Engineering Methods Research Articles

Valorization of marble sludge waste in biodiesel production using a central composite design.

This work addresses the scarcity of energy resources and environmental issues by concentrating on the synthesis of biodiesel by the transesterification of waste cooking oil with methanol. Marble sludge (MS), a novel heterogeneous catalyst, was used to speed up the rate of reaction. The catalyst's physical and chemical characteristics were thoroughly examined using a variety of methods, including X-ray diffraction, X-ray Fluorescence, SEM, particle size distribution, and BET analysis. Using the MS catalyst, the study investigated the impact of important parameters on the yield of biodiesel from waste cooking oil with the aid of response surface methodology using Design-Expert version 13 software. These parameters included temperature (50-70℃), reaction time (1-4h), catalyst concentration (1-5 wt%), and methanol-to-oil molar ratio (5-20mol/mol). Optimization of the parameters was performed for economic targets to lower the production cost of biodiesel. The results showed that a methanol-to-oil molar ratio of 20:1, a catalyst of 5 wt%, and a reaction time of 1h at 57℃ were the ideal parameters for obtaining a biodiesel yield of 93.5%. The resultant biodiesel revealed promising characteristics, such as a flash point of 160℃, a kinematic viscosity of 4 mm2/s, and a density of 0.871g/cm3. The study demonstrates the significant consequences and real-world advantages of using rational engineering methods to use MS as a very effective, stable, and easily recoverable catalyst for the long-term, sustainable generation of biodiesel from waste cooking oil.

A Review on the Implementation and Effectiveness of Lean Manufacturing Strategies for Industrial and Service Sectors

Ensuring a neat, clean, organized, safe, and productive workplace is essential for every organization. Waste and abnormalities may lead to a high loss of productivity and, consequently, capital, along with a significant compromise to the health and safety of the stakeholders. To overcome such challenges, Lean manufacturing is implemented worldwide. The main aim of this technique is to reduce or eliminate certain types of waste (such as those related to motion, transportation, overproduction, waiting time, etc.) that may contribute to financial loss for the companies. The Lean technique is hybridized with other industrial engineering methods such as DMAIC, Six Sigma, Kanban, etc., depending on the situation. This paper reviews some of the vital work in the last five years on implementing Lean manufacturing for various industrial, commercial, and service setups. It first introduces Lean manufacturing, discusses its implementation procedure and tools and techniques, and presents an analysis of previous attempts made by researchers and engineers using Lean to minimize waste, maximize productivity and efficiency, and enhance quality. The article ends with concluding remarks and highlighting the directions for future research. The novelty of this article lies in the fact that along with a basic introduction and review of the last five years’ literature, it also sheds light on current trends; recent developments; Lean integration with Six-Sigma, Kanban, Kaizen; automation and digital technology interventions to increase the effectiveness of Lean manufacturing; contribution of Lean in sustainable development.

Multi-Criteria Decision Making in Chemical and Process Engineering: Methods, Progress, and Potential

Multi-criteria decision making (MCDM) is necessary for choosing one from the available alternatives (or from the Pareto-optimal solutions obtained by multi-objective optimization), where the performance of each alternative is quantified against several criteria (or objectives). This paper presents a comprehensive review of the application of MCDM methods in chemical and process engineering. It systematically outlines the essential steps in MCDM including the various normalization, weighting, and MCDM methods that are critical to decision making. The review draws on published papers identified through a search in the Scopus database, focusing on works by authors with more contributions to the field and on highly cited papers. Each selected paper was analyzed based on the MCDM, normalization, and weighting methods used. Additionally, this paper introduces two readily available programs for performing MCDM calculations. In short, it provides insights into the MCDM steps and methods, highlights their applications in chemical and process engineering, and discusses the challenges and prospects in this area.

Live or Let Die: MILSTD 1472 Type Usability Checklists in an Agile Development World

Traditional Human System Integration (HSI) processes are at risk of being eliminated given the industry driven velocity and continuous delivery methods of Agile and Development to Operations Engineering. One such process at risk is usability standard checklists like MIL-STD 1472. The DoD Design Criteria Standard—Human Engineering, or MIL-STD 1472 is a military standard that provides guidelines for the ergonomic design of military systems and equipment. It is primarily focused on ensuring that military systems are designed to optimize human performance, safety, and comfort. However, it can be time-consuming to use given that it contains over 4,400 compliance items in its entirety. In an Agile DevOps environment, the typical delivery of products is 2 weeks with some software products boasting deployments every 11 min. Incorporation of usability and rigorous human factors checklists in the design of products using a DevOps environment is a challenge given the shorter timelines and smaller increments between product development and deployment combined with the expertise and hours needed to execute the checklists. The need for regression testing, the act of re-checking items to make sure new features have not created unforeseen usability issues, exacerbates the problem. Software quality testing for each release demands automatic methods to reduce the efforts of recursive testing. Industry standard methods in agile engineering utilize heuristics for quick turn low-cost usability inspections. This paper describes the derivation of a set of usability heuristics based on MIL-STD 1472 which can be used to identify potential human factors issues more quickly, with less cost, and reduced amount of expertise required. The paper also gives an example of a case study which incorporated automatic checking to support usability experts keeping pace with the high velocity pipelines of software development in an agile DevOps environment.

Strain Engineered Semiconductor Nanomembranes for Photonic and Optoelectronic Applications

AbstractWhen semiconductor crystals are made into the form of thin sheets, i.e., nanomembranes, their properties and behaviors may be remarkably different from their bulk counterparts. A plethora of fascinating science and important applications arise consequently, some of which are investigated in recent years, and there are still a lot more to be discovered in the future. Nanomembranes (NMs) provide a good platform for strain engineering and offer tremendous research opportunities in photonics and optoelectronics applications. Strain alters energy band line up of a material furthermore influencing its carrier mobility which impacts a wide range of applications. In this article, the strain‐engineered NMs are reviewed using semiconductor materials as a model system for photonics and optoelectronics applications. While many fundamental aspects of NMs are discussed and outlined different methods for strain engineering of NM, the use of semiconductor NMs for photonics and optoelectronics applications is the locus of the present review article.

Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders

Most single-screw extruders used in the plastics processing industry are plasticizing extruders, designed to melt solid pellets or powders within the screw channel during processing. In many cases, the efficiency of the melting process acts as the primary throughput-limiting factor. If the material melts too late in the process, it may not be sufficiently mixed, resulting in substandard product quality. Accurate prediction of the melting process is therefore essential for efficient and cost-effective machine design. A practical method for engineers is the modeling of the melting process using mathematical–physical models that can be solved without complex numerical methods. These models enable rapid calculations while still providing sufficient predictive accuracy. This study revisits the modified Tadmor model by Potente, which describes the melting process and predicts the delay-zone length, extending from the hopper front edge to the point of melt pool formation. Based on extensive experimental investigations, this model is adapted by redefining the flow temperatures at the phase boundary and accounting for surface porosity at the beginning of the melting zone. Additionally, the effect of variable solid bed dynamics on model accuracy is examined. Significant model improvements were achieved by accounting for reduced heat flow into the solid bed due to the porous surface structure in the solid conveying zone, along with a new assumption for the flow temperature at the phase boundary between the solid bed and melt film.

Molecular Engineering in the Semiconductor Industry: Progress and Prospects

Abstract. Along with population growth and economic development, human demand for energy and information will be more than ever, and humans need to rely on semiconductor devices to achieve energy storage, signal and other conversions. So how to design and prepare semiconductor materials with better performance, and industrialise and commercialise the materials has become a new hot topic. Typically, semiconductor materials are nanomaterials, and the current mainstream industrial processing is a top-down process, which raises the cost of production and leads to a waste of resources. Because of this, scientists are starting to believe that molecular engineeringa bottom-up strategy based on molecule self-assembly can save resources, energy, and production costs by constructing semiconductor material structures. This paper examines the bottom-up conceptual approach of molecular engineering and discusses the potential challenges in applying molecular self-assembly technology, which is a crucial method in molecular engineering, to the semiconductor industry. It ultimately concludes that molecular engineering plays a significant role in the semiconductor production process due to its advantages and vast potential for development.

Penerapan Model Incremental Delivery pada Pengembangan Aplikasi Sistem Informasi Hotel Cipta Jakarta

Along with the development of the times, we see many hotels experiencing changes. A change that is rarely reviewed as a news topic is the software overhaul that occurs in hotels from offline to online systems. Lay people only see changes in hotels from a visible perspective, without having to know whether the hotel's system and system applications have changed. One of the factors in system development at Hotel Cipta is the need for hotel management to prioritize the development of system applications from offline to online systems, even web-based. It is not easy to overhaul an existing system application compared to creating a new system application. There are several software engineering methods and models that are commonly used to analyze system needs and design systems in the software development process. One of them is the incremental delivery model. This makes it interesting to try to apply the incremental delivery model to the development of the Hotel Cipta information system application by taking place at the Hotel Cipta on KH. Wachid Hasyim Street, Central Jakarta. In this study, the object of research is the Front Office department.

The HVAC system engineering method for a new family of unified cabins of combine harvesters

BACKGROUND: Designing a combine harvester cabin climate system is a complex and multi-stage process that includes solving a set of tasks. To solve them, a design engineer must have knowledge and skills in various fields, starting with thermal engineering calculations and ending with experimental research methods and computer modeling, which requires a large amount of intellectual and time resources. Therefore, the task of creating a unified method of engineering of combine harvester cabin HVAC system is highly relevant. AIM: Development of the HVAC system for a unified cabin of a grain harvester and a forage harvester. The designed HVAC system is purposed to create a comfortable microclimate in the cabin of the combine for 2 people in summer and winter operating conditions. METHODS: The methodology of calculation and selection of the combine harvester cabin HVAC system, which includes the development of engineering calculation methods and mathematical modeling of thermodynamic and ventilation processes in the cabin, is considered. RESULTS: The main parameters were determined: heat intakes and heat losses for the grain harvester and forage harvester cabins, which amounted to 2.8 and 2.2 kW for the grain harvester, 2.9 and 2.35 kW for the forage harvester; the required air flow rate supplied to the cabin to ensure a comfortable temperature — 740 m3/h; the percentage of air recirculation regarding the conditions of absence of fogging and creation of excessive pressure in the cabin — 75%; the cooling and heating capacity of the HVAC system, taking into account the operating conditions of the combine, are 7.8 and 6.3 kW respectively. The selection of the main equipment of the HVAC system for a unified cabin for a new family of unified cabins of combines — the BUHLER 1000 MFWD evaporator-heater and the Valeo TM16 compressor are chosen. CONCLUSION: The HVAC system designed in accordance with the presented methodology is capable of ensuring a comfortable cabin air temperature in the range of 22–24 °C at various operating modes of the combine harvester in different regions. In addition, the HVAC system parameters eliminate fogging of the cabin windows and the penetration of dusty air inside due to the created excessive pressure.

Application of Machine Learning for Predictive Analysis and Management of Mediterranean-Farmed Fish Mortalities: A Risk Management Case Study Using Apache Spark

The current study evaluates the performance of three machine learning models—Decision Trees, Random Forest, and Linear Regression—applied to aquaculture data to mitigate risks in aquaculture management. The performances of these models are analyzed and properly demonstrated using metrics including the Mean Squared Error (MSE), R-squared (R2), Root Mean Squared Error (RMSE), and Concordance Index (C-index). The Random Forest model achieved the highest prediction accuracy among all machine learning models, followed by Linear Regression and the Decision Trees. The scatter plot for Linear Regression demonstrates good predictive accuracy for mid-range values. However, it shows significant deviations at the extremes, indicating that the model struggles to capture the full range of variability in the data. The bar chart of coefficients pinpoints the variables with the greatest impact on the predictions, providing suggestions for potential areas that can be improved and providing model interpretability. Future work could incorporate more predictive statistics models focusing on improving the models for extreme values by assessing non-linear models, feature engineering methods, and expanding research into less influential variables. The results greatly impact several sections, including aquaculture management, policy-making, and operational strategies, providing valuable insights for stakeholders and decision-makers. Apache Spark was used for data processing and machine learning model implementation; Apache Cassandra was also used for data storage, ensuring efficient large dataset management and SQL tools for structured data handling; Oracle VM VirtualBox for cross-platform virtualization; and Spark Connector was also used.

DEVELOPMENT OF AUTOMATED CONTROL SYSTEM AND REGISTRATION OF METAL IN CONTINUOUS CASTING

Context. Modern industrial enterprises face challenges that require introduction of latest technologies to improve efficiency and competitiveness. In metallurgy, one of key stages is continuous casting, where quality of products and economic performance of enterprise depend on accuracy and efficiency of process control. Products made using continuous casting technology are widely used in various industries due to their high mechanical properties, structural uniformity and cost-effectiveness. The development of automated metal management and registration system is becoming not only relevant, but also necessary to ensure stable and efficient production. The problem of improving quality of metal products has always been one of most important tasks in steel industry. Imperfect technological processes, human error and equipment malfunctions can lead to defects in finished metal products. This, in turn, affects final characteristics of products, their durability and reliability. To date, available sources have not yet found complete solution to this problem. Therefore, it is necessary to formulate problem and develop algorithm for operation of automated system for controlling and registering metal in continuous casting. Objective. The goal of work is to develop automated metal management and registration system to improve quality of metal products. Method. To achieve this goal, parametric model was proposed, which is formalized on basis of set theory. The model takes into account key parameters of continuous casting process: material characteristics, structural features of crystallizer, casting modes, metal level in crystallizer, and position of shot stopper. Results. The problem was formulated and key parameters were determined, which are taken into account in system’s algorithm, which made it possible to develop system for controlling parameters of continuous casting to solve problem of improving quality of metal products. Conclusions. To improve quality of metal products and stability of casting process, parametric model was created that is comprehensive, allows optimization of key parameters and ensures accuracy of process control by integrating not only modes of product formation, but also takes into account specific properties of source material (chemical composition of material grade, etc.) and design features of casting plant. Algorithm for automated control system has been developed that takes into account relationships between certain key parameters and ensures optimal control of casting process. Based on proposed complex parametric model and algorithm, automated control and metal registration system was created. The focus of work is on quality and efficiency of metal management and registration in continuous casting, based on modern methods of computer science and engineering. A comprehensive experimental comparison of developed system with commercial analogs in real production conditions was carried out, which allowed us to objectively assess its efficiency and reliability.

Product development of sweets chocolate cube using value engineering method

Cocoa is one of the plantation commodities that has an important role in economic activities as a foreign exchange earner. Indonesia is ranked first in Asia with the highest consumption of chocolate, which is 7.3 kg per capita. Chocolates are seen by consumers as a comfort food or stress relief. For consumers who buy chocolate for their own consumption, consuming chocolate in a small size causes consumers to act more impulsively to consume larger quantities. Consumption of chocolate in small sizes (one bite size) gives the impression that the product has a premium image and higher quality. The purpose of this study was to identify the characteristics of chocolate that influence the decisions of product purchasing and to develop one-bite-sized chocolate cubes using the value engineering method. The study used 433 respondents with the criteria of chocolate consumers aged 15-40 years. Based on the research, chocolate bars and molded chocolate are the types of chocolate most often consumed with a frequency of 2-3 times a month. Consumers have the highest complaints when consuming chocolate, namely melted chocolate which makes hands dirty due to its big size and is too hard to bite. Based on the consumer needs analysis, consumers want the development of milk chocolate cube candy with nuts filling. Four alternative cube milk chocolate concepts with a cocoa mass percentage of 50% were prepared using 2 variations in the number of cocoa beans and cocoa fat (40%:10% and 35%:15%) and 2 variations of nuts (almonds and cashews). Based on the hedonic test results, milk chocolate cubes with a formula of 10% cocoa butter and cashew nut filling had the highest product value of 0.013 compared to other formulas. Chocolate color and ease of eating are the attribute weights with the highest weights. It can be concluded that the milk chocolate cube formula is 40% cocoa beans; 10% cocoa butter, cashew nut filling is the selected formula with a production cost of IDR 985.00/g.

3D Bioprinting Tissues: Revolutionizing Organ Transplants

The shortage of organ donors presents a critical challenge in modern healthcare, with demand for organ transplants far outstripping supply. 3D bioprinting, a transformative innovation leveraging biological materials and cells to create tissues and organs, offers a promising solution. This review examines the evolution of 3D bioprinting from early tissue engineering methods to its current role in regenerative medicine and organ transplant applications. It discussed key bioprinting techniques, bio-inks, and scaffold materials that support tissue growth, as well as the technical challenges and ethical considerations faced by researchers. With potential applications ranging from cartilage and skin grafts to fully functional organs, 3D bioprinting stands at the forefront of a new era in organ transplantation. However, barriers such as vascularization, biocompatibility, and regulatory hurdles remain before this technology can be fully integrated into clinical practice. Keywords: 3D bioprinting, organ transplantation, bioink, regenerative medicine, tissue engineering.

Interlayer engineering of V2O5·nH2O by conductive Ni-BTA enabling high-performance aqueous ammonium ion batteries

Aqueous ammonium ion batteries (AAIBs) are of interest due to the low molar mass, small hydration radius, abundant raw materials and high safety of the carrier ammonium-ion. Nevertheless, there are numerous constraints associated with electrode materials that are suitable for ammonium-ion storage. In this study, we design and synthesize a composite comprising of one-dimensional conductive metal-organic skeleton material (1D c-MOF) embedded between layers of hydrated vanadium pentoxide (VOH) with improved ammonium-ion storage. The central ion of the 1D c-MOF is selected to be the nickel ion, while the ligand is 1,2,4,5-benzenetetramine (BTA). The incorporation of Ni-BTA between the vanadium oxide layers results in the formation of a composite (Ni-BTA/VOH) exhibiting enhanced structural stability, augmented layer spacing and elevated conductivity. Furthermore, the dual energy storage mechanisms of VOH and CN rearrangement act in concert to yield a “1+1 > 2” effect, thereby markedly enhancing the ammonium-ion storage. The specific capacity of Ni-BTA/VOH can reach 183 mAh g−1 at 0.2 A g−1, and the retention rate can reach 52.5 % after 500 cycles at 2 A g−1. This work not only proves the potential of Ni-BTA/VOH for widespread application in the field of aqueous batteries, but also provides a new method for structural engineering of VOH with boosted ammonium-ion storage properties.

Machine learning-based predictive model for temperature and comfort parameters in indoor enviroment using experimantal data

The research introduces an artificial neural network model that predicts temperature and assesses thermal comfort metrics for a cooling room, demonstrating how machine learning advancements can enhance thermal efficiency and cost-effectiveness in building design. The study utilized the Levenberg-Marquardt (LM) artificial neural network (ANN) approach to derive the average temperature and thermal comfort metrics collected under actual operating settings. The Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD)values were measured at three distinct sites and then compared to the trial findings. The model uses a dataset of 205 observations, with 143 cases used for training and 31 examples for testing and validation. The ANN model demonstrated effective training, with negligible errors in estimated error values. The mean squared error values for average temperature and thermal comfort parameters were 0.0342, 0.0376, 0.0571, 0.0029, and 0.2296. The R values for temperature measurements are 0.9947 and 0.9923, 0.9847 and 0.9437, and 0.9737, demonstrating a highly effective engineering method. The ANN model provided precise predictions for temperature and thermal comfort metrics, such as PMV and PPD in a cooling chamber, with a tolerance of ± 15 %. The LM approach, a machine learning methodology, produced excellent outcomes, particularly at lower temperatures, with 15 % of the data exceeding this range.

Al modification layer method for enhancing InAlZnO transistors

In this work, a surface engineering method is proposed to boost electrical performance and stability of the InAlZnO (IAZO) transistors, of which an Al modification layer is deposited on surface of the IAZO channel layer. Through analysed by transmission electron microscope and X-ray photoelectron spectroscopy, the IAZO thin film with Al modification layer undergoes a reduction reaction to generate more oxygen vacancies. Hall effects measurement further demonstrates that IAZO thin films with Al modification layer exhibit higher carrier concentrations than the ones without Al modification layer. The IAZO transistors with Al modification layer exhibit better performance and stability, including a field-effect mobility of 4.36 cm2 V−1s−1 (an improvement of about three-fold), a small subthreshold swing of 105.23 mV/decade, a high on-to-off current ratio greater than 107, and a threshold voltage shift of less than 0.50 V under positive and negative gate bias stress. Moreover, the IAZO transistors with Al modification layer demonstrate high thermal stability under 400 °C for 120 min in air atmosphere. Based on this method, the IAZO inverters have been implemented with high voltage gain of 87.55 V/V. This surface engineering technology paves the way for application of high-performance oxide transistors for advanced monolithic three-dimensional integration.

Innovative Design and Fast Iterative Manufacturing of Micro-Turbojet Engines at Low Cost

The turbojet is the foundation of the gas turbine engine, which combines knowledge of fluid dynamics, thermodynamics, heat transfer, mechanical design, manufacturing, and jet propulsion. This paper describes in detail the inspiration source, design process, fluid dynamics analysis, manufacturing steps, ignition test method and test process of small jet engines. 3D modeling software SolidWorks was used for the preliminary modeling and fluid simulation was performed to optimize the design. Part of the model was produced by 3D resin printing technology, and the turbine engine model was driven by compressed air for no-load testing to verify the feasibility and structural stability of the resin model. Subsequently, some parts were printed with metal materials, combined with traditional machining techniques to complete production and assembly, and finally successfully carried out static ignition tests. The micro turbojet engine designed in this paper has successfully achieved static ignition test and demonstrated the feasibility of efficient development with limited resources and low manufacturing cost. This exploration proves the feasibility of rapid iteration technology route. The market prospect and manufacturing cost of micro turbojet are also analyzed.

Synergistic Surface Engineering of BiVO4 Photoanodes for Improved Photoelectrochemical Water Oxidation.

Surface engineering of BiVO4 photoanodes is effective and feasible for photoelectrochemical (PEC) water splitting. To achieve superior PEC performance, however, more than one surface engineering method is usually indispensable, for which a positive synergistic effect is vital and thus highly desired. Herein, it is reported that the incorporation of borate moieties into ultrathin p-type NiOx catalysts can induce the reconfiguration of surface catalytic sites to form new highly active species, in addition to enhanced fast charge separation and transfer. The photocurrent density of BiVO4 photoanodes is enhanced from 1.49 to 5.76 mA cm-2 at 1.23 V versus reversible hydrogen electrode (RHE) under AM 1.5G illumination, which is achieved by successive modifications of NiOx and borate moieties. It is found that BO3 groups anchored to Ni atoms by replacing the surface hydroxyl sites of NiOx catalysts not only increase the relative ratio of Ni3+ species to facilitate charge transfer but also provide efficient active sites for H2O molecule adsorption and oxidation reactions. This work demonstrates the positive synergistic effect of these two surface engineering methods and provides an effective pathway to construct highly efficient and stable photoanodes for PEC water splitting.

Determination of converter parameters for high-voltage electromechanical systems of stationary installations of industrial fans

Purpose. To study the electromagnetic processes in the circuit of the phase rotor of a high-voltage induction motor connected to the network through a step-up converter, to determine the parameters of the converter and their relationship with the voltage gain to ensure the optimal level of energy efficiency of the electromechanical system. Methodology. Methods of theoretical electrical engineering for the construction of a rotor circuit replacement scheme for an induction motor with a step-up converter, methods for solving a system of first-order differential equations, analytical methods. Findings. The expediency of using a converter that combines the rotor circuit of a high-voltage induction motor with the power supply network and provides regulation of the rotor EMF with the recovery of the slip energy of the induction motor rotor to the power supply network has been proved. This will ensure speed control of powerful high-voltage induction motors on the rotor side with an EMF of up to 600 V and significantly reduce the cost of a high-voltage electromechanical system. A methodology for determining the converter gain and the parameters of the rotor circuit of the electromechanical system is proposed, which allows determining the transformation ratio of the matching transformer at the optimal value of the voltage gain. The conditions of trouble-free operation of the inverter at the moment of start-up of the electromechanical system are determined. Achieving these conditions is ensured by determining the delay of the control signal to the power keys of the inverter of a step-up converter. The correlation between the voltage gain and the equivalent resistance of the rotor circuit of the electromechanical system is established. Originality. The ratio of the voltage gain to the equivalent resistance of the rotor circuit of the electromechanical system is established, which will ensure the matching of the rotor EMF with the voltage of the power supply network while maintaining a high level of energy efficiency. Practical value. A methodology for determining the gain and parameters of a step-up converter is proposed, which allows determining the transformation ratio of a matching transformer at the optimal value of the voltage gain. The proposed methodology can be applied to the modelling of complex powerful high-voltage electromechanical systems, especially for stationary installations of industrial fans.

The Dawning Era of Anticancer Nanomedicines: From First Principles to Application of Silk Nanoparticles

AbstractThis review introduces nanomedicines and medical silks by addressing seminal and recent research within these fields. First, the successes of nanoparticles in improving the safety profiles and pharmacokinetic–pharmacodynamic properties are explored but also the concepts of threshold dosing and targeting of tumor‐associated macrophages. Current barriers to systemic delivery of nanomedicines are detailed and methods to overcome these barriers and increase tumor targeting are evaluated, namely: tuning the nanomedicine size and surface charge for enhanced tumor accumulation and penetration; non‐spherical nanomedicine morphologies for macrophage evasion and targeted delivery to endothelial cells; and, surface functionalization for stealth coatings and targeting receptor‐mediated endocytosis. The advantages of using silk as a nanomedicine with reference to its structure, composition, biological performance, and formulation are discussed. While batch methods for silk processing enable the formation of nano to microparticles, continuous technology can overcome bottlenecks of the deployed engineering methods such as low throughput and poor reproducibility. Finally, the chemical modification of silk using homogeneous and heterogenous chemistries is assessed within the nanomedicine context. Overall, this review covers silk nanomedicines from first principles to carrier design and on to areas of future development.