (SpCas9) is notorious for having high levels of off-target toxicity effects. Thus, a variety of Cas proteins is required for greater flexibility of genetic manipulation within a wider range of Streptomyces strains. This study explored the first use of Acidaminococcus sp. Cas12j, a hypercompact Cas12 subfamily, for genome editing in Streptomyces and its potential in activating silent biosynthetic gene clusters (BGCs) to enhance natural product synthesis. While the editing efficiencies of Cas12j were not as high as previously reported efficiencies of Cas12a and Cas9, Cas12j exhibited higher transformation efficiencies compared to SpCas9. Furthermore, Cas12j demonstrated significantly improved editing efficiencies compared to Cas12a in activating BGCs in Streptomyces sp. A34053, a strain wherein both SpCas9 and Cas12a faced limitations in accessing the genome. Overall, this study expanded the repertoire of Cas proteins for genome editing in actinomycetes and highlighted not only the potential of recently characterized Cas12j in Streptomyces but also the importance of having an extensive genetic toolbox for improving the editing success of these beneficial microbes.

Experimental Investigation of a Free-Form Honed Cylinder Liner for Heavy-Duty Engines

For future internal combustion engines, driven by regenerative fuels, efficiency is more important than ever. One approach to reduce the losses inside the piston cylinder unit (PCU) is to improve the alignment of the liner and the piston. Therefore, a cylinder liner with a free form was developed at the Institute of Technical Combustion (ITV) of the Leibniz University Hannover which compensates radial and linear deformations along the stroke. The layout is based on a FEM simulation. The liner was manufactured by the Institute of Production Engineering and Machine Tools (IFW) of Leibniz University of Hannover with a novel turn-milling process. The liner was investigated on the heavy-duty Floating-Liner engine of ITV with a displacement of 1991 ccm and a bore diameter of 130 mm. The experimental results show improvement in the friction losses over the whole engine map in the range of 9% and up to 17.3% compared to a serial liner. Sealing efficiency could be improved up to 28.8%, depending on the operational point. Overall, the investigation aims for lower fuel consumption which would in result fewer emissions.