Machining Cost Research Articles

A modified Johnson-Cook constitutive model of Inconel 690 weld overlay taking into account the strain rate softening effect

Precise material constitutive models are essential for finite element (FE) cutting simulation and analytical calculations of cutting mechanics. In this work, a split Hopkinson pressure bar (SHPB) equipment was employed to investigate the dynamic mechanical behavior of Inconel 690 weld overlay with a wide range of temperatures (20℃, 200℃, 400℃, 600℃, and 800℃) and strain rates (5000s-1, 7500s-1, 10,000s-1, and 12,500s-1). Based on the material flow characteristics at different loading conditions, a modified Johnson-Cook (JC) constitutive model was established, which takes into account the strain rate softening effect at high strain rates and the softening behavior induced by the competition between work hardening and dynamic recovery at large strains. Compared with the original JC constitutive model, the modified constitutive model can provide a closer correspondence between the predicted flow stresses and experimental data. The modified material constitutive model was introduced into FE simulation for orthogonal cutting of Inconel 690 weld overlay. The results indicate that the average prediction errors for the main cutting force and thrust force are 6.38% and 11.38%, respectively, validating the applicability and reliability of the modified JC constitutive model for cutting simulation applications. This study can provide a mechanical foundation for FE analysis in high-speed cutting of Inconel 690 weld overlay, which is conducive to optimizing cutting parameters, reducing machining costs, and enhancing production efficiency in practical industrial manufacturing.

Expert elicitation to assess real-world productivity gains in laser powder bed fusion

Purpose Laser powder bed fusion (LPBF) additive manufacturing (AM) enables the design of complex parts using materials that are otherwise difficult to fabricate. Due to the high cost of machines, the parts produced by LBPF are expensive. Both researchers and industry are therefore focused on lowering costs by improving productivity while ensuring part quality. The purpose of this study is to quantify the productivity gains from using laser beam shaping, multi-laser printing and the use of large build chambers to print larger size parts. Design/methodology/approach This paper performs an expert elicitation with 18 experts. Findings This paper finds that experts believe that larger parts are less likely to print successfully. Increasing the part footprint is more detrimental to print success than increasing part height. Experts also believe that beam shaping is expected to provide limited print time improvement (median 4% reduction, 90% CI: 2%–25%) while improving part quality, whereas going from one to two lasers is expected to provide a median of 25% (90% CI: 10%–45%) print time improvement but degrade part quality. Through cost analysis of a representative part, this paper shows that the uncertainty in build success rates for large parts dominates expected cost reductions from laser beam shaping or multi-laser printing. Research limitations/implications The study has three key limitations. First, it is possible that the sample of experts who agreed to take the survey biases the results. By definition, these are individuals who are willing to share what they know. There may be other experts who have a different view of the efficacy of the technologies evaluated here, but that view might be based on proprietary knowledge, which those experts are unable to share. Second, an elicitation captures what is known at a moment in time. As technology improves and as widespread deployment results in learning, the most consequential finding − that experts believed that success rates for large builds are likely to be low − may become less valid. Third, the overarching goal of this study is to assess technologies to improve AM productivity for high performance metal parts. A single study can only partially achieve this goal. The selection of technologies is constrained by both the desire to keep the study tractable and the suitability of expert elicitation as a method. For example, expert elicitation is not appropriate to assess the efficacy of technologies where sufficient empirical data or analytical techniques exist. Practical implications The results show that AM research and policy initiatives, including standards and regulatory schemes, must support efforts to improve the repeatability and reliability of the technological innovations that are needed to deploy AM in cost-critical or high throughput applications. These results also reinforce the criticality of workforce development components of existing (and future) AM policy initiatives. The elicitation revealed a significant number of factors that must be considered and potentially managed to ensure successful builds. Notably, no experts interviewed discussed all factors. While this may be a consequence of availability bias, it suggests that inexperienced AM users and nonexpert decision-makers, including managers, who would like to adopt new AM technologies, may be unaware of the myriad mechanisms by which build failure can occur and may fail to take mitigating action. This result contradicts a common belief that complicated parts can be fabricated with little to no expertise (assuming access to a design file for the part). Workforce development programs will be essential to help AM users develop the knowledge required to successfully implement metal AM. Originality/value Several strategies, including increasing the build volume to print larger parts or more parts at a time, using multiple lasers and beam shaping are proposed to improve the productivity of AM. However, the real-world efficacy of these strategies is not known. This work pools the judgment of experts to give decision-makers some insight into the current, real-world efficacy of these approaches.

Insourcing additive manufacturing for spare parts production: is it profitable? An extensive analysis and the proposal of a Decision Support System

Recently, Additive Manufacturing (AM) has gained significant interest as promising technology for spare parts production. Unlike Conventional Manufacturing (CM), insourcing AM machine(s) enables the production of spare parts on demand, which in turn reduces inventory levels. However, AM is characterised by high costs, primarily associated with the purchase of AM machines. Therefore, the question arises as to whether insourcing AM is profitable for spare parts production. Here, we elaborated a full factorial comparison of 2,187 instances. Following industrial applications, we considered on demand production for insourced AM, while for CM, a make-to-stock approach was used. We found that under unconstrained stock system, the insourcing of AM is not preferable due to the high costs of AM machines. Under constrained stock system, however, AM is profitable in 68.5% of the analysed instances, leading to an average saving of 46%. Furthermore, for each tested scenario, we determined the maximum order-up-to level that makes AM profitable. From this analysis, we derived a decision tree to identify under which spare parts characteristics (i.e. costs, lead time, and part reliability) and maximum order-up-to levels AM becoming profitable. This serves as a Decision Support System (DSS) to assist practitioners in selecting the best production technology.

Alumina-enriched sunflower bio-oil in machining of Hastelloy C-276: a fuzzy Mamdani model-aided sustainable manufacturing paradigm

With the increasing emphasis on sustainable manufacturing practices, eco-friendly lubricants have gained significant attention to moderate the friction coefficient at the tool-work interface. In line with this, the contemporary study aimed to examine the viability of Alumina-enriched sunflower bio-oil as a metalworking fluid. Different volume fractions of Alumina nanoparticles (varying from 0 to 1 vol%) were mixed with sunflower bio-oil, and the physical properties, for instance, contact angle and dynamic viscosity, were analyzed to determine the optimal concentration of Alumina. Subsequently, machining experiments were executed on Hastelloy C-276 under various lubricating conditions, including dry cutting, compressed air, sunflower bio-oil, and 0.6 vol% Alumina-sunflower bio-oil. A comparative analysis among these lubricating mediums demonstrated that sunflower bio-oil with a 0.6 vol% Alumina concentration outperformed others, resulting in a significant reduction of surface roughness, and tool wear by 73.31%, and 82.14% respectively when compared to dry machining. Besides, the utilization of 0.6 vol% Alumina-sunflower bio-oil has demonstrated a reduction of 17.86% in total machining cost, along with reductions of 15.44% in energy consumption and carbon emissions, when compared to dry machining. Finally, a Taguchi-designed experiment consisting of sixteen trials was performed in different lubricating conditions, and a Fuzzy-Mamdani model was employed to achieve a sustainable machining environment. The sustainability assessment results indicated that a cutting speed of 75 m/min, feed of 0.05 mm/tooth, depth of cut of 0.15 mm, and the utilization of the 0.6 vol% Alumina-sunflower bio-oil resulted in the most sustainable machining environment, with the highest Multi-Performance Characteristics Index of 0.75.

Machining performance, economic and environmental analyses and multi-criteria optimization of electric discharge machining for SS310 alloy

With the expansion of the manufacturing sector, it has become crucial to incorporate sustainable production methods in order to remain competitive in the market. This study focuses on addressing the needs of the manufacturing industry by conducting a sustainability analysis of electric discharge machining for SS310 alloy. The analysis explores the impact of various electrode materials, for instance, copper and brass, as well as different machining variables, including discharge current (I = 4–12 A), spark gap (SG = 6–12 mu), pulse duration (Pon = 15–45 μs), and duty cycle (DC = 75–85%) using Taguchi method. The objective is to optimize the machining performance measures, which includes material removal rate (MRR), surface roughness (Ra), electrode wear (EW), and energy consumption (EC). In addition, the economic analysis of the machining process takes into account factors such as energy cost, dielectric consumption cost, EW cost, labor cost, and machine depreciation cost for both types of electrodes. Furthermore, the study investigates the carbon emissions resulting from EC, dielectric consumption, and EW to assess the environmental impact of the machining process. Multi-criteria decision-making approach is employed to assess the sustainability of the machining process by taking into account several performance, cost and environmental factors simultaneously. From empirical analysis, it has been observed that the copper electrode outperformed the brass electrode in terms of MRR (2.67 mm3/min), Ra (3.36 µm), EW (0.272 g), and EC (145.08 kJ) due to its superior electrical and thermal characteristics. In the cost analysis, copper offered lower costs for EC (2.02 PKR) attributed to its higher electrical conductivity while higher costs in terms of EW (5.5 PKR) and dielectric consumption (5.2 PKR) than brass. However, the analysis of labor and machine depreciation costs revealed that the application of copper electrode results in lower costs (80.1 and 99.3 PKR, respectively) than the brass electrode primarily due to its shorter machining time. The analysis of the environmental impact showed that the utilization of a copper electrode leads to reduced carbon emissions of 9.8 g CO2 due to its lower EC during the machining process. However, the copper electrode results in higher emissions from EW (5.07 g CO2) and dielectric consumption (54.58 g CO2) compared to the brass electrode. Based on the multi-criteria decision-making using the composite desirability function approach, it is evident that the copper electrode exhibits superior performance in terms of MRR, Ra, and total machining cost. Conversely, the brass electrode demonstrates better performance in terms of overall carbon emissions.

COMPARATIVE PERFORMANCE EVALUATION BETWEEN AJM AND HOT-AJM DURING MACHINING OF ZIRCONIA CERAMIC USING SILICON CARBIDE ABRASIVES

Abrasive jet machining (AJM) process is commonly used for cutting and drilling of brittle materials in which the phenomenon of material removal can be considered as mechanical erosion by the impingement of high-velocity abrasives. The focus of this research is to compare the performance and economic benefits of recently developed hot abrasive jet machining (hot-AJM) with traditional AJM techniques when machining zirconia ceramic using silicon carbide (SiC) grain particles. The modified AJM employed abrasive air jet (combination of hot abrasive and compressed air) to strike on the work surface for material erosion. Briefly, the cutting performance is investigated by comparing the technological characteristics like material removal rate, machining cost, and taper angle of the developed hole. Abrasive grain size, nozzle pressure, and stand-off distance are considered as the variable factors for machining trials in accordance with the design of experiments. The usage of hot abrasives in AJM improved the material erosion owing to the occurrence of plastic deformation followed by deep chipping on the machined surfaces. From the results, it was observed that the hot-AJM outperformed the normal AJM with regard to improved material removal, reduced dimensional deviation of hole and minimal machining cost. According to the findings of the cost assessment, the machining of zirconia ceramic using hot-AJM was more cost-effective than using normal AJM since it resulted 25% reduction in the total cost of production. The overall machining cost expenditure per unit in hot-AJM was lower (INR 123.12) than expenditure in traditional AJM (INR 153.47). Machining with hot-modified AJM, compared to normal AJM, offers a more techno-economically viable solution for enhancing machinability.

Optimum selection of nature-inspired texture pattern for cutting tool surface using an integrated multi-criteria decision-making approach: a comparative analysis

Purpose This paper aims to focus on the selection of an appropriate nature-inspired texture pattern for cutting tool tribological surface. The selection process uses the recognized skin textures of different snakes scrolling on highly rough and projected surface conditions to analyze suitability of texture based on the texture geometry and machining conditions. The work also aims to propose a texture pattern selection process to incorporate on cutting tool tribological surface. Design/methodology/approach The selection of alternative nature-inspired texture patterns based on the texture pattern geometry and machining properties leads to a multi-criteria decision-making problem. Thirteen criteria are considered for selecting an appropriate texture pattern among 14 alternatives, i.e. nature-inspired texture patterns. In the present work, an integrated analytical hierarchy process (AHP)-TOPSIS, AHP-multi-objective optimization on the basis of ratio analysis (MOORA) and AHP-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approaches have been proposed for the selection of an appropriate nature-inspired texture pattern. AHP is used for the formulation of decision-making matrix and criteria weight calculations and ranking of alternatives is done by three methods. Spearman’s correlation compared and found positive relations between rank assigned by methods. Experimental validation is done in Lathe for selected texture effects. Findings The texture parameters C-1 (Width of texture) and C-2 (Depth of texture) are found significant, while T-2 (Blended Krait) and T-6 (Banded Racer-1) texture is found optimal to generate on cutting tool surface. Research limitations/implications Only some nature-inspired texture patterns have been recognized before the selection; an infinite number of textures are available in nature. The size of the texture pattern is difficult to identify by the selection process because each texture pattern may have different effects on tribological surfaces. Practical implications The proposed selection methodology of nature-inspired texture patterns will help identify optimal texture geometry for specific tribological applications. The nature-inspired texture patterned tool has a significant impact on the cutting force and temperature due to its tribological effect on the cutting tool surface; it decreases the power required for machining. The machining characteristics like roughness are found to decrease by using nature-inspired texture patterned tools. Social implications Various nature-inspire texture studies to generate specific effects on the tribological surfaces may be started study for the surface of aircraft, ships, bearings, etc. Small and big fabrication industries may benefit by decreasing the cost of machining using nature-inspired texture-patterned tools. Research society will pay attention to nature’s inspiration. Originality/value Novel snake-skin-inspired texture patterns are recognized and hybrid MCDM methods are proposed to select optimal texture pattern. Proposed method used single time normalization to effectively rank the alternatives. The insights gained from this research can be extrapolated to address similar challenges in selecting nature-inspired textures for various applications. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0163/

Cost and Efficiency analysis of the Secondary electric machine in a CRAFT wind turbine

Abstract Floating offshore wind turbines are ideal for deeper waters, providing access to stronger and more stable winds. The Counter-Rotating Axis Floating Tilting (CRAFT) turbine features a unique design with two counter-rotating turbines on a tilted vertical shaft and two independent electrical machines submerged below sea level. The primary generator, connected to both turbines, includes counter-rotation which doubles the relative torque, while the secondary machine controls the upper turbine. This study examines the impact of primary and secondary machine efficiency on electricity generation. The findings indicate that the primary generator’s efficiency is crucial for system stability, whereas the secondary machine’s efficiency is less critical. Reducing the secondary machine’s efficiency from 97% to 83% resulted in a 0.1% reduction in annual electricity generation. Despite the asynchronous machine’s lower efficiency, it is the economically favorable choice as the secondary machine over its synchronous counterpart due to its reduced design complexity and lower magnet costs, leading to lower overall expenses. Future research investigate how turbulent flow effects and airflow interactions between the turbines influences the model. Incorporating the cooling factor, a more comprehensive cost model and a refined dynamic stall model will also further improve the simulation’s accuracy and robustness.

Fragmentation characteristics of abrasive particles for hard rock drilling with waterjet energy parameter

The use of abrasive waterjets (AWJs) for rock drilling offers advantages in urbanized areas, locations that are vulnerable to damage, and piling operations. However, the overall operational cost of AWJ systems remains high compared to that of conventional drilling methods, which constrains the long-term industrial application of AWJs. For instance, the abrasive costs account for over 60% of the total process cost, but the recycling of abrasives remaining after drilling could significantly reduce machining costs. In this study, the post-impact characteristics of abrasives were explored, aiming to enhance their recyclability. The physical properties and particle distribution of used abrasives vary depending on the jet energy, ultimately affecting their recyclability and recycling rate. The particle properties of used abrasives (particle size distribution, particle shape, and mean particle size) were compared under different waterjet energy variables (standoff distance (SOD) and water pressure) and test conditions (dry and underwater). Furthermore, the collision stages of the abrasive particles within a waterjet system were classified and analyzed. The results revealed that abrasive fragmentation predominantly occurred due to internal collisions within the mixing chamber. In addition, an attempt was made to optimize the waterjet parameters for an economical and efficient operation. The findings of this study could contribute to enhancing the cost-effectiveness of AWJ systems for rock drilling applications.

Determinants of net value added to produced and processed paddy rice in South East, Nigeria

The study principally examined the determinants of net value added to produced and processed paddy rice in South east Nigeria It specifically, identified the socio-economic characteristics of the respondents, analyzed the determinants of net value added to produced and processed paddy rice as well as ascertained the constraints to processed and produced paddy rice. Multi-stage sampling technique involving purposive and random sampling methods was used to select 240 respondents. Primary data were collected on rain-fed production season using structured questionnaires administered to the respondents by personal interview. Descriptive statistics,, multiple regression and principal component analysis were used to analyze the data. Results obtained showed that gender distribution of the respondents was 63%males and 38% females. More respondents are between the ages of 41-50 and31-40 respectively and house hold size of 4-6 .Farming experience showed that 136 respondents representing 57% had engaged in the business between 11-20yrs.The results also showed that 67% of the respondents accessed farm credit while 25% did not.66% of the respondents belonged to farmers association while 75% were not visited by extension agents. Variables (age, gender, years in school, household size, years of experience, training/extension visits, costs incurred, value addition technique and market price) significantly influenced the net value added while marital status, membership of cooperative, and access to credit did not. Constraints to paddy producers and processors were accessibility to farm machine, poor infrastructure and scarcity/high cost of labor, low access to credit/grant; low proactive measures to flood and drought control; insufficient knowledge of agro-chemicals, and late provision of essential training and services; and processors: use of outdated rice milling machines, high cost of modern rice processing machines, low access to modern rice processing machineries and low acceptability of local rice. Recommendations include; establishment of farm machinery hiring centers for producers and supply of modern rice milling machines to rice processing clusters, development of dams and irrigable lands, training and re-training on access to fund, utilization of biodegradable wastes from paddy rice, proactive measures of flood and drainage control, adequate use of agro-chemicals, use of modem techniques, and involvement of National Agency for Food and Drug Administration and Control in quality control. Keywords: Agriculture, Paddy Rice, Value Addition, Nigeria.

Comparative Study Of Keratometer And Autorefractometer For Non-Invasive Tear Break-Up Time Measurement In Rural Settings

Tear break-up time (TBUT) is a crucial indicator of ocular surface health, often used in diagnosing dry eye syndrome. Traditional assessment methods may not be accessible in rural areas due to the high cost of advanced diagnostic machines. This study investigates the reliability and accuracy of keratometers and autorefractometers for measuring non-invasive TBUT in a cohort of 200 patients. Our findings indicate a strong correlation between TBUT values from these tools and the conventional invasive TBUT test, demonstrating their potential utility in resource-limited settings

Enhancing Coconut Processing Efficiency: Design and Evaluation of A Cost-Effective Coconut De-Husking Machine

Coconut (Cocos nucifera) plays a crucial role in agricultural economies, particularly in coconut-producing regions, where traditional de-husking methods are labor-intensive and time-consuming. This study focuses on the design, fabrication, and evaluation of a coconut de-husking machine aimed at improving processing efficiency, reducing labor demands, and increasing throughput. The machine was designed to address key performance factors such as frame stability, blade strength, and spring tension. Testing demonstrated that the machine consistently outperformed manual methods, reducing de-husking time to an average of 96.4 seconds compared to 164.8 seconds for traditional techniques. The machine achieved an efficiency rate of 80%, with a throughput capacity of 0.0086 kg/s, significantly higher than the manual method's 0.005 kg/s. Additionally, the machine's cost, approximately N32,000, makes it accessible to smallholder farmers, offering a practical solution for improving productivity and sustainability in coconut farming. The study highlights the potential for mechanized de-husking to transform traditional practices, reduce labor costs, and contribute to economic growth in coconut-rich regions. Future research should explore further optimization of the machine design and its adaptability to different coconut varieties and moisture levels, ensuring broad applicability in diverse farming contexts.

Enhancing Surface Quality and Tool Longevity in EDM of D2 Steel Using Copper Composite Tools

Hard material machining and die manufacture are the main applications for electrical discharge machining (EDM). For EDM, conventional electrode materials include graphite, steel, brass, pure copper, and alloys based on copper. Unfortunately, excessive tool wear is a common problem with these materials, which raises the cost of machining. In this investigation, hardened D2 steel was machined using a composite tool made of 90% copper and 10% silicon carbide. The powder metallurgy method was used to create the composite tool. Surface roughness (SR) and electrode wear rate (EWR) were compared to a number of process variables. For experimentation, a response surface methodology based on CCD design in design of experts software was used. SR and electrode wear rate models were created using the CCD approach. Utilizing analysis of variance, the most important factors and their effects on EWR and SR were determined. The lowest tool wear rate of 0.39 gm/min is achieved with a current of 5 Amps, a pulse duration of 100 µs, and a pulse interval of 10 µs with an R2 of 0.9957, which accounts for 99.57% of the variability, the tool wear rate model fits the data very well and obtained lowest surface roughness of 2.8 µm.

Exploring the machined surface characteristics of Haynes 25 superalloy: Cost mitigation and quality enhancement perspective

The current study investigates the surface characteristics and machining cost of electrical discharge machining (EDM) of Haynes 25 superalloy using tools made by additively manufactured CuCr1Zr, pure copper and graphite. Before assessing machinability, the workpiece and tool materials were characterized using Energy Dispersive Spectroscopy (EDS), X-ray Diffraction (XRD) and evaluations of tensile strength, micro-hardness, density and thermal conductivity. The effects of current (I), voltage (V), pulse duration (Ton), duty cycle (τ) and flushing pressure (Fp) is analyzed on surface characteristics viz. surface roughness (SR), surface crack density (SCD), recast layer thickness (RCT), heat-affected zone (HAZ), micro-hardness (MH) and machining cost (MC). Post machining XRD analysis revealed the formation of cobalt oxides like (CoO and Co3O4) affecting the micro-hardness of the machined surface. Alongside, a field emission scanning electron microscopy (FESEM) is carried out which confirms, the deposition of metal carbides and oxides on the EDMed surface. Current and pulse-on-time significantly influenced performance, with optimal EDM parameters identified and validated through confirmative experiments, resulting in a mean error of ∼2.84 %. It is seen that the use of additively manufactured CuCr1Zr tools resulted in improved machined surface characteristics and a more cost-effective approach for producing intricate profiles with minimal surface defects.

Effective machine lifespan management using determined state–action cost estimation for multi-dimensional cost function optimization

ABSTRACT This study introduces a comprehensive framework designed to enhance production efficiency by integrating maintenance strategies, energy costs, and production specifications. This integration is achieved through a novel empirical method for estimating state–action costs, suitable for both machines with measurable and non-measurable states-of-health. We address the challenge of under-determination in state–action cost optimization by employing a k-means clustering approach, ensuring robustness and applicability. Utilizing an adapted SARSA algorithm, our framework optimally controls shop-floor machinery to minimize the global cost function. The efficacy of the state–action cost estimation method is validated using NASA’s C-MAPSS dataset. Additionally, the optimization strategy is further corroborated through its successful implementation in an autonomous mining cart model on the shop floor. Our results highlight the framework’s ability to optimize machine lifetime and production processes effectively, providing tailored solutions that adapt to varying operational conditions without depending on predefined machine degradation models and costs.

Geometric Benchmarking of Metal Material Extrusion Technology: A Preliminary Study

Metal additive manufacturing technologies such as powder bed fusion (PBF) and direct energy deposition (DED) are experiencing fast development, due to the growing awareness of industries. However, high energy consumption, slow production processes, and high costs of both machines and feedstocks hamper their competitiveness, compared to conventional manufacturing techniques. Metal material extrusion (metal-MEX) can represent a cost- and energy-effective alternative for metal additive manufacturing. This article aims to assess the potential of such technology by addressing uncertainties related to product design and process stability through a preliminary geometric benchmarking study. The geometric tolerances and minimum achievable sizes of some simple geometries produced in 316L stainless steel were evaluated using geometric benchmark test artifacts (GBTAs). Process maps were also proposed to forecast the feasibility of achieving acceptable values of the investigated tolerances, based on the nominal dimensions of the features.

Multicriteria Optimisation of Machining Operations Using a Spreadsheet Model

The rapid development of new materials and tools demonstrates the need for efficient and feasible machining processes. Modern production systems must guarantee sustainable, flexible, productive and high-quality production at low cost. Therefore, the combination of technological data with advanced software solutions is very important, especially when using complex CNC machining systems, where the reliability of the technological information is crucial, as simple measures can make a very positive contribution to the productivity achieved. When optimising the machining parameters, costs and machining time must be taken into account. The article deals with the optimisation of the turning process with a large number of influencing variables (machine, workpiece material, tool, cutting parameters, costs, etc.) and two objectives: the fastest possible machining (minimisation of machining time) and the lowest possible machining costs. The model is designed in an Excel spreadsheet and the multi-criteria optimisation is carried out using the approximation method. Step by step, we can find the optimal processing regime for each selected case.

МЕТОДИКА ВЫБОРА РЕСУРСОСБЕРЕГАЮЩИХ ОРГАНИЗАЦИОННО-ТЕХНОЛОГИЧЕСКИХ РЕШЕНИЙ НА ЭТАПЕ ЗАВЕРШЕНИЯ ЖИЗНЕННОГО ЦИКЛА ЗДАНИЙ

The article discusses the main aspects of resource and energy conservation at the stage of completion of the life cycle of buildings. It is shown that the stage of completion of the life cycle is extremely important for buildings and other capital construction projects and requires a systematic approach to the choice of organizational and technological solutions for the liquidation or reconstruction of the building. The concept of the final stage of the life cycle of buildings has been clarified. The importance of making resource-saving organizational and technical decisions taken at the stage of completion of the life cycle of buildings is shown. Indicators have been developed for making appropriate organizational and technical decisions. The methodology of choosing organizational and technological solutions at the stage of completion of the life cycle of buildings, taking into account resource conservation, is presented. The methodology includes several stages, the results of which are a star-shaped infographic model of the values of organizational and technological solutions, which is created at the stage of completion of the life cycle of buildings. The methodology takes into account the indicators of resource and energy consumption for the implementation of various organizational and technological solutions. Calculation formulas for use in the infographic model are proposed: material consumption, labor costs of workers, financial costs labor costs of construction machines and mechanisms energy intensity of construction reconstruction. The proposed model is used to evaluate and select options for the feasibility of reorganizing buildings at the end of their life cycle, taking into account resource and energy conservation.

Sustainable optimization of micro-milling machining parameters considering reliability assessment

Micro-milling is a crucial machining technology used for complex and precise 3D parts and plays a crucial role in modern manufacturing. In this work, to comprehensively evaluate the safety, economic feasibility, and environmental friendliness of the micro-milling processing process, a sustainable optimization framework including reliability assessment is designed. Firstly, modeling and experimental measurements are conducted on sustainability evaluation standards such as tool life, machining process, machining surface quality, material removal rate, machining cost, and carbon emissions. Subsequently, the influence of physical information such as observation/measurement data and processing errors is analyzed, and a Bayesian update method is proposed and integrated with neural networks to precisely inversion the probability distribution of parameters within the optimization cycle under conditions of uncertainty. Finally, combined with the overall sustainability indicators, the multi-objective optimization process is refined through penalty functions and weighting methods, aiming to achieve the best balance between processing performance and sustainability. The simulation and experimental results have verified the superiority of the developed framework, and the present method provides valuable guidance for sustainable micromanufacturing.

Mathematical models and an effective exact algorithm for unrelated parallel machine scheduling with family setup times and machine cost

Mathematical models and an effective exact algorithm for unrelated parallel machine scheduling with family setup times and machine cost