Machine Capacity Research Articles

Human Intelligence to Artificial Intelligence: Critical thinking and Emotional Intelligence

Artificial Intelligence may be it is branch of computing. The computer science engineering is creating intelligent machines and especially intelligent computer programs. AI could also be how of making a computer. A computer-controlled robot or software thinks intelligently. AI is accomplished by studying the way to think human brain. How humans learn, decide, and work while trying to unravel a haul. We also create intelligent machines. It is often developing human activities. Some human activities are reading, listening, each and are going to be covered. Machine learning, deep learning may be a part of this AI. The AI projects have a machine control and remote. Mostly AI is machine learning. Current status will be there from AI. Feature goals in AI. Computing system study that plan to model and applying human brain. It is a branch of computer simulating a intelligent behavior. The machine capacity is intimate human behavior. The intelligence has some types are going to be there, linguistic intelligence, musical intelligence, logical-mathematical intelligence, spatial intelligence, intra-personal intelligence, interpersonal intelligence. The intelligence composed by reasoning, learning, problem solving, perception, linguistic intelligence and so on. Ability to calculate a system, reasoning, perceives a relationships and analogs, learn from experience. Store and retrieve information from memory. Solving a problems and complex ideas to use tongue fluently classifying. Generalize and adapt new situation

Development and Performance Evaluation of Low-Cost 2WT-Operated Earthing-Up Machine for Sugarcane Cultivation in Bangladesh

Like most crops, sugarcane needs to be kept upright until it is harvested. The lodging of sugarcane has significant negative effects on the cane yield and sugar content of sugarcane. To keep sugarcane upright, earthing up is an essential in the cultural part of the operation. In Bangladesh, most of the sugarcane cultivation operations, including earthing-up, are generally performed in a traditional manual method which increases the production costs as well as reduces the income of sugarcane growers. Therefore, a cost-effective two-wheeled tractor (2WT)-mounted earthing-up machine was developed at the Bangladesh Sugarcrop Research Institute (BSRI), Pabna, to reduce drudgery and the cost of sugarcane production. Field tests were conducted in an experimental sugarcane field at BSRI and technical and economic performances of the developed earthing-up machine were also carried out based on the field test. The average effective field capacity and field efficiency of the earthing-up machine were found to be 0.16 ha/h and 77.41%, respectively. The 2WT-driven earthing-up machine was not found to be economically viable when it was used only for earthing-up operations. However, when the 2WT was used as the main driver for other activities, including earthing-up operation, the earthing-up machine became economically beneficial with net cash flow (NCF), net present value (NPV), internal rate of return (IRR), benefit–cost ratio (BCR), and payback period (PP) of BDT 148,497/ha, BDT 23,184, 3%, 3.81:1, and approximately 1 year, respectively. On the contrary, considering the cost of only earthing-up tool without 2WT, it was found to be economically beneficial with NCF, NPV, IRR, BCR, and PP of BDT 16,428/ha, BDT 3053, 4.7%, 2.71:1, and approximately 2 years, respectively. In Bangladesh, 2WT is commonly used for versatile farming purposes. Therefore, the versatile use of 2WT as a prime mover for other machines, including the earthing-up machine, can make earthing-up machine economically viable and beneficial for sugarcane growers in Bangladesh.

Sustainability assessment framework of biomedical scaffolds: Additive manufacturing versus traditional manufacturing

Sustainability assessment is a method for regulating and enhancing the sustainability performance of a product, process, or system. New technologies have streamlined the process of sustainable growth by progressively moving from conventional manufacturing to new technologies. The current study developed a sustainability assessment framework from the lifecycle perspective of a medical device i.e., scaffold. The framework first involved economic, environmental and social assessment to assess scaffold's life cycle supply chain with two different manufacturing routes, i.e. additive manufacturing (AM) and traditional manufacturing (TM) routes. Further, the sustainability index weight of different indicators and subsystems has been evaluated. Finally, the overall composite sustainability index for AM and TM routes has also been calculated using the entropy weight method (EWM). The economic assessment revealed that AM route has significantly lower cost (20%) than TM route for unit scaffold. Additionally, production rate of TM was found to be lower than AM (24.24%) instead of having high machine capacity utilization. The TM route showed higher environmental load, especially from fabrication, sterilization, and material processing stage. Similarly, social assessment also presented that AM is superior to TM methodology for workers and customers. The subsystem index's weight showed that environmental index (0.8292) has high importance followed by economic index (0.1473) and social index (0.0235). The overall composite Sustainability Index (SI) showed that AM route (SI = 0.9271) is more sustainable than TM route (SI = 0.0136). The sensitivity analysis proved the robustness of the method without changing the ranks of the subsystem's index. Overall, the work provides a quantitative perspective for sustainability assessment of a medical product's life cycle supply chain, which is greatly helpful in making differentiated management measures in the medical industry.

A new variety of axial piston hydraulic machines with multi-row units and a dual oscillating unit

The possibility of increasing the working volume, power, specific energy capacity (energy efficiency), and acceleration response of hydraulic machines under reduced supply and torque pulsation is investigated. The research methodology included the geometric, kinematic, power, and energy analysis of a four-row axial piston hydraulic machine with a dual oscillating unit and without an end distribution system. As a result, a new type of compact rotary hydraulic machines with volumetric action was created. In the proposed model, each subsequent row of cylinders is located in the inter-cylinder space of the previous cylinders with smaller radii. Such a design provides for a 24.5-fold increase in the working capacity and power of a hydraulic machine compared to a single-row design, as well as an increase in the acceleration response in the hydraulic motor mode. The elimination of end distribution systems excludes the possibility of violation of joint tightness between blocks and distribution disks due to block overturning by piston centrifugal forces at high rotation speeds and a multiple reduction of supply and torque pulsation. It was established that the increase in the specific power capacity of a hydraulic machine depends on its particular implementation, potentially reaching 18–25 kW/kg. The abovementioned features of the proposed axial piston hydraulic machine with a dual oscillating unit ensure the compactness of oscillating units, minimum dimensions of the cylinder blocks, and the hydraulic machine as a whole, resulting in its minimum mass and maximum specific power capacity.

Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation

BackgroundArtificial intelligence (AI) is the capacity of machines to perform tasks that ordinarily require human intelligence. AI can be utilized in various pharmaceutical applications with less time and cost. ObjectivesTo evaluate community pharmacists’ willingness and attitudes towards the adoption of AI technology at pharmacy settings, and the barriers that hinder AI implementation. MethodsThis cross-sectional study was conducted among community pharmacists in Jordan using an online-based questionnaire. In addition to socio-demographics, the survey assessed pharmacists’ willingness, attitudes, and barriers to AI adoption in pharmacy. Binary logistic regression was conducted to find the variables that are independently associated with willingness and attitude towards AI implementation. ResultsThe present study enrolled 401 pharmacist participants. The median age was 30 (29–33) years. Most of the pharmacists were females (66.6%), had bachelor’s degree of pharmacy (56.1%), had low-income (54.6%), and had one to five years of experience (35.9%). The pharmacists showed good willingness and attitude towards AI implementation at pharmacy (n = 401). The most common barriers to AI were lack of AI-related software and hardware (79.2%), the need for human supervision (76.4%), and the high running cost of AI (74.6%). Longer weekly working hours (attitude: OR = 1.072, 95% C.I (1.040–1.104), P < 0.001, willingness: OR = 1.069, 95% Cl. 1.039–1.009, P-value = 0.011), and higher knowledge of AI applications (attitude: OR = 1.697, 95%Cl (1.327–2.170), willingness: OR = 1.790, 95%Cl. (1.396–2.297), P-value < 0.001 for both) were significantly associated with better willingness and attitude towards AI, whereas greater years of experience (OR = 20.859, 95% Cl (5.241–83.017), P-value < 0.001) were associated with higher willingness. In contrast, pharmacists with high income (OR = 0.382, 95% Cl. (0.183–0.795), P-value = 0.010), and those with<10 visitors (OR = 0.172, 95% Cl. (0.035–0.838), P-value = 0.029) or 31–50 visitors daily (OR = 0.392, 95% Cl. (0.162–0.944), P-value = 0.037) had less willingness to adopt AI. ConclusionsDespite the pharmacists' positive willingness and attitudes toward AI, several barriers were identified, highlighting the importance of providing educational and training programs to improve pharmacists' knowledge of AI, as well as ensuring adequate funding support to overcome the issue of AI high operating costs.

A matheuristic for flowshop scheduling with batch processing machines in textile manufacturing

Inspired by a real-world textile packing process, this paper investigates a novel hybrid flowshop scheduling problem with batch processing machines to minimize the makespan. Geometry sizes of textile products, non-identical capacities of packing machines, and the capacity of the needle detector are addressed in parallel-batching modes. To make batching and sequencing decisions simultaneously, a mixed integer linear programming model (MILP) is formulated. Then, a matheuristic method, Tabu Search with Fixing and Optimization (TSFO), is developed. Using tabu search to determine which variables to be fixed, the MILP is solved through a fix-and-optimize process. The results of extensive computational experiments show that the TSFO yields better solutions within much less computation time than solving the model directly in a commercial solver. Furthermore, the TSFO also outperforms an existing method in a special case from literature.

Incremental Feeding High-Pressure Sliding (IF-HPS) Process for Upscaling Highly Strained Areas in Metallic Materials with Enhanced Mechanical Properties

This paper presents an overview of the recent development of incremental feeding high-pressure sliding (IF-HPS) process for grain refinement of metallic sheets with enlarged areas. The IF-HPS process is a method of severe plastic deformation (SPD) under high pressure without increasing the machine capacity. The IF-HPS process combines an incremental feeding technique with the high-pressure sliding (HPS) process so that a severely deformed area can be extended. Development of the IF-HPS process includes the use of flat-type anvils instead of groove-type anvils, which makes it easier to enlarge the SPD-processed areas. The development is also described in terms of the sliding mode and the feeding pattern, where the former is determined by the sliding distance and the numbers of the reciprocation of the sliding and the latter by the feeding distance and the feeding direction. The application of the IF-HPS process is made to metallic materials such as a Ni-based superalloy (Inconel 718), a Ti-6Al-7Nb alloy (F1295) and commercially available Al alloys (A1050, A3105, A5052 and A5182). It is shown that the grain refinement is successfully achieved so that superplastic elongation more than 400% is attained in the Ni- and Ti-based alloys, and the room-temperature tensile strength is well enhanced in the Al alloys. It is then demonstrated that the IF-HPS process is promising to extend the SPD-processed area without increasing the machine capacity. Furthermore, a new approach is suggested for material design, such as the hybrid materials composed of conventional and fine-grained materials and functionally graded materials.

CNC machining optimization of hydro-turbine runner blade based on VERICUT

Aiming at the problem of low production efficiency caused by the unreasonable setting of cutting parameters for CNC machining of hydro-turbine runner blade, the Force module of VERICUT software is used to analyze and compare the cutting force, the cutting power, and the material removal rate of the blade under different cutting parameters, find the cutting parameters that can give full play to the machining capacity of the machine tool, and use the optimization function of Force to automatically adjust the feed speed in the machining program. The test results show that after the optimization of cutting parameters, the production efficiency of the NC machining program is significantly improved, and the cutting power of the machine tool spindle is stable.

Моделирование технологии очистки леса с помощью многооперационной машины

A conceptual model of a forest multi-operator machine for clearing debris caused by tree mortality is presented. A technological process of sanitary forest clearing that minimizes manual labour with the help of a machine and a winch is considered, including the technology of litter removal with its processing into firewood in the forest. Two variants of multi-operating machine's work with a winch are given: sequential, when the machine processes the wood from the fell as it is received from the winch, and parallel, when the winch and machine work independently of each other. It is established that the productivity at debris removal at parallel operation of the machine and winch is higher by 7...14 % than at their consecutive operation. It is revealed that the productivity of a multi-operator machine when the machine and a winch work in parallel increases by 53...55 %. It is determined that the load of the machine, when working together with a winch, is less than 50 % of working time. It is recommended that the winch and the machine work together at close capacities, if the winch capacity is very different from the machine capacity, then they should work separately.

Multi-objective hierarchical clustering for tool assignment

Due to the limited tool magazine capacities of CNC machines, time-consuming tool changeovers result in inefficient equipment utilization. This study provides a method to minimize the changeovers by optimizing the allocation of the tools to the machines. The proposed algorithm is efficient as it approaches the tool assignment task as a multi-objective hierarchical clustering problem where the products are grouped based on the similarity of the tool demands. The novelty of the goal-oriented agglomerative clustering algorithm is that it is based on the Pareto optimal selection of the merged clusters. The applicability of the method is demonstrated through an industrial case study. The tool assignment problem has also been formulated as a bin-packing optimization task, and the results of the related linear programming were used as a benchmark reference. The comparison highlighted that the proposed method provides a feasible solution for large real-life problems with low computation time.

On the thermodynamics of DNA methylation process

DNA methylation is an epigenetic mechanism that plays important roles in various biological processes including transcriptional and post-transcriptional regulation, genomic imprinting, aging, and stress response to environmental changes and disease. Consistent with thermodynamic principles acting within living systems and the application of maximum entropy principle, we propose a theoretical framework to understand and decode the DNA methylation process. A central tenet of this argument is that the probability density function of DNA methylation information-divergence summarizes the statistical biophysics underlying spontaneous methylation background and implicitly bears on the channel capacity of molecular machines conforming to Shannon’s capacity theorem. On this theoretical basis, contributions from the molecular machine (enzyme) logical operations to Gibb entropy (S) and Helmholtz free energy (F) are intrinsic. Application to the estimations of S on datasets from Arabidopsis thaliana suggests that, as a thermodynamic state variable, individual methylome entropy is completely determined by the current state of the system, which in biological terms translates to a correspondence between estimated entropy values and observable phenotypic state. In patients with different types of cancer, results suggest that a significant information loss occurs in the transition from differentiated (healthy) tissues to cancer cells. This type of analysis may have important implications for early-stage diagnostics. The analysis of entropy fluctuations on experimental datasets revealed existence of restrictions on the magnitude of genome-wide methylation changes originating by organismal response to environmental changes. Only dysfunctional stages observed in the Arabidopsis mutant met1 and in cancer cells do not conform to these rules.

Application and development of Artificial Neural Networks to predict structural damage subjected to earthquake-A review

The complexity of earthquake incidents supports efforts to use machine learning methods as an alternative to conventional methods because they can simply capture difficult relations between the input and output parameters without requiring a particular functional structure. Machine learning is a branch of artificial intelligence techniques that applies the capacity of machines to recreate intelligent human behavior and has been receiving increasing consideration as an effective solution for damage detection due to earthquakes. Artificial neural networks (ANNs) are one of the most important machine techniques, inspired by the human brain. There hasn’t been a lot of published research on the use of ANNs for structural damage identification to predict earthquakes on various structures up until now. This paper presents a comprehensive review of recent studies on the applications and development of ANNs to predict earthquakes and damage caused by earthquakes on different structures. ANNs can learn from their experience and have drawn significant consideration in damage detection due to their capability of pattern identification and error tolerance in forming a nonlinear modeling between the inputs and outputs. According to this research, the use of ANNs can prevent unpredictable failures and reduce maintenance costs, increasing the safety and functionality of structures. A brief introduction to the ANN algorithm is presented first. Following that, the benefits, and limitations of ANNs, as well as some new research trends, have been discussed.

New Trends of Sugarcane Cultivation Systems Toward Sugar Production on the Free Market: A Review

Sugar is one of the staple food commodities that has an important role in the Indonesian economy. The high demand for domestic sugar has resulted in the inability of sugar factories to meet the demand for sugar consumption because domestic sugar production is still low. This is due to decreased land area and productivity, low sugar yield rates, and low factory efficiency. This paper describes the improvement of sugarcane cultivation to the process of making sugar to support national consumption. The article uses a systematic review method on the latest sugarcane research and reports the conditions directly on the plantation. The results show that the existing sugarcane supply is still less than the factory's demand, so the factory worked inefficiently. Even though the factory has new machines and technology to produce good quality sugar with a capacity of 4,600 TCD, companies can take a coaching approach to the surrounding community to carry out sugarcane cultivation and provide financial support to the surrounding community. Based on the reality of low production and factory efficiency, the government needs to support the sugarcane cultivation system through farming production systems, improving factory machine capacity and labor for sugarcane estate in the global market era.

Cost and Time Optimization in Fleet Management- Case Study of Sinnar Shirdi Highway

Abstract: The aim of the study is to show how fleet management can help in saving time and cost by comparing the current onsite equipment to optimised results. The detailed study of fleet of equipment and their related parameters and specifications is important because it helps to determine requirement of equipments for a particular activity. All the cost including labor, maintenance, operating costs, machine capacity were considered to find out the productivity as well as expenses. Based on the site visit and data collection various parameters such as productivity of excavator, production rate, cycle time and other parameters of activities such as earthmoving equipment, hauling of trucks as well as productivity of paver were also calculated. The parameters were obtained for various combinations of different truck sizes as shown in the MS- Excel sheet. For different truck sizes and different combinations we get different cost index.

Manufacture of Composite Plastic Pellet Seed Machine Capacity 2.5 Kg/Hour

Manufacture of Composite Plastic Pellet Seed Machine Capacity 2.5 Kg/Hour

OPTIMISATION OF INTERRUPTED GRINDING PARAMETERS ACCORDING TO THE TEMPERATURE CRITERION

In the paper analytical optimization of discontinuous grinding parameters according to temperature criterion is carried out and on its basis conditions for significant reduction of cutting temperature, which consist mainly in increasing the number of contacts of working ledges of discontinuous wheel with fixed cross-section of machined workpiece, are determined. It is established by calculations that providing 20 contacts the cutting temperature may be reduced up to 3 times in comparison with the conventional grinding by a continuous wheel. This is achieved in the conditions of deep interrupted grinding with relatively low workpiece speed, as in the conditions of traditionally used multipass interrupted grinding not more than 6 contacts of working ledges of an interrupted wheel with the fixed cross-section of the workpiece are realized and the cutting temperature is reduced only in the range of 50 %. It is established by calculations that the minimum of cutting temperature at discontinuous grinding is achieved under conditions of equality of lengths of the working shoulder and the notch on the discontinuous grinding wheel and their reduction. It is also established that excess of the length of the working ledge over the length of the notch of the discontinuous wheel leads to insignificant increase of the cutting temperature. This reduces the wear of the discontinuous wheel and increases the machining capacity without actually increasing the cutting temperature. The paper shows that the obtained theoretical solutions are a necessary condition for ensuring a significant reduction of cutting temperature in discontinuous grinding. A sufficient condition should be considered as complete or partial cooling of grinding zone between contacts of machined workpiece with working jaws of discontinuous grinding wheel by intensive supply of effective technological media into the grinding zone.

Risk prevention of plywood product defects using Failure Mode Effect Analysis (FMEA) in the Indonesian plywood processing industry

ABSTRACT This case study aims to determine factors that cause defects in plywood products using failure mode effect analysis (FMEA) parameters. It also analyzes prevention strategies against plywood product defects in the plywood industry in Indonesia. The study involved 9 participants who are employees of different divisions. The research data were collected from direct observations of the plywood production process, analysis of documents recording plywood product defects, and focus group discussions. Based on the results of thematic analysis using FMEA parameters, this study identified five factors that significantly contribute to the failure of plywood products, as indicated by their highest Risk Priority Number (RPN) values. These factors are: (1) lack of employee discipline, (2) unstable machine temperature and excessive machine capacity usage, (3) waste on the veneer surface, (4) excessive adhesive wastage, and (5) inefficient work performance of the employees. The study suggests that the FMEA concept employed to capture product defects can potentially be used to explore employees’ perspectives and their lived experiences in plywood production. In addition, FMEA can provide improvement feedback to prevent defects in plywood products.

Material Flow Cost Accounting as a Resource-Saving Tool for Emerging Recycling Technologies

Material Flow Cost Accounting (MFCA) is an environmental management accounting method that allocates costs to material and energy flows through a process, thereby enabling a simultaneous reduction in environmental impacts alongside an improvement in business and economic efficiency. This study illustrates the versatility of MFCA beyond its usual application to existing production and manufacturing processes. In this paper, MFCA is used to assess the financial viability of two emerging recycling technologies, IRETA2 (Development and Evaluation of Recycling Routes to Recover Tantalum from Electronic Waste) and ReComp (Development of an Innovative, Economically and Ecologically Sensible Recycling Method for Metallised ABS and PC/ABS Composite Waste). These two projects differ in their process structure. Whilst IRETA2 is a strictly linear recycling process, ReComp consists of two process streams, split according to the treatment of its two material fractions. For both projects, the lab-scale experimental results were used to develop an MFCA model of the recycling process scaled at each project partner’s facilities. MFCA was utilised to calculate the projects’ overall profit or loss, the impact of the final products’ market conditions and processing rate (in the case of IRETA2), or machinery capacity (for ReComp) on the overall results. The results show that neither IRETA2 nor ReComp are financially viable based on the current output products’ market value and quantity produced. However, through a sensitivity analysis, it is demonstrated that IRETA2 could become financially viable if the processing rate or market conditions were to improve. Additionally, ReComp could become financially viable if there was an increase in machine capacity. Finally, this paper also explores possible implications of MFCA when applied to emerging recycling technologies on EU policy and strategy, particularly those related to the EU Green Deal, such as extended producer responsibility and supply chain acts.

Life cycle assessment of injection moulding tools and multicomponent plastic cap production

Long-term product improvement requires detailed analysis that includes information from the entire product life cycle. Life cycle assessment according to the standards ISO 14040 and ISO 14044 provides information on the environmental impact of products throughout their life cycle. The aim of the study is to analyze the environmental impact of a multicomponent plastic product in two variants and the associated customized tools using life cycle assessment. The subject of this analysis is the previous and the improved design of a multicomponent plastic cap for 19 l water bottles and the associated custom-manufactured tools. The main improvements of the custom-made tools are in the larger number of cores, and the new cap design was improved with fewer components and mass. The results show that the production and packaging of the improved multicomponent plastic cap has more than two times lower environmental impacts in the categories of global warming potential, freshwater eutrophication, terrestrial acidification ozone formation, human health and non reneweable, fossil. The environmental impact of custom injection moulding tools is strongly influenced by the capacity of the injection moulding machine and the number of cores or number of products that can be produced in a batch. In addition, the results of the improved 19 l multicomponent plastic cap showed a lower environmental impact compared to previous studie of the 5 l plastic cap.

PENGEMBANGAN MESIN PENCABIK IKAN TUNA UNTUK PEMBUATAN ABON IKAN SKALA INDUSTRI RUMAH TANGGA

This study aims to develop a fish grater machine to produce shredded fish on a household scale. The development of this fish shredder machine considers getting the maximum capacity, a minimum percentage of losses, a maximum percentage of the samples with short grade and middle grade size, and a maximum percentage of the samples with rough grade size with limited sources specified power. The method used in this research is the machine manufacturing and testing approach. Three types of shredder machine teeth (K-type, P-type, and B-type) are the main focus of this research to optimize the quality of the shredded material and the machine's performance. The machine capacity, the percentage of losses, and the optimal quality of the counting size of the developed machine can be achieved using K-type shredder machine teeth. Analysis of variance and the t-test are used simultaneously to determine the optimal performance of this machine. The results of this study suggest that using a K-type shredder machine teeth is the most appropriate shredder machine for shredded fish.