Minimize Production Time Research Articles

3D Printing Materials Mimicking Human Tissues after Uptake of Iodinated Contrast Agents for Anthropomorphic Radiology Phantoms.

(1) Background: 3D printable materials with accurately defined iodine content enable the development and production of radiological phantoms that simulate human tissues, including lesions after contrast administration in medical imaging with X-rays. These phantoms provide accurate, stable and reproducible models with defined iodine concentrations, and 3D printing allows maximum flexibility and minimal development and production time, allowing the simulation of anatomically correct anthropomorphic replication of lesions and the production of calibration and QA standards in a typical medical research facility. (2) Methods: Standard printing resins were doped with an iodine contrast agent and printed using a consumer 3D printer, both (resins and printer) available from major online marketplaces, to produce printed specimens with iodine contents ranging from 0 to 3.0% by weight, equivalent to 0 to 3.85% elemental iodine per volume, covering the typical levels found in patients. The printed samples were scanned in a micro-CT scanner to measure the properties of the materials in the range of the iodine concentrations used. (3) Results: Both mass density and attenuation show a linear dependence on iodine concentration (R2 = 1.00), allowing highly accurate, stable, and predictable results. (4) Conclusions: Standard 3D printing resins can be doped with liquids, avoiding the problem of sedimentation, resulting in perfectly homogeneous prints with accurate dopant content. Iodine contrast agents are perfectly suited to dope resins with appropriate iodine concentrations to radiologically mimic tissues after iodine uptake. In combination with computer-aided design, this can be used to produce printed objects with precisely defined iodine concentrations in the range of up to a few percent of elemental iodine, with high precision and anthropomorphic shapes. Applications include radiographic phantoms for detectability studies and calibration standards in projective X-ray imaging modalities, such as contrast-enhanced dual energy mammography (abbreviated CEDEM, CEDM, TICEM, or CESM depending on the equipment manufacturer), and 3-dimensional modalities like CT, including spectral and dual energy CT (DECT), and breast tomosynthesis.

Multi-Objective Particle Swarm Optimization for Al 6351-T6 Alloy CNC Turning Parameter Optimization

CNC turning is a popular machining process where material is removed from a rotating workpiece using a cutting tool. Productivity in CNC turning depends on parameters such as cutting speed, feed rate, and depth of cut. This paper presents an optimization approach using ANOVA to enhance production time, cost, and surface finish in CNC turning. The study examined the effects of cutting speed, feed rate, and depth of cut on machining Al 6351-T6 alloy. Key parameters were identified using ANOVA, and the multiobjective Particle Swarm Optimization (MOPSO) algorithm was employed to find optimal cutting conditions that minimize production time and cost while maximizing surface finish. A manufacturing time of 593.19 minutes, a manufacturing cost of Rs. 47.69, and a surface finish of 1.16 µm were achieved with the optimized parameters that included a feed rate of 0.107 mm/rev, cutting speed of 82 m/min, and depth of cut of 1.4 mm. This approach can significantly enhance CNC turning efficiency and reduce costs in manufacturing.

Production risk analysis and prioritization in manufacturing industry: A hybrid approach using Monte Carlo simulation and DEMATEL analysis

Risk identification and prioritization in production sector is critical if an enterprise wishes to compete successfully. To achieve this, Delphi technique was utilized to finalize 36 identified risks in a ‘metal plate production’ stage prior to risk analysis through risk probability and its impact. Risk prioritization is performed by Monte Carlo Simulation (MCS) and Decision Making and Trial Evaluation Laboratory (DEMATEL) analysis. The novelty of this study is to develop an effective hybrid approach by utilizing strengths of MCS (with iterations in thousands on the simulation) as well as DEMATEL analysis (to assess the causal relationship among risk factors). A more accurate risk identification by developing a consolidated list of risks in one of the important production stages followed by an efficient prioritization of interacting (process and product related) risks will help the shop floor operator making better decisions to enhance the quality by minimizing production time and cost.

Product design of upper sandal fabric cutting machine using ergonomic function deployment method

In the production process, the upper sandal cutting of KUB Mampu Jaya is still done manually using scissors one by one for each mold. The purpose of this research is to create an ergonomic upper sandal cutting machine. The method used in this research is Ergonomic Function Deployment (EFD). Direct data collection involved observing the production stages and activities carried out by workers through interviews and surveys. The results show that this sandal upper cutting machine has been designed by adjusting user needs so as to minimize production time and the cutting process becomes more efficient. Previously, the production or cutting time took 2 minutes per one upper sandal mold, but with this new cutting machine, the cutting process only takes 1 minute per upper sandal mold, saving up to 1 minute. The results of this study will provide a better solution in designing a sandal upper fabric cutting machine that prioritizes ergonomic aspects and can reduce musculoskeletal complaints.

Identification and Minimization of Waste with the Application of Lean Manufacturing in the Cireng Production Process at PT Brecxelle Berkah Uniti

Based on the results of observations and the 7 waste questionnaires at PT Brecxelle Berkah Uniti production, it was found that the waste of defects occurs such as cireng are shapeless, destroyed, and do not pass through the metal detector machine. Waste of waiting occurs during the cooling process, when starting the engine, and waiting for the pressing process. Waste of transportation occurs due to circular and non-consecutive process flows. This research aims to minimize production time and increase production result by simulating the cireng production process of PT Brecxelle Berkah Uniti using the Lean Manufacturing and System Simulation method. Based on the simulation results with the proposed improvements, the results obtained from the simulation were that the total production lead time was reduced by 10,97 minutes from 40.45 minutes to 29,48 minutes. The NVA and NNVA time on FVSM also decreased by 10.81 minutes from the activity time on CVSM. Based on the simulation results, production results increased by 80% after the proposed improvements, from 4,671,945 pcs per month to 8.429.679 pcs per month.

RESEARCH OF PROPERTIES OF CERAMIC COMPOSITE FIBER PRINTED USING FUSED DEPOSITION MODELING TECHNOLOGY

This research article presents a comprehensive study on ceramic materials using Fused filament fabrication of ceramic (FFFC) for the production of test samples. The study investigates the effects of different production strategies on three types of ceramic materials: experimental ceramic composite fiber (e.c.c.f.)(composite material produced by STU FCHPT), Zirconium Silicate, and White Zirconia. The primary objective is to compare the production times of the different strategies and investigate their effects on the properties of the samples. This research is important because production time is a crucial factor in the manufacturing industry, and minimizing production time without compromising quality is essential. The study aims to explore the impact of various production strategies on the production time and properties of the test samples, such as hardness, porosity, and flexural strength. The experimental procedure involves printing test samples using a MakerBot METHOD X 3D Printer with FDM technology and varying the layer thickness, raster angle, infill density, and other production strategies. The study aims to identify the optimal production strategy for each ceramic material, which can significantly reduce production time while maintaining the desired quality of the parts. Overall, the research provides valuable insights into the optimal production strategies for different types of ceramic materials and contributes to the development of novel, cost-effective, and efficient manufacturing processes for ceramic composites.

The Benefits of using Computerized system over Manual System in Apparel Production

Bangladesh's clothing industry is the backbone of the country's economy. One of the most crucial first phases in the apparel industry is to create and develop garment patterns based on the anticipated apparel's specifications, and then to plan the marker and cut the fabric according to the pattern pieces. These can be done manually or with the use of Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) software (CAM). The garment business has been transformed by computer-aided design (CAD) and computer-aided manufacturing (CAM). Because fabric costs account for a large portion of the cost of garment manufacture, it is critical to properly utilize the fabric and reduce the percentage of fabric waste (percent). Additionally, minimizing production time will reduce lead time even more. Although CAD/CAM is expensive, it has a number of economic and technological advantages over other methods. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 8, Dec 2021 P 36-40

Point-of-care anti-CD19 CAR T-cells for treatment of relapsed and refractory aggressive B-cell lymphoma

Anti CD19 chimeric antigen receptor (CAR) T-cell therapy has transformed the care of relapsed and refractory aggressive B-cell lymphoma. However, financial toxicity and manufacturing time represent barriers to its widespread implementation. Study applicability, toxicity, and efficacy of a locally produced autologous CD19-directed CAR T-cell product were studied. We performed a phase 1b/2 clinical trial with a point-of-care (POC) CAR T-cell product that contains a CD28 costimulatory domain. Adult patients with aggressive B-cell lymphoma or transformed low-grade lymphoma who received at least 2 prior regimens were eligible. A total of 73 patients, with a median age of 49 years, met inclusion criteria. CAR T-cell production time from apheresis was 10 days (interquartile range 10-11), negating the need for bridging chemotherapy. Overall and complete response rates were 62.5% and 37.5%. Median progression-free and overall survival were 3.7 and 12.1 months, respectively. Overall and progression-free survival at 12 months were 52.1% (confidence interval [CI]: 40.8%-66.5%) and 40% (CI: 30%-53.7%), respectively. Patients who achieved response had longer progression-free and overall survival. Grade 3-4 cytokine release syndrome was observed in 9.5% of the patients, and immune effector cell-associated neurotoxicity syndrome grade 3-4 in 21.9%. No deaths occurred due to CAR T-cell toxicity. Fifteen patients (20%) underwent allogeneic stem cell transplantation at a median time of 60 days after CAR T-cell therapy; 8 were alive at last follow-up. Of the 6 patients who underwent the transplantation in complete response 2 deceased because of toxicity. POC CAR T-cells are a feasible therapeutic option in aggressive B-cell lymphoma. They provide good efficacy while minimizing production time and the need for bridging therapy.

Multiagent modeling of production logistics in the creation of high-tech products

Economic instability and stochastic behavior of the market lead to the need to develop new methods and models to reduce the life cycle of high-tech products. Therefore, the urgent task is a detailed consideration and analysis of each main stage of the life cycle of creating complex technical products. The current study develops a method for optimizing production processes. The subject of research is a production planning and management as the main stage of the life cycle. The method proposed in the publication is based on the component architecture of the created innovative high-tech product, which is obtained because of decomposition at the initial stage of design. Modern production is of distributed nature. While planning production, it is necessary to pay attention to the management and synchronization of material and other types of flows in the logistics chain of distributed production. To form a set of basic and subsidiary operations of distributed production, it is necessary to consider the logistical features, the level of decomposition of the component architecture of the created product, as well as the type of component in the production cycle. Logistics operations are conducted following the requirements for the relevant indicators, namely, the cost of the operation, quality, competitiveness, innovation, the risk of the operation. The main criterion for optimization is the duration of operations. The work uses multi-agent simulation modeling of a sequential logistics chain of production processes, as well as mathematical models and methods: system analysis, optimization using integer programming, multi-criteria optimization, and expert evaluations. The method reduces the duration of the production cycle for the manufacture of individual components of the complex architecture of high-tech products by determining the optimal set of production and ancillary logistics operations for each component, considering the requirements for key production indicators, which minimize production time of high-tech products.

Truck Assembly Line Reconfiguration to Reduce Cycle Time with Lean Manufacturing Approach in the Indonesian Automotive Industry

The automotive industry is one of the industries that plays a major role in Indonesia’s revenue sources, one of which is in meeting daily needs, especially for transportation and logistics. This causes the growth of truck production targets each year and has become one of Indonesia’s focus to target 1.29 million trucks produced in 2020. This study aims to minimize production time with the optimal number of workstations to minimize costs that will come out for increasing production capacity in truck assembly lines in Indonesia. The study was conducted with a lean manufacturing approach to analyze the waste contained in the assembly line. The study began by calculating time for each work using the time study method. The time obtained is then inputted to the mixed integer linear programming mathematical programming model developed in the LINGO 17.0 software. The result of data processing in the LINGO 17.0 software is the allocation of each job to the new workstation to get the production cycle time in accordance with the production takt time, and also the total idle time of the new assembly line.

Simultaneous Fabrication of Porous Alumina Lines By 3D Printed Multi-Capillary Sf-MDC

IntroductionPorous-type anodic aluminum oxide (porous alumina) films with an ordered nanostructure have attracted much attention in recent years. It is well known that the size and length of the pores are controlled by the anodizing conditions, including the concentration and composition of the used electrolyte.There are demand for formation of porous alumina film at selected area, and are a number of techniques for the formation of porous alumina at the desired size and shape. However, commonly used local anodized techniques present disadvantages in the complex processes involved.One technique that gets around the these problems is the droplet cell techniques. The droplet cell used electrolyte droplet that formed at the tip of capillary tube uses as electrochemical cell. One of the authors reported the application of solution flow type micro-droplet cell with co-axial dual capillary tubes (Sf-MDC) to form porous alumina film at selected area 1, 2, 3, 4. The thickness and width of the oxide film increases with decreasing droplet moving speed, and the growth rate of the oxide film is greatly affected by the specimen temperature. Using this cell makes it possible to form porous alumina lines with layered structure. However previously used Sf-MDC has drawback of slow alumina line fabrication. One technique that gets around this problem is using multi-capillary Sf-MDC. It is difficult to increase number of capillaries using previous making technique for Sf-MDC.3D printer is widely used and recent advancements in 3D printing technology allows us to produce complex structures with great accuracy and minimal production time. Therefor 3D printing technique is apply to make multi-capillary Sf-MDC. The purpose of this experiment is to design and fabricate a novel Sf-MDC using 3D printer and form multi porous alumina lines on the substrate.Fabrication of multi-capillary Sf-MDCA Sf-MDC was designed and photopolymer resin was used for 3D printing the parts. Optimal orientation was chosen to print the parts in order to minimize the number of supports, number of layers, time and volume required for printing. Using optimized printing parameter, multi-capillary Sf-MDC was made. Before using the Sf-MDC for anodizing, the support structure was trimmed and Pt wire was inserted inside the capillaries.ExperimentalSpecimen and electrolyte: High purity Al sheets (99.99 %, 10 × 30 mm, 110 µm in thickness) were used as specimens. The specimens were ultrasonically cleaned with highly purified water for 300 s, followed by ultrasonic cleaning in ethanol for 300 s. Then, the specimens were electropolished in 13.6 kmol m-3 CH3COOH /2.56 kmol m-3 HClO4 at a constant voltage of 28 V for 150 s at 278 K. After the polishing process, specimens were cleaned with highly purified water and acetone.The solutions used as the electrolyte for the anodizing were 0.22 kmol m-3 (COOH)2, 0.22 kmol/m-3 H3PO4, 0.3 kmol/m-3 H2SO4solutions.Anodizing: An electropolished specimen was set on a computer-controlled pulse-XYZ stage, and the specimen temperature during the anodizing was controlled by a Peltier device at 323 K. The cell was filled with electrolyte via a solution pump, then a droplet of electrolyte was formed at the tip of the inner capillary by adjusting the solution flow rate and a vacuum pressure. After the droplet of electrolyte was formed, thereafter, the droplet was put in contact with the specimen surface, and a constant voltage was applied. The moving speed of the specimen was controlled at 2.0 μms-1, and distance was 4 mm for the formation of the oxide film lines.Observation:Specimen surfaces and cross-sections after anodizing were examined by an optical microscope and scanning electron microscope, SEM. The specimens for the cross-sectional observation were prepared by simple curving and breaking. Before the SEM observations, a thin Au layer was sputtered on the specimens.ResultsThree uniformly sized porous alumina lines on the Al specimen can be formed by the Sf-MDC. From SEM observation, formed anodic oxide lines have a porous structure and average pores arrangement and pore diameter is nearly same for each lines.References T. Yamaguchi and M. Sakairi, Journal of The Surface Finishing Society of Japan, 385-390, 65 (2014)M. Sakairi, F. Nishino, and R. Itzinger, Surface and Interface Analysis, 48, 921-925 (2016)T. Matsumoto and M. Sakari, Journal of The Japan Institute of Light Metals, 68, 401-405 (2018).M. Sakairi, E. Han, T. Matsumoto, Journal of The Surface Finishing Society of Japan, 70, 20-24 (2019).T. Murata, Y. Goto, M. Sakairi, K. Fushimi, and T. Kikuchi, ECS Transaction, 33, 57 (2011).

Neuro-tabu search approach to scheduling in automotive manufacturing

The work concerns a new problem of minimizing production time of a set of tasks on machines while limiting the availability of machine operators. The problem is taken from practice, from a company producing subassemblies for the automotive industry. A mathematical model of the problem is formulated, and for its solution a neuro-tabu algorithm is proposed, which is a variation of the tabu search algorithm with a neural mechanism replacing the tabu list: short-term memory. The efficiency of the algorithm constructed in this way is verified on test examples based on real data from the production process.

Stable honeycomb structures and temperature based trajectory optimization for wire-arc additive manufacturing

We consider two mathematical problems that are connected and occur in the layer-wise production process of a workpiece using wire-arc additive manufacturing. As the first task, we consider the automatic construction of a honeycomb structure, given the boundary of a shape of interest. In doing this, we employ Lloyd’s algorithm in two different realizations. For computing the incorporated Voronoi tesselation we consider the use of a Delaunay triangulation or alternatively, the eikonal equation. We compare and modify these approaches with the aim of combining their respective advantages. Then in the second task, to find an optimal tool path guaranteeing minimal production time and high quality of the workpiece, a mixed-integer linear programming problem is derived. The model takes thermal conduction and radiation during the process into account and aims to minimize temperature gradients inside the material. Its solvability for standard mixed-integer solvers is demonstrated on several test-instances. The results are compared with manufactured workpieces.

Optimization of Part Consolidation for Minimum Production Costs and Time Using Additive Manufacturing

AbstractThis research presents a method of optimizing the consolidation of parts in an assembly using metal additive manufacturing (MAM). The method generates candidates for consolidation, filters them for feasibility and structural redundancy, finds the optimal build layout of the parts, and optimizes which parts to consolidate using a genetic algorithm. Results are presented for both minimal production time and minimal production costs, respectively. The production time and cost models consider each step of the manufacturing process, including MAM build, post-processing steps such as support structure removal, and assembly. It accounts for costs affected by part consolidation, including machine costs, material, scrap, energy consumption, and labor requirements. We find that developing a closed-loop filter that excludes consolidation candidates that are structurally redundant with others dramatically reduces the number of candidates, thereby significantly reducing convergence time. Results show that when increasing the number of parts that are consolidated, the production cost and time at first decrease due to reduced assembly steps, and then increase due to additional support structures needed to uphold the larger, consolidated parts. We present a rationale and evidence justifying that this is an important tradeoff of part consolidation that generalizes to many types of assemblies. Subsystems that are smaller, or can be oriented with very little support structures or have low material costs or fast deposition rates can have an optimum at full consolidation; for other subsystems, the optimum is less than 100%. The presented method offers a promising pathway to minimize production time and cost by consolidating parts using MAM. In our test-bed results for an aircraft fairing produced with powder-bed electron beam melting, the solution for minimizing production cost (time) is to consolidate 17 components into four (two) discrete parts, which leads to a 20% (25%) reduction in unit production cost (time).

Closed Shop Scheduling Optimisation using Max-Plus Automata

An appropriate scheduling system is needed in manufacturing activities to minimize production time and costs. Flow shop is one type of production flow that widely used in manufacturing. Based on the demand criteria, it has been known as a scheduling problem called closed shop. This scheduling emphasizes the make-to-stock (MTS) which produces a stock. We take the closed shop scheduling case studies from an existing literature and optimize scheduling using max-plus automata optimum. We compare the result with regular scheduling and the previous result in the literature. We show that the result of max-plus automata optimum scheduling are optimum compared than the existing regular scheduling and the existing previous result of the literature.

Optimization of machining economics and energy consumption in face milling operations

Metal cutting (or machining) is one important aspect of the manufacturing system. Selecting optimal cutting conditions for machining is then a crucial process planning task for manufacturing. Traditionally, solving such machining problems was only focused on economic objectives such as maximizing profit or minimizing production time requirement. In the recent decade, however, minimizing energy consumption in manufacturing processes has attracted increased attention due to increasing energy costs and concern with greenhouse gas emissions. Energy loss could be avoided by carefully selecting cutting parameters. This paper develops a multi-objective mathematical model to minimize unit production costs along with energy consumption for face milling operations. In addition, an evolutionary strategy (ES)-based optimization approach is used to identify optimal cutting conditions for the proposed model.

Bi-objective optimization of a job shop with two types of failures for the operating machines that use automated guided vehicles

Reliability of machinery and equipment in flexible manufacturing systems are among the most important issues to reduce production costs and to increase efficiency. This paper investigates the reliability of machinery in job shop production systems, where materials, parts, and other production needs are handled by automated guided vehicles (AGV). The failures time of the parallel machines in a given shop follow either an exponential or a Weibull distribution. As there is no closed-form equation to calculate the reliability of the shop in the Weibull case, a simulation approach is taken in this paper to estimate the reliability. Then, a bi-objective nonlinear optimization model is developed for the problem under investigation to maximize shop reliability as well as to minimize production time, simultaneously. In order to assess the efficacy of the proposed model, some random instances are generated, based on which two meta-heuristic algorithms called non-dominated sorting cuckoo search (NSCS) and multi-objective teaching–learning-based optimization (MOTLBO) are designed. Finally, to evaluate and compare the effectiveness of the proposed solution algorithms, an efficient solution AHP-TOPSIS technique is utilized.

Application of lean six sigma to waste minimization in cigarette paper industry

The cigarette paper industry is one of the industry that is always experiencing increasing demand from consumers. Consumer expectations for the products produced also increased both in terms of quality and quantity. The company continuously improves the quality of its products by trying to minimize nonconformity, waste and improve the efficiency of the whole production process of the company. In this cigarette industry, there is a disability whose value is above the company’s defect tolerance that is 10% of the production amount per month. Another problem also occurs in the production time is too long due to the many activities that are not value added (non value added activities) on the production floor. To overcome this problem, it is necessary to improve the production process of cigarette paper and minimize production time by reducing non value added activities. Repairs done with Lean Six Sigma. Lean Six Sigma is a combination of Lean and Six Sigma concept with DMAIC method (Define, Measure, Analyze, Improve, Control). With this Lean approach, obtained total production time of 1479.13 minutes proposal with cycle efficiency process increased by 12.64%.

Performance Evaluation of Cutting Fluids with Carbon Nano-Onions as Lubricant Additives

In machining of high precision automotive parts, the dimensional variation of the cutting process is very critical. The demand for high quality and fully automated production places a lot of emphasis on the cutting process, which has a major contribution to part quality. Cutting fluid has been a key factor to machining performance and a key contributor to increase the effectiveness of machining systems. In this way, cutting fluids play an important role in minimizing production time, cost, and energy in different machining operations. Maintaining and operating the cutting fluid supplies is a huge cost driver and an environmental challenge. Carbon onion nanoparticles have been successfully developed with high tribology performance and mixed in metalworking fluids (MWF) to improve the performance of the fluids. Even though the trend has been to use less MWF, which is dry or MQL whenever possible, MWF are still utilized in large volumes. The literature has reported several cases of very successful use of nanofluids in machining operations for various tough-to-machine materials. To enhance the coolant, nanoparticles such as carbon nano-onions are mixed in the oil and water-based MWF. The paper presents the results from several tests performed during the evaluation of the above nanoparticles in oil and water based cutting fluids in machining processes.

Обоснование технологических режимов многократной пропитки–сушки и последующей автоклавной обработки для обеспечения требуемого состава материала теплозащитного покрытия и минимального времени его изготовления

Обоснование технологических режимов многократной пропитки–сушки и последующей автоклавной обработки для обеспечения требуемого состава материала теплозащитного покрытия и минимального времени его изготовления