Minimum Manufacturing Cost Research Articles

Robust and repairable PET superwicking surfaces: A simple two-step fabrication approach for enhanced liquid transport

Superwicking surfaces stand out for their superior wicking abilities that expedite liquid flow across their structural form. The surface has attracted significant attention due to its promising applications in water harvesting, thermal management, biomedical fields, and more. However, minimizing manufacturing costs while ensuring long-term stability remains a challenge in the production of superwicking surfaces and enhancing their applications. This study presents the development of polyethylene terephthalate (PET) superwicking surfaces using a straightforward two-step technique with sandpaper abrasion and nanocomposite coating of TiO2-SiO2. Superwicking performance was evaluated through droplet spread analysis, contact angle measurements, and water drying tests. Results exhibited a more than 100% rise in absorbed water film thickness on the 180-grit abraded superwicking surface versus the coating on raw PET. Additionally, a 10μl droplet displayed more than triple the spreading diameter. Sandpaper abrasion, high-pressure water impact, and outdoor stability tests appraised surface durability. The PET superwicking surface showed enhanced mechanical durability and outdoor stability, attributed to protective microgrooves and photocatalytic self-cleaning capacity. The findings of this study clearly address the high cost, instability, and extreme lack of durability associated with conventional superwicking surface preparation. More importantly, the developed self-repairing capability of the surface allows it to be restored by reapplying the spray coating after the nanoparticles have been worn away due to heavy use. This advancement will significantly promote the use of such surfaces in heat transfer and self-cleaning applications.

An artificial intelligence-based optimization framework for the optimal composition and thermomechanical processing schedule for specialized micro-alloyed multiphase steels

An artificial intelligence-based heuristic approach is presented to optimize the chemical composition and the thermomechanical processing schedule to obtain specialized micro-alloyed multiphase steels with desired mechanical properties, at minimal manufacturing cost. The optimization framework uses a modified form of genetic algorithm, called the micro-genetic algorithm (μGA), that uses a penalty-based cost function formulation operating on a multi-dimensional search space spanning 15 alloying elements, an average cooling temperature, an austenitizing temperature and eight time–temperature points from the cooling profiles of multiphase steels. With superior search speed and convergence rates to the traditional genetic algorithm, μGA uses a neural network-based reduced-order model to predict hardness. Additional correlation equations are used to determine the corresponding tensile strength and elongation. Microstructural analysis was performed using neurocomputing techniques to further validate the accuracy of the algorithm. The entire computational framework was validated using data from the literature, establishing its utility in steel design.

More is better? The role of strategic data management in a lean manufacturing process

Purpose Lean manufacturing has been pivotal in emphasizing the reduction of cycle times, minimizing manufacturing costs and diminishing inventories. This research endeavors to formulate a lean data management paradigm, through the design and execution of a strategic edge-cloud data governance approach. This study aims to discern anomalous or unforeseen patterns within data sets, enabling an efficacious examination of product shortcomings within manufacturing processes, while concurrently minimizing the redundancy associated with the storage, access and processing of nonvalue-adding data. Design/methodology/approach Adopting a lean data management framework within both edge and cloud computing contexts, this study ensures the preservation of significant time series sequences, while ascertaining the optimal quantity of normal time series data to retain. The efficacy of detected anomalous patterns, both at the edge and in the cloud, is assessed. A comparative analysis between traditional data management practices and the strategic edge-cloud data governance approach facilitates an exploration into the equilibrium between anomaly detection and space conservation in cloud environments for aggregated data analysis. Findings Evaluation of the proposed framework through a real-world inspection case study revealed its capability to navigate alternative strategies for harmonizing anomaly detection with data storage efficiency in cloud-based analysis. Contrary to the conventional belief that retaining comprehensive data in the cloud maximizes anomaly detection rates, our findings suggest that a strategic edge-cloud data governance model, which retains a specific subset of normal data, can achieve comparable or superior accuracy with less normal data relative to traditional methods. This approach further demonstrates enhanced space efficiency and mitigates various forms of waste, including temporal delays, storage of noncontributory normal data, costs associated with the analysis of such data and excess data transmission. Originality/value By treating inspected normal data as nonvalue-added, this study probes the intricacies of maintaining an optimal balance of such data in light of anomaly detection performance from aggregated data sets. Our proposed methodology augments existing research by integrating a strategic edge-cloud data governance model within a lean data analytical framework, thereby ensuring the retention of adequate data for effective anomaly detection.

Deposition and structural investigation of uniform AlN(100) films at wafer scale through RF magnetron sputtering

a-axis-oriented AlN(100) films are identified as promising candidates for surface acoustic wave devices owing to their high transversal-acoustic velocity. Achieving uniform films across a wafer scale is crucial for enhancing device performance and minimizing manufacturing costs. In this study, we employ radio-frequency magnetron sputtering to deposit AlN(100) films on 2-in Si(100) wafers. We further examine the influence of various process parameters on the nonuniformity of film thickness and structural properties, including crystallite size, microstrain, and dislocation density. The optimization of parameters leads to the selection of a gas flow ratio of N2:Ar = 4:7, a sputtering power of 160 W, and a substrate temperature of 350 °C. Under these optimized conditions, the AlN films not only demonstrate a preferred (100) orientation and remarkable crystallinity, as indicated by a full width at half maximum of the X-ray diffraction peak of just 0.03°, but also achieve an optimal film thickness nonuniformity of 1.66 %. Our results offer valuable insights for the wafer-scale fabrication of AlN(100) films, potentially enhancing industrial production yields and reducing costs.

Development of flexible and sustainable all quasi-solid-state supercapacitors based on ecofriendly binders on aluminum foil

Since the beginning of the 21st century, ecological, light weight and low-cost power sources devices with excellent mechanical flexibility are crucial to fulfill the requirements of emerging technologies for the new generation, including robots, foldable phones and wearable electronics. Herein, we report the integration of eco-friendly and biocompatible binders Polyvinyl alcohol (PVA) and Pullulan (Pu) for the straightforward manufacturing of flexible and sustainable carbon-based electrodes for supercapacitors applications. Furthermore, Glycerol (GCy) has been employed as a dual-purpose plasticizer agent for both electrode and electrolyte preparation, thereby minimizing manufacturing costs. Firstly, GCy content influence on the electrochemical performances and PVA-GCy/KOH films quality was investigated. Pullulan/Activated Carbon (Pu/AC) based supercapacitors have shown superior energetic performances in contrast to those achieved by the PVA/AC based ones. The Pu-based device exhibited a maximum aerial capacitance of 155 mF cm−2 at 5 mV s−1, and a maximum energy and power densities of 31.8 μWh cm−2 and 34.3 mW cm−2 respectively at 0.1 A g−1. Furthermore, the device showed excellent stability behavior (>91 % of its initial capacitance after 9000 cycles). More importantly, the fabricated supercapacitor presented acceptable electrochemical performances when folded at different bending angles, opening the way to the practical applications of micro-storage and flexible embedded systems.

Static Performance Characteristics Of Vortex Rate Sensor

The vortex rate sensor is a fluidic gyroscope with no moving parts and can be used in very difficult conditions like radiation, high temperature and noise with minimum cost of manufacturing and maintenance. A vortex rate sensor made of wood has been designed and manufactured to study theoretically and experimentally its static performance .A rig has been built to carry out the study, the test carried out with three different air flow rates (100, 150, and 200 l/min).The results show that the relation between the differential pressure taken from the sensor pickoff points and the angular velocity of the sensor was linear.The present work involved theoretical and experimental study of vortex rate sensor static characteristics .Vortex rate sensor has been designed and manufactured with dimensions :- Radius of vortex chamber= 140 mm, Radius of sink tube rs= 4.5 mm, the pickoff hole diameter = 2mm, Height of vortex chamber b= 19 mm, Height of pickoff pipe h= 25 mm.

A bioengineered pseudovirus nanoparticle displaying SARS-CoV 2 RBD fully protects mice from mortality and weight loss caused by SARS-CoV 2 challenge.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused considerable morbidity and mortality worldwide. Although authorized COVID-19 vaccines have been shown highly effective, their significantly lower efficacy against heterologous variants, and the rapid decrease of vaccine-elicited immunity raises serious concerns, calling for improved vaccine tactics. To this end, a pseudovirus nanoparticle (PVNP) displaying the receptor binding domains (RBDs) of SARS-CoV-2 spike, named S-RBD, was generated and shown it as a promising COVID-19 vaccine candidate. The S-RBD PVNP was produced using both prokaryotic and eukaryotic systems. A 3D structural model of the S-RBD PVNPs was built based on the known structures of the S60 particle and RBDs, revealing an S60 particle-based icosahedral symmetry with multiple surface-displayed RBDs that retain authentic conformations and receptor-binding functions. The PVNP is highly immunogenic, eliciting high titers of RBD-specific IgG and neutralizing antibodies in mice. The S-RBD PVNP demonstrated exceptional protective efficacy, and fully (100%) protected K18-hACE2 mice from mortality and weight loss after a lethal SARS-CoV-2 challenge, supporting the S-RBD PVNPs as a potent COVID-19 vaccine candidate. By contrast, a PVNP displaying the N-terminal domain (NTD) of SARS-CoV-2 spike exhibited only 50% protective efficacy. Since the RBD antigens of our PVNP vaccine are adjustable as needed to address the emergence of future variants, and various S-RBD PVNPs can be combined as a cocktail vaccine for broad efficacy, these non-replicating PVNPs offer a flexible platform for a safe, effective COVID-19 vaccine with minimal manufacturing cost and time.

A framework for hybrid manufacturing cost minimization and preform design

This paper describes preform design optimization in hybrid additive-subtractive manufacturing. In hybrid manufacturing, the question of what form and what geometry the additive preform should take has largely been a matter of intuition and experience, or trial and error. The choice of a more optimal preform depends on the target parameters, such as stiffness, cost, or lead time. We demonstrate a framework for preform optimization using static stiffness, and then the combined cost of additive and subtractive manufacturing, while respecting stable cutting conditions for the tool-part combination. The procedure is illustrated by comparing three preform geometries for a thin wall.

Mass Customization of Polylactic Acid (PLA) Parts via a Hybrid Manufacturing Process.

Mass customization is the development of items tailored to specific customers, but produced at low unit cost in high-volume. In this context, hybrid manufacturing (HM) combines fused deposition modeling (FDM) and injection molding (IM) to fabricate a single personalized part with minimum manufacturing cost. In this technique, inserts with different physical features are first FDM-fabricated and then IM-overmolded. This study investigated the effect of hybrid FDM-IM production technology, FDM insert geometry on mechanical properties, and micro-structural evolution of Polylactic Acid (PLA) samples. The findings indicated a comparable tensile properties of FDM-IM samples (68.38 MPa) to IM batch (68.95 MPa), emphasizing the potential of HM in the manufacturing industry. Maximum tensile stress of FDM-IM specimens shows an upward trend due to the increased infill density of preforms. In addition, overmolding interface direction results in a big gap for the maximum tensile strengths between half-length series specimens (12.99 MPa to 19.09 MPa) and half-thickness series specimens (53.83 MPa to 59.92 MPa). Furthermore, four joint configurations resulted in different mechanical performances of finished specimens, in which the female cube sample exhibits the highest tensile stress (68.38 MPa), while the batch with male T joint shows a lower value in maximum tensile strength (59.51 MPa), exhibiting a similar tensile performance with the half-thickness 75% batch without joint configuration. This study lays the groundwork for using HM to produce bespoke and mechanically improved parts over FDM alone.

Performance Analysis, and Economic-Feasibility Evaluation of Single-Slope Single-Basin Domestic Solar Still under Different Water-Depths

The impact of single-slope solar still with and without flat-plate collector was evaluated experimentally and numerically. Experimental analysis was conducted for four different water depths (3, 6, 9, 12 cm) in on-sunshine hours between 11 AM to 5 PM in Bhopal (23.2599° N, 77.4126° E), India. The thermo efficiency was 51.31% for 3 cm water depth while 24.29% for 12 cm water depth in an active mode of operation. In the case of passive mode, the thermo efficiency was 17.02% for 3 cm water depth and 6.77% for 12 cm water depth. The average exergy efficiency of single-slope solar still is 66.60% for 3 cm depth which is higher than 12 cm depth, i.e., 23.14%. The hourly variation parameters of solar still were also calculated and analyzed. The overall results obtained in the analysis state that solar still performs effectively when coupled with a flat-plate solar collector. According to econometric evaluation, the fabrication expense of a single-slope solar-basin-still is 126.43$ whereas the cost of producing distilled water per day is 1.61$, and the payback period of a single-slope solar-basin-still with FPC is 17.53 months. In a nutshell, the single-slope solar-basin-still design is commercially viable, functional, and technically sustainable, minimizing manufacturing costs in comparison with a traditional solar still, and past findings. The proposed solar still produced remarkable results in all experimental trials.

Potential and challenges of tool condition monitoring in gear hobbing

Due to its high productivity, gear hobbing is one of the most frequently used manufacturing processes for the soft machining of cylindrical gears. One of the main objectives of an optimized manufacturing process is to maintain the required component quality while minimizing manufacturing costs. In both cases, knowledge of the tool wear is of great importance. Tool Condition Monitoring (TCM) provides a methodical approach to tracking tool wear during the process. In this report, various sensors are investigated with regard to their potential for TCM. Fly-cutting and hobbing experiments were conducted for this purpose. The signal data recorded during the tests were processed using high-pass filters, Hilbert transforms and Fast Fourier Transforms (FFT) in the time and frequency domain and evaluated according to various parameters. Based on the results, statements were made about the relationships between signal data and process conditions. For a precise evaluation of the tool condition, the combination of several sensors is necessary. In particular, the tool-side-mounted acoustic emission and acceleration sensors in combination with the power sensor and the airborne sound sensor showed increased amplitude values with increased wear. For the acceleration signals it could be shown that higher orders reacted more sensitively to increased tool wear. For the workpiece-side-mounted sensors, no meaningful results could be obtained due to the large distance to the cutting zone.

An integrated resource allocation and tolerance allocation optimization: A statistical-based dimensional tolerancing

Today's industrial world is facing rising demand for highly reliable and safe products. Complex industries, such as automobiles, medical, and aircraft, require a well-designed engineering plan which has a comprehensive understanding of the various certainties and uncertainties that occur in reality. Consequently, the need for reliable and precise parts has impacted the tolerancing activity. Key functions of complex products can often be realized by high precision part use. Thus, producers are confronted with high-quality requirements, cost pressure, and a rising number of demands. The introduction of new technologies and the need to meet the requirements have broadened the scope of tolerancing. In this paper, a statistical tolerance allocation model is developed to study the economic impact of allocated tolerances on an assembled product. The problem is aimed at optimizing the allocated tolerances to each part of the product while minimizing manufacturing costs. A modular cost model is proposed to determine the manufacturing costs related to each activity and part. The manufacturing costs include processing cost, inspection cost, scrap cost, assembly cost, and warranty cost. Furthermore, a genetic algorithm is adapted to study the applicability of the model developed on an exemplary assembled product.

Minimum Manufacturing Costs, National Prices, and Estimated Global Availability of New Repurposed Therapies for Coronavirus Disease 2019.

BackgroundCurrently, only dexamethasone, tocilizumab, and sarilumab have conclusively been shown to reduce mortality of coronavirus disease 2019 (COVID-19). Safe and effective treatments will need to be both affordable and widely available globally to be used alongside vaccination programs. This analysis will estimate and compare potential generic minimum costs of a selection of approved COVID-19 drug candidates with available international list prices.MethodsWe searched for repurposed drugs that have been approved by at least one of the World Health Organization, US Food and Drug Administration, or the United Kingdom National Institute of Health and Care Excellence organizations or at least given emergency use authorization or recommended for off-label prescription. Drug prices were searched for dexamethasone, budesonide, baricitinib, tocilizumab, casirivimab, and imdevimab, and sarilumab, using active pharmaceutical ingredients (APIs) data extracted from global shipping records. This was compared with national pricing data from a range of low-, medium-, and high-income countries. Annual API export volumes from India were used to estimate the current availability of each drug.ResultsRepurposed therapies can be generically manufactured for some treatments at very low per-course costs, ranging from US $2.58 for intravenous (IV) dexamethasone (or US $0.19 orally) and US $4.34 for inhaled budesonide. No export price data were available for baricitinib, tocilizumab, casirivimab, and imdevimab, or sarilumab, but courses of these treatments have higher prices, ranging from US $6.67 for baricitinib to US $875.5 for sarilumab. When comparing international list prices, we found wide variations between countries.ConclusionsSuccessful management of COVID-19 will require equitable access to treatment for all populations, not just those able to pay high prices. Dexamethasone and budesonide are widely available and affordable, whereas monoclonal antibodies and IV treatment courses are more expensive.

407. Minimum Manufacturing Costs, National Prices and Estimated Global Availability of New Repurposed Therapies for COVID-19

BackgroundCurrently, only dexamethasone, tocilizumab and sarilumab have conclusively been shown to reduce mortality of COVID-19. No drug for prevention or treatment in earlier stages of COVID-19 are yet found, with previously promising drugs such as hydroxychloroquine and remdesivir have been shown to be ineffective. Several new candidates are now being studied in clinical trials. Safe and effective treatments will need to be both affordable and widely available. We therefore revised our original 2020 analysis to reflect recent developments. In this update we analysed the cost of production, current national list prices, and API availability for oral and IV dexamethasone, ivermectin, colchicine, dutasteride, budesonide, baricitinib and monoclonal antibodies tocilizumab and sarilumab.MethodsCosts of production for new and potential COVID-19 drugs (dexamethasone, ivermectin, dutasteride, budesonide, baricitinib, tocilizumab, sarilumab and colchicine) were estimated using an established and published methodology based on costs of active pharmaceutical ingredients (API), extracted from the global shipping records database Panjiva. This was compared with national pricing data from low, medium, and high-income countries. Annual API export volumes from India were used to estimate the current availability of each drug.ResultsRepurposed therapies can be generically manufactured at very low per-course costs: ranging from &2.58 for IV dexamethasone (or &0.19 orally) to &0.12 for ivermectin. No export price data was available for baricitinib, tocilizumab or sarilumab. When compared against international list prices, we found wide variations between countries. Drug API availability was generally good, with colchicine being the most available with sufficient annual API exported for 59.8 million treatment courses. A summary is shown in Table 1.Table 1. Summary of list prices, estimated production costs, and current availability of potential COVID-19 drugs selected for analysis. OD = Once daily, BD = twice per day, EUA = Emergency Use Authorisation (only to be given with remdesivir) *In most recent 12-month period. ConclusionSuccessful management of COVID-19 will require equitable access to treatment for all, not just those able to pay. Repurposed drugs can be manufactured at very low costs if shown to be clinically effective, and offers an affordable, widely available option for patients at all stages of the disease from pre-exposure prophylaxis to asymptotic and mild infections, through to critical care until vaccination coverage is expanded.Disclosures All Authors: No reported disclosures

891. Minimum Manufacturing Costs and National Prices for Weight Loss Treatments, as Potential Mitigation for Anti-Retroviral Related Weight Gain in HIV

BackgroundWeight gain is being observed for a wide range of antiretroviral treatments. Weight gains are higher for people taking first-line integrase inhibitor based treatments, especially those including TAF/FTC. Weight gains are higher for women and people of colour. Clinical obesity increases the risks of cardiovascular disease, diabetes, adverse birth outcomes and could lower survival rates. Anti-obesity treatments are needed to supplement lifestyle interventions and counteract progressive weight gains, but are not routinely provided as part of HIV care.MethodsCosts of production for FDA-recommended weight loss treatments and anti-diabetic medications (orlistat, naltrexone-bupropion, topiramate, phentermine, semaglutide, liraglutide and metformin) were estimated using an established and published methodology based on costs of active pharmaceutical ingredients (API), extracted from the global shipping records database Panjiva. This was compared with national drug list price data from a range of low, medium, and high-income countries. Figure 1. Example of methodology for calculating the estimated minimum cost of production for orlistatResultsWeight loss and anti-diabetic treatments can be generically manufactured at low per-course costs, e.g. &85 per person per year for oral treatments such as orlistat and &1 per person per month for metformin. However, prices for a year of treatment with orlistat are as high as &1,205 in the USA and as low as &11 in Vietnam. In comparison, a month of ARV treatment costs about &15 via global health institutions like CHAI. Price for injectable (subcutaneous) treatments were higher, ranging from &1,985 for liraglutide in USA to &330 in Morocco, whilst they could potentially be profitably sold for &155 for a 12-week course. No export price data was available for semaglutide. When compared against international list prices, we found wide variations between countries. Table 1. Summary of drug prices and minimum cost estimates Figure 2. Orlistat course costs in a range of countries, compared with estimated minimum cost Figure 3. Liraglutide course costs in a range of countries, compared with estimated minimum costConclusionWe show that weight loss treatments can be manufactured and sold profitably for low prices, but have a wide price range between countries. Government and non-governmental healthcare systems should be evaluating weight loss agents for inclusion within ART programmes. Disclosures All Authors: No reported disclosures

Optimization for minimum manufacturing costs of tower cranes based on the plant growth simulation algorithm

Tower cranes are the most widely used lifting equipment in the construction industry. Studies on structural optimization have generally been conducted to achieve the lightest weight. Although the lighter structural weight generally brings lower manufacturing costs, the objective of minimum structural manufacturing costs for tower cranes has not been investigated extensively. In this study, a full parametric model of a tower crane was established based on the data provided by an enterprise to minimize manufacturing costs. The maximum error was within 9.5% of the actual costs for the enterprise. The main procedure was developed using the plant growth simulation algorithm (PGSA) to solve the numerical model, which requires the subprocedures of finite element analyses and manufacturing cost computations. The results showed that the optimal plan decreased the manufacturing cost of the tower crane by 15.94%, which was 2209.5 yuan lower than that of the lightest weight design.

Techno-economic evaluation for recovering phenolic compounds from acai (Euterpe oleracea) by-product by pressurized liquid extraction

Acai is one of the leading Brazilian Amazon fruits, which pulp is consumed throughout the country and exported to several others. Acai by-product represents 80–90% berry mass. In order to reuse the by-product, pressurized liquid extraction (PLE) was applied. Solvent composition and temperature were studied through their effect on the global extraction, total phenolic, reducing sugars yields, and antioxidant capacity. High temperature (115 ºC) and ethanol+water (75 wt%) favored obtaining antioxidant extracts. These PLE conditions were kinetically studied and economically evaluated. The end of the first theoretical extraction period (tCER) resulted in the extracts’ minimum cost of manufacturing (COM). Regardless of the extraction time, scale-up reduced the COM, advising the process at large scales. A sensitivity study was carried out considering different extract selling prices as scenarios. All the estimated selling prices showed encouraging economic indexes. PLE proved to be technically and economically feasible to obtain acai by-product extracts with confirmed antioxidant capacity.

Biobjective Scheduling for Joint Parallel Machines with Sequence-Dependent Setup by Taking Pareto-Based Approach

Modern factories have been moving toward just-in-time manufacturing paradigm. Optimal resource scheduling is therefore essential to minimize manufacturing cost and product delivery delay. This paper therefore focuses on scheduling multiple unrelated parallel machines, via Pareto approach. With the proposed strategy, additional realistic concerns are addressed. Particularly, contingencies regarding product dependencies as well as machine capacity and its eligibility are also considered. Provided a jobs list, each with a distinct resource work hour capacity, this novel scheduling is aimed at minimizing manufacturing costs, while maintaining the balance of machine utilization. To this end, different computational intelligence algorithms, i.e., adaptive nearest neighbour search and modified tabu search, are employed in turn and then benchmarked and validated against combinatorial mathematical baseline, on both small and large problem sets. The experiments reported herein were made on MATLAB™ software. The resultant manufacturing plans obtained by these algorithms are thoroughly assessed and discussed.

Tolerance synthesis for lost motion requirement of planetary gear train based on a mechanism model

In this paper, an original equivalent mechanism with parallel linkages is proposed for lost motion behavior analysis and tolerance synthesis of planetary gear train (PGT). The parallel linkages are equivalent in kinematics of PGT to depict the multiple branches of sun-planet-ring gears with a driving link/sun gear and an output platform/carrier, a slider-block with two strokes in the circle curve guide rail of the platform is introduced in each linkage to intuitively express the lag rotation of output platform driven by the parallel linkages under error condition, and the errors are described by the deviations of link lengths. With the mechanism model, the lost motion expression of PGT is explicitly derived and then the tolerance synthesis method is formulated to allocate the optimum tolerances for satisfying the lost motion requirement with the minimum manufacturing cost. The lost motion behavior of PGT was simulated and the tolerances of errors were allocated involving tooth thickness reduction, planet position errors and gear eccentricity errors. The lost motion tests of two PGTs with the allocated tolerances were conducted. The results well agree with the simulations’, which validated the effectiveness of the developed tolerance synthesis method by the proposed mechanism model.

Patient-specific desktop 3D-printed guides for pelvic tumour resection surgery: a precision study on cadavers

3D-printed patient-specific instruments have become a useful tool to improve accuracy in pelvic tumour resections. However, their correct placement can be challenging in some regions due to the morphology of the bone, so it is essential to be aware of the possible placement errors in each region. In this study, we characterize these errors in common pelvic osteotomies. We conducted an experiment with 9 cadaveric specimens, for which we acquired a pre-operative computed tomography scan. Small PSIs were designed for each case following a realistic surgical approach for four regions of the pelvis: iliac crest (C), supra-acetabular (S), ischial (I), and pubic (P). Final surgical placement was based on a post-operative scan. The resulting positions were compared with pre-operative planning, obtaining translations, rotations, and maximum osteotomy deviations in a local reference frame defined based on the bone's morphology. Mean translations and rotations in the direction of the osteotomy plane were as follows: C = 5.3mm, 6.7°; S = 1.8mm, 5.1°; I = 1.5mm, 3.4°; P = 1.8mm, 3.5°. Mean translations in the remaining axes were below 2mm. Maximum osteotomy deviations (75% of cases) were below 11.8mm in C (7.8mm for half-length), 7.8mm in S (5.5mm for half-length), 5.5mm in I, and 3.7mm in P. We have characterized placement errors for small PSIs in four regions of the pelvis. Our results show high errors in C and S PSIs in the direction of the resection plane's normal, and thus large osteotomy deviations. Deviations in short osteotomies in S, I and P and placement errors in the remaining directions were low. The PSIs used in this study are biocompatible and can be produced with a desktop 3D printer, thus minimizing manufacturing cost.