Manufacturing Methodology Research Articles

Liposomal Nω-hydroxy-l-norarginine, a proof-of-concept: arginase inhibitors can be incorporated in liposomes while retaining their therapeutic activity ex vivo

Cancer immunotherapy has evolved significantly over the last decade, with therapeutics targeting the adaptive immune system showing exciting effects in clinics. Yet, the modulation of the innate immune system, particularly the tumor-associated innate immune cells which are an integral part of immune responses in cancer, remains less understood. The arginase 1 (Arg1) pathway is a pivotal metabolic pathway that tumor-associated innate immune cells exploit to create an immunosuppressive tumor microenvironment, leading to the evasion of immune surveillance. The inhibition of Arg1 presents a therapeutic opportunity to reverse this immunosuppression, and Nω-hydroxy-l-norarginine (nor-NOHA) has emerged as a potent arginase inhibitor with promising in vivo efficacy. However, the rapid systemic clearance of nor-NOHA poses a significant challenge for its therapeutic application. This study pioneers the encapsulation of nor-NOHA in liposomes, aiming to enhance its bioavailability and prolong its inhibitory activity against Arg1. Historically, the extensive interaction between innate immune cells and nanoparticles has been one of the biggest drawbacks in nanomedicine. Here we seek to utilize this effect and deliver liposomal nor-NOHA to the arginase 1 expressing innate immune cells. We systematically investigated the effect of lipid composition, acyl chain length, manufacturing and loading methodology on the encapsulation efficiency (EE%) and release profile of nor-NOHA. Our results indicate that while the manufacturing method and lipid acyl chain length do not significantly impact EE%, they crucially influence the release kinetics of nor-NOHA, with longer acyl chains demonstrating a more sustained release of nor-NOHA from liposomes enabling continuous inhibition of Arg1. Our findings suggest that liposomal nor-NOHA retains its functional inhibitory activity and could offer improved pharmacokinetic properties, making it a compelling base for iterations for further innovative cancer immunotherapeutic strategies in preclinical and clinical evaluations.

Deformation Evolution and Perceptual Prediction for Additive Manufacturing of Lightweight Composite Driven by Hybrid Digital Twins

This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins (HDT). In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering, the HDT meaning hybridization of physical and digital domains, including deformation and energy efficiency can be built, where the essential parameters can be perceptually predicted in advance, by virtue of the fusion of physical sensors and digital information. The long short term memory (LSTM) can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks, thereby laying a foundation for the HDT. The diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service simulation. The effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional accuracy. The manufacturing efficiency and comprehensive costs are accounted as consideration factors, which are perceptually predicted via LSTM. The designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process simulation. The physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling (FDM). The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction outcomes. The dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine (CMM) and 3D optical scanner. The proposed method demonstrates effectiveness in improving manufacturing quality and accurately predicting energy consumption, which have been verified with a three-way solenoid valve element, in which the maximum deformation was reduced by 39.78% and the mean absolute percentage error for perceptual prediction was 3.76%.

Manufacturing, Processing, and Characterization of Self-Expanding Metallic Stents: A Comprehensive Review.

This paper aims to review the State of the Art in metal self-expanding stents made from nitinol (NiTi), showing shape memory and superelastic behaviors, to identify the challenges and the opportunities for improving patient outcomes. A significant contribution of this paper is its extensive coverage of multidisciplinary aspects, including design, simulation, materials development, manufacturing, bio/hemocompatibility, biomechanics, biomimicry, patency, and testing methodologies. Additionally, the paper offers in-depth insights into the latest practices and emerging trends, with a special emphasis on the transformative potential of additive manufacturing techniques in the development of metal stents. By consolidating existing knowledge and highlighting areas for future innovation, this review provides a valuable roadmap for advancing nitinol stents.

Investigation of hot deformation behavior and three-roll skew rolling process for hollow stepped shaft of Al–Zn–Mg–Cu alloy

The increasing demand for high-strength lightweight hollow shafts in transportation highlights the need for advanced fabrication techniques. Al–Zn–Mg–Cu alloys, noted for their superior properties, are selected for three-roll skew rolling (TRSR). In TRSR, the material undergoes combined axial tensile and radial compressive stresses. This study evaluates the feasibility of TRSR for producing high-strength lightweight hollow stepped shafts from Al–Zn–Mg–Cu alloy. An integrated approach, including constitutive modeling, hot processing map development, and TRSR numerical simulations/experiments, is employed to optimize the TRSR forming process. The constitutive model was established based on 300°C–450 °C & 0.01–10 s−1 hot compression and 350°C–430 °C & 0.1–5 s−1 high-temperature tensile test data. The established Johnson-Cook optimization by genetic algorithms (GA-JC) model and unified viscoplastic constitutive model, accurately capture the alloy's hot deformation behavior, exhibiting minimal average absolute relative errors (AARE) of 5.431% and 5.808%, respectively. Microstructure evolution analyses shed light on the predominant softening mechanisms, emphasizing dynamic recovery (DRV) at elevated strain rates and diminishing texture intensity with escalating deformation temperatures. The composite hot processing map delineates optimal process parameters (400°C–450 °C & 0.1s−1-1s−1), facilitating informed decision-making in manufacturing practices. The validation of numerical simulations through TRSR forming experiments with initial temperature of 450 °C for the billet and axial moving speed of 10 mm/s for the chuck in affirms the feasibility of producing hollow stepped shafts from high-strength Al–Zn–Mg–Cu alloy. Close agreement was found between simulated and experimental wall thickness variations. This study enhances understanding and optimization of TRSR forming for high-strength lightweight alloys, advancing industrial manufacturing methodologies.

Integrating smart manufacturing techniques into undergraduate education: A case study with heat exchanger

The process systems domain is undergoing the fourth industrial revolution, which is helping industries digitize and optimize their production techniques. Concurrently, the field of data-based modeling has been expanding, leading to the proposal of many fault detection models. However, the rapid expansion has created gaps in the field. For instance, Smart Manufacturing (SM) methodologies have yet to be incorporated into undergraduate chemical engineering education. Additionally, only a few developed fault detection models have been deployed for real-time usage and practical applications. This study takes a crucial step toward bridging the two mentioned gaps by enabling undergraduate students to learn SM techniques and developing a safe and controlled academic environment for deploying fault detection models. The demonstration is implemented on a shell and tube heat exchanger, taught in a senior year laboratory course, using the Smart Manufacturing Innovation Platform (SMIP). The implementation provides an easily customizable pipeline for SM applications involving human-in-the-loop decision-making on a real-life hardware system. Actual data from heat exchanger equipment is used to train and compare the performances of several state-of-the-art fault detection models, including fully connected, convolutional, and recurrent neural networks. Current work also presents tutorials on deploying models for practical real-time applications using the SMIP. The overall architecture is a plug-and-play package that will motivate students to learn about SM and catalyze their interest in developing and deploying fault detection models using real-world data.

A highly responsive and sensitive flexible strain sensor with conductive cross-linked network by laser direct writing

As a critical component of wearable electronic devices, flexible strain sensors have made significant contributions in the fields of smart healthcare, motion monitoring and communication, garnering escalating research interests. However, the pursuit of ideal materials synergizing high sensitivity with facile and cost-effective manufacturing methodologies remains a persistent challenge, significantly hindering the full realization of the potential of flexible strain sensors. Herein, an innovative hybrid conductive network architecture constituted by multi-walled carbon nanotubes and laser-induced graphene (MWCNTs/LIG) has been explored via a facile, cost-effective, controllable, and environmentally friendly laser direct writing (LDW) technique. Subsequently, the resultant MWCNTs/LIG composite with a cross-linked microstructure has been harnessed for the fabrication of a high-performance strain sensor. Notably, the proposed sensor exhibits remarkable sensitivity with a gauge factor (GF) reaching 192, rapid response and recovery times of 27/20 ms, and favorable durability exceeding 2300 cycles. Furthermore, the developed sensor demonstrates the capability to accurately capture full-range motions in real-time, as well as the ability to transmit information as a portable communication device. This promising discovery offers a new insight for the flourishing development of high-performance flexible strain sensors in the realm of wearable sensing.

Engineering the Crystalline Architecture for Enhanced Properties in Fast-Rate Processing of Poly(ether ether ketone) (PEEK) Nanocomposites.

Rapid cooling in fast-rate manufacturing processes such as additive manufacturing and stamp forming limits the development of crystallinity in semicrystalline polymer nanocomposites and, therefore, potential improvements in the mechanical performance. While the nucleation, chain mobility, and crystallization time from rapid cooling are known competing mechanisms in crystallization, herein we elucidate that the crystalline morphology and architecture also play a key role in tuning the mechanical performance. We explore how modifying the spherulite morphology via a cellulose nanocrystal (CNC) and graphene nanoplatelet (GNP) hybrid system in their pristine form can improve or preserve the mechanical properties of poly(ether ether ketone) (PEEK) nanocomposites under two extreme cooling rates (fast -460 °C/min and slow -0.7 °C/min). A scalable manufacturing methodology using water as the medium to disperse the powder system was developed, employing a CNC as a dispersing agent and stabilizer for PEEK and GNP. Despite the expected limited mechanical reinforcement due to thermal degradation, CNCs significantly impacted PEEK's crystalline architecture and mechanical performance, suggesting that surface interactions via lattice matching with PEEK's (200) crystallographic plane play a critical role in engineering the microstructure. In fast cooling, the CNC and CNC:GNP systems reduced the crystallinity, respectively, yet led to minimizing the reduction in the tensile strength and maintaining the tensile modulus at the Neat level in slow cooling. With slow cooling, crystallinity remained relatively unchanged; however, the addition of CNC:GNP improved the strength and modulus by ∼10% and ∼16%, respectively. These findings demonstrate that a hybrid nanomaterial system can tailor PEEK's crystalline microstructure, thus presenting a promising approach for enhancing the mechanical properties of PEEK nanocomposites in fast-rate processes.

An Improvement of Hand Press Machine by Design for Manufacturing and Assembly (DFMA) Methodology

This research consists of the analysis of hand press machine selected using the Design for Manufacturing and Assembly (DFMA) method. DFMA is a method that combines both Design for Manufacturing (DFM) and Design for Assembly (DFA) techniques. It has the purpose to make improvements on the existing product by implementing DFMA to reduce number of components, time, and cost. The combination of hand press machine and a die cutting tool has been an effective tool to produce and replicate identical designs in the shortest time. The main objective of this research is to develop a Hand Press Machine that exhibits superior design efficiency and reduced manufacturing costs compared to the original design. To achieve this, the chosen existing model, the WUTA Pro Leather Cutting Machine, was remodelled using SolidWorks 2022 software. The original design of the Hand Press Machine had a design efficiency of 25.89%. However, the improved design achieved a significantly higher design efficiency of 36.56%, representing an increase of 10.67%. To attain this improvement, four modifications were implemented. One notable achievement in the improved design was a reduction in the total number of parts. The original design comprised 52 parts, whereas the improved design successfully reduced this to 34 parts, resulting in a reduction of 18 parts. The cost analysis, based on total absorption cost, revealed that the manufacturing cost of the original design was estimated at $362.01 for 18 manufactured parts. In contrast, the improved design was able to achieve a cost reduction, with an estimated manufacturing cost of around $339.16 for 16 manufactured parts. This indicates a cost reduction of $22.85 between the two models.

3D volume construction methodology for cold spray additive manufacturing

Cold spraying has proved as an attractive and rapidly developing solid-state material deposition process that allows for fast formation of high quality, large 3D volume objects. Low risks of undesirable heat effects lead to increased interest in cold spraying based rapid additive manufacturing. However, by continuous powder spraying and high-pressure gas operation, cold spray additive manufacturing in terms of shape building is sensitive to operating parameters and imposes high requirements on the control of process conditions and locally needed kinematics. Every step of the manufacturing process therefore needs to be meticulously conceived and planned, especially the toolpath planning and implementation. This is not only essential to meet basic performance requirements, but also needed for the desired geometric accuracy. To address these needs, this study presents a new implementation method for cold spray additive manufacturing to improve manufacturing accuracy and flexibility. The workflow and principles of the proposed method are explained and strategies are presented for building up various component types, including rotational geometries as well as freestanding parts. The developed algorithms for 3D applications can be well integrated into the cold spray additive manufacturing process for toolpath planning and path parameter determination. Reliable and accurate robot programs were developed to make the process easy to repeat and to follow. Toolpath planning and robot programming are supported and performed by applying virtual cells to simulate the automation process for the real scenario. Path parameter adjustment and kinematic optimization can then be conducted according to the feedback from the simulation result. Applied benchmarking tests prove acceptable shape accuracy and demonstrate that the current method can enhance the capabilities of cold spray additive manufacturing for near-net shape construction. This implies that careful planning and manufacturing strategies should enable overcoming the challenges associated with cold spray additive manufacturing.

Rapid Production Nasal Osteotomy Simulators With Multi-Modality Manufacturing: 3D Printing, Casting, and Molding.

To expand and improve upon previously described nasal osteotomy models with the goals of decreasing cost and production time while ensuring model fidelity. To assess change in participant confidence in their understanding of and ability to perform nasal osteotomies following completion of the simulation course. Prospective study. Simulation training course for otolaryngology residents at West Virginia University. A combined methodology of 3D printing, silicone molding, and resin casting was used to design a nasal osteotomy model to address material issues such as print delamination. Multiple models were then used in a simulation lab on performing nasal osteotomies. Model utility and impact on participant confidence was assessed at baseline, postlecture, and postsimulation lab. Using a combined manufacturing methodology, we achieved a production time reduction of 97.71% and a cost reduction of 82.02% for this polyurethane resin nasal osteotomy model relative to a previously described osteotomy model. Participants in the simulation course were noted to have a significant improvement in confidence in their understanding of and ability to perform nasal osteotomies from baseline and postlecture and also from postlecture and postsimulation lab (P < .05 for all). By incorporating multiple manufacturing modalities (molding and casting) in addition to 3D printing, this study achieved a large reduction in both production time and cost in fabrication of a nasal osteotomy simulator and addressed material limitations imposed by fused deposition modelingprinters. This design methodology serves as an example on how these barriers may be addressed in unrelated simulation projects. Model fidelity was improved with addition of a silicone soft tissue midface. Improvement in participant confidence was noted following completion of the simulation lab.

3D-printed topological-structured electrodes with exceptional mechanical properties for high-performance flexible Li-ion batteries

A vital aspect in advancing flexible batteries is the development of flexible electrodes capable of enduring repeated stretching while upholding satisfactory electrochemical performance. Thus, adopting a systematic and efficient approach to structural design and fabrication becomes imperative. In this study, we introduce an optimal structural design achieved through topology optimization and fabricate flexible electrodes via 3D printing, representing a departure from traditional design and manufacture methodologies in the development of flexible electrodes for batteries. Our research underscores the impressive mechanical strength of these topologically-structured electrodes (TSEs), validated through rigorous finite element analysis (FEA) and tensile strength testing. The results of both the stretch deformation and twist deformation analysis on the TSEs and the conventional mesh-structured electrodes (MSEs) show that the peak strain and stress of TSEs are much lower than those of MSEs. Notably, even under 50 % stretching, the TSEs maintain structural integrity, contrasting sharply with conventional mesh-structured electrodes (MSEs) and flat film electrodes which often crack under similar conditions. Moreover, after enduring 50 cycles of stretching, the TSEs retain an outstanding 98 % of their original capacity, surpassing MSEs which retain only 80 % of their capacity. These findings highlight the significant potential of topologically designed flexible electrodes, offering promising avenues for the development of stretchable and flexible energy storage devices such as wearable tech and bio-integrated electronics.

The impact of functional and service quality on perceived security in manufacturing and telecommunication services

PurposeThis research deals with the critical factors of quality and their significance to perceived security as an effort to build a formidable loyalty of customers in a technology driven service environment. The primary purpose of this study is to investigate the key contributing elements of functional and service quality on perceived security and to further analyze its impact on customer satisfaction and loyalty.Design/methodology/approachA hypothesized structure model is proposed and justified using the data collected in the manufacturing and telecommunication service sectors in South Korea through survey with total 647 respondents. To clarify the reliability of model and validity of the proposed hypothesis, AMOS 24.0 software was utilized. Furthermore, two moderating variables were adopted for the depth understanding.FindingsThis study reveals that service quality dominantly influences the level of perceived security due to its characteristics that are mostly formed on the stage of customer-contact activity. This study further provides a strategic methodology for manufacturing and telecommunication firms to foster sustainable growth by focusing on perceived security during the service delivery process.Originality/valueThis finding is particularly important as Ontact technology becomes increasingly critical during the COVID-19 pandemic. It is worthwhile noting that the research outcome of this study may, in turn, trigger the trust issue that need to be combined with quality in the era of Industry 4.0.

Adaptive Critic Design for Event-Triggered Tracking Control in Discrete-Time on Linear Systems with Observers

This research pioneers an innovative methodology for the bespoke manufacturing of SquidSkin safety products, meticulously tailored to the distinct requisites of diverse industries encompassing medical, military, and defense sectors. The triple DES algorithm is a three instance of DES on same plain text in blocks of 64 bits and converts them to cipher text using keys of 168 bits. The triple DES encryption process creates cipher text, which is an unreadable, effectively indecipherable conversion of plaintext data, the version of information that humans can read and understand. The output of the encryption process, the triple DES cipher text, cannot be read until a secret triple DES key is used to decrypt it. The delineation of industry- specific manufacturing parameters mandates a nuanced approach to material composition and production processes, culminating in a paradigmatic advancement in safety product customization. Integral to this methodology is a rigorous analysis of industry-specific requirements, guiding the selection of optimal material compositions. This selection is underpinned by a meticulously designed material testing phase, ensuring adherence to exacting industry standards and performance benchmarks. Augmenting this paradigm is an imperative emphasis on fortifying the security framework underpinning the handling of proprietary manufacturing data. The proposal introduces an advanced cryptographic architecture, featuring encryption and decryption protocols. Approach assures heightened efficiency, unwavering reliability, and the preservation of proprietary information across varied industry sectors.

The European Union's Ecodesign Directive – Analysis of Carbon Footprint Assessment Methodology and Implications for Photovoltaic Module Manufacturers

With an increasing shift away from fossil fuels toward renewable energy sources within the European Union (EU), photovoltaics (PV) are projected to see substantial growth with estimates of nearly 600 GWp of capacity by 2030. As the use of PV technology continues to expand, the European Commission has introduced various policy instruments, enabling consumers to make informed choices. Among those, the Ecodesign directive 2009/125/EC sets a carbon footprint threshold as a minimum qualification for the European market to cut out the least sustainable PV modules. For this directive, the methodological guidelines for the complex carbon footprint calculation of PV modules are under development. To this end, this analysis compares the two methodologies, namely Electronic Product Environmental Assessment Tool (EPEAT) and the Ecodesign adaptation of Product Environmental Footprint Category Rules (PEFCR), emphasizing the implications of choosing one over the other for the PV industry. This study illustrates how varying parameters, like module lifetime, degradation rate, and purchased renewable electricity certificate allowance limit, stemming from the differing methodological approaches can influence the carbon footprint calculation. Apart from the strengths and weaknesses of each methodology, this article emphasizes the need for globally harmonized standards to ensure consistency in evaluating the carbon footprint of PV modules. The observations made in this study should be considered not just for Ecodesign directive but for any such market regulation policy like the recently passed EU Net Zero Industry Act or the EU Ecolabel for PV modules. It underlines the significance of choosing a transparent and fair approach to ensure the credibility of carbon footprint labels and meet the EU's decarbonization objectives successfully, propelling the transition toward a more sustainable energy landscape.

Tailoring surface roughness through the temporal variation of additive manufacturing process parameters

The benefits that additive manufacturing (AM) offers to the industry are generally well understood and appreciated. However, the current design for additive manufacturing (DfAM) methodologies and computer-aided manufacturing (CAM) packages neglect to exploit the full potential that AM can offer through its unique ability to vary material characteristics whilst the final component geometry is being formed. The purpose of this research is to demonstrate that additional design control can be gained through temporal DfAM (TDfAM). In this study, the ability to tailor the surface roughness of fused deposition modelling (FDM) AM polylactic acid (PLA) parts through the variation of two process parameters, nozzle temperature and print speed, is explored. The underpinning hypothesis is that variation of temperature and printing speed, can provide a significant change of surface roughness within one homogeneous part. This research demonstrated that nozzle temperature and print speed have a statistically significant effect on the surface roughness of the top and side surfaces. By increasing temperature and speed, the roughness of the side surfaces decreased and the roughness of the top surface increased. Furthermore, the in-silico implementation of TDfAM is demonstrated. As such, the research supports the hypothesis that TDfAM can enable additional control over the surface characteristics of a homogeneous part.

A design and manufacturing methodology for encoded soft-textile robots

A design and manufacturing methodology for encoded soft-textile robots

Improvement of transportation system through the Lean methodology application with the purpose of mitigating environmental impacts at the U.M. SUMMA GOLD CORPORATION [Mejora del sistema de transporte a través de la aplicación de la metodología Lean con el propósito de mitigar los impactos ambientales en la U.M. SUMMA GOLD CORPORATION

The purpose of this evaluation is to determine to what extent the improvement of the transportation process based on the Lean methodology reduces environmental impacts at the SUMMA GOLD Unit. The main focus of the analysis of this research is to know, define, measure and minimize the causes of errors generated in the material transportation process in a mining unit, which in turn identifies and reduces negative environmental impacts. This evaluation is carried out using the approach of the DMAIC tool (Define, Measure, Analyze, Improve and Control), which offers a solid structure for problem solving and goes hand in hand with the Lean Manufacturing methodology. The application of the Lean methodology and the proposal to improve a technological tool managed to increase the transportation performance of each area, from 19.95% to 31.32%, obtaining as a variation 11% improvement; This increases the amount of ore produced by 3094 on average per trip. It also allows increasing the fuel use cost reduction rate from 25% to 54.91%, obtaining an improvement of 30% which translates into a reduction of 1.9 gallons per hour with a decrease in costs of S/5,616.1.

3D Printing Technology: Role in Safeguarding Food Security.

The rising threats to food security include several factors, such as population growth, low agricultural investment, and poor distribution systems. Consequently, food insecurity results from a confluence of issues, including diseases, processing limitations, and distribution deficiencies. Food insecurity usually occurs in vulnerable areas where certain technologies and traditional food safety testing are not a viable solution for foodborne disease detection. In this regard, 3D printing technologies and 3D printed sensors open the platform to produce portable, accurate, and low-cost sensors that address the gaps and challenges in food security. In this paper, we discuss the perspective role of 3D printed sensors in food security in terms of food safety and food quality monitoring to provide reliable access to nutritious, affordable food. In each section, we highlight the advantages of 3D printing technology in terms of cost-effectiveness, accuracy, accessibility, and reproducibility compared to traditional manufacturing methodologies. Recent developments in robotic technologies for mechanization, such as food handling with soft grippers, are also discussed. Lastly, we delve into the applications of advanced 3D printing technologies in agricultural monitoring, particularly the future of plant wearables, environmental sensing, and overall plant health monitoring.

Theory of constraints in healthcare: a systematic literature review

PurposeTheory of Constraints (TOC), though a well-established process improvement methodology in manufacturing, is still a novel philosophy for healthcare and an exhaustive review of literature is needed to summarize the key findings of various researchers. Such a review can provide a direction to the researchers and academicians interested in exploring the application of TOC in the healthcare sector. This paper aims to review the existing literature of TOC tools and techniques applied to the healthcare environment, and to investigate motivating factors, benefits and key gaps for identifying directions for future research in the domain of healthcare.Design/methodology/approachIn this paper, different electronic repositories were searched using multiple keywords. The current study identified 36 articles published between January 1999 to mid-2021 to conceptualize and summarize the research questions used in the study. Descriptive analysis along with pictorial representations have been used for better visualization of work.FindingsThis paper presents a thorough literature review of TOC in healthcare and identifies the evolution, current trends, tools used, nature of services chosen for application and research gaps and recommends future direction for research. A variety of motivating factors and benefits of TOC in healthcare are identified. Another key finding of this study is that almost all implementations listed in literature reported positive outcomes and substantial improvements in the performance of the healthcare unit chosen for study.Practical implicationsThis paper provides valuable insight to researchers, practitioners and policymakers on the potential of TOC to improve quality of services, flow of patients, revenues, process efficiency and cost reduction in different health care settings. A number of findings and suggestions compiled in the paper from literature study can be used for diagnosing, learning and making substantial changes in healthcare. The methodologies used by different researchers were analysed and combined to propose a generic step by step procedure to apply TOC. This methodology will guide the practising managers about the appropriate tools of TOC for their specific need.Social implicationsGood health is always the first desire of all men and women around the globe. The global aim of healthcare is to quickly cure more patients and ensure healthier population both today and in future. This article will work as a foundation for future applications of TOC in healthcare and guide upcoming applications in the booming healthcare sector. The paper will help the healthcare managers in serving a greater number of patients with limited available resources.Originality/valueThis paper provides original collaborative work compiled by the authors. Since no comprehensive systematic review of TOC in healthcare has been reported earlier, this study would be a valuable asset for researchers in this field. A model has been presented that links various benefits with one another and clarifies the need to focus on process improvement which naturally results in these benefits. Similarly, a model has been presented to guide the users in implementation of TOC in healthcare.

Interlayer mechanical performance of 3D-printed cementitious systems: A comprehensive study on operational and material parameters

This study delves into the interlayer mechanical performance of 3D-printed cementitious materials, exploring a variety of operational and material parameters to understand the practical effects on the performance of printed structures. To achieve this, a comprehensive battery of tests, encompassing compression, triplet shear, direct tensile, and diagonal tension tests, was conducted. Within the scope of this investigation, the anisotropic performance in perpendicular, lateral, and parallel directions was examined, along with varying printing time intervals (0, 15, 30, and 60 min between consecutive layers), material aging times (0, 30, and 60 min), and different manufacturing methodologies, including cast, horizontal-printed, and vertical-printed specimens. The research findings indicate that well-established mechanical tests, commonly utilized for evaluating masonry structures, can be effectively transferred and applied to assess 3D printed structures. A noteworthy discovery is the anisotropic behavior observed in compressive strength, characterized by diminishing results from perpendicular to parallel and parallel to lateral loading directions. Extended printing time intervals have an adverse impact on the interlayer mechanical performance of cementitious systems. Material aging time also significantly influences bond strength, particularly in mixtures aged for 60 min. In conclusion, it is evident that material aging exerts a more substantial influence on bond strength compared to printing time intervals in cementitious systems. Additionally, it was observed that vertically printed specimens replicate the mechanical performance and fracture mechanism of cast specimens, while horizontally printed specimens exhibit slightly lower performance with distinct fracture patterns.