{"title":"A new characterization methodology for assessing machinability through cutting energy consumption","authors":"","doi":"10.1016/j.cirpj.2024.10.008","DOIUrl":"10.1016/j.cirpj.2024.10.008","url":null,"abstract":"<div><div>Improving machinability has consistently been an essential research topic in the machining community. However, a rapid and effective method to characterize machinability from the fundamental essence of machining is still lacking. This work proposed a new characterization methodology for assessing machinability from the principle of cutting energy consumption. An original Drop Hammer based Orthogonal Cutting (DHOC) test machine driven by gravitational potential energy was developed to conduct the machinability test. Using the Cutting Distance with Equal Energy (CDEE) method, machinability can be assessed by measuring the cutting distance without expensive measuring apparatus. Therefore, the cutting distance indicator can simplify the test procedure. Meanwhile, the CDEE method avoids the necessity for precisely calculating the consumptions of various complex cutting energies. Moreover, in-situ measurements coupled with the Digital Image Correlation (DIC) technique and Electron Back-Scattered Diffraction (EBSD) characterizations were utilized to evaluate the deformation characteristics and surface integrity during the CDEE tests. The proposed CDEE method has been validated from three aspects involving materials, cutting tools, and surface modification technology. Furthermore, a machinability optimization procedure based on the CDEE method has been proposed. The cutting distance indicator was used as an optimization objective for optimizing technology parameters to improve machinability. This CDEE method based on the DHOC test machine proved to have high application potential for the characterization and optimization of machinability.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Layer-level fabrication of continuous functionally graded materials (cFGMs) via Powder Bed Fusion – Laser Beam technology","authors":"","doi":"10.1016/j.cirpj.2024.10.009","DOIUrl":"10.1016/j.cirpj.2024.10.009","url":null,"abstract":"<div><div>Multi-material fabrication of metals through Additive Manufacturing (AM) processes is attracting more and more attention in recent years. This work presents a novel methodology that enables the fabrication of continuous functionally graded materials (cFGMs) at the layer level using Powder Bed Fusion – Laser Beam (PBF-LB) technology. This has been achieved by designing and building a customized powder separation system that can be easily installed on a currently operating PBF-LB system with a blade/roller-based powder spreading technique (extremely limited for layer-level multi-material fabrication). This technique overcomes one of the main drawbacks of AM multi-material fabrication by properly joining materials with very different mechanical properties and low compatibility, thus extending the productive capacity of this technology. Two steels, AISI 316 L and 18 Ni Maraging 300, with different physical, chemical and mechanical properties, were used to study the applicability and verify the proposed methodology. A high-resolution optical system was used to monitor, layer by layer, the different laser-matter interactions given by the different materials and thus the presence of a graded transition zone between them. Results in terms of statical mechanical properties, microstructure, chemical analysis and optical monitoring showed that the proposed solution is reliable and cost-effective, paving the way for future applications.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Assessment of cutting force coefficient identification methods and force models for variable pitch and helix bull-nose tools","authors":"","doi":"10.1016/j.cirpj.2024.09.010","DOIUrl":"10.1016/j.cirpj.2024.09.010","url":null,"abstract":"<div><div>The mechanistic approach is commonly implemented to predict and optimise the cutting forces in milling processes to prevent tool breakages, reduce tool wear, reduce form error, and improve surface quality. To implement this method, the cutting force coefficients (CFCs), that characterise the mechanics of the process, must be calculated. This study compares the accuracy of the predicted cutting forces for variable pitch and helix bull-nose milling tools using a rapid testing (RT) optimisation-based mechanistic CFC identification method that only requires a single angular cut with increasing radial engagement to the traditional mechanistic approach that requires several straight cuts. Along with developing a hybrid technique that combines variation in feed rate and radial engagement. The traditional radial, tangential, and axial (RTA) force model is also compared with the frictional and normal rake face (UV) force model that is independent of the local tool rake and inclination angles which is a necessary for bull nose tools. The RT and the developed hybrid CFC identification method with the UV force model predicted the average <span><math><msub><mrow><mi>F</mi></mrow><mrow><mi>x</mi></mrow></msub></math></span>, <span><math><msub><mrow><mi>F</mi></mrow><mrow><mi>y</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>F</mi></mrow><mrow><mi>z</mi></mrow></msub></math></span> cutting forces to within 7.1 %, 4.3 %, and 3.8 % error, respectively. These methods were slightly less accurate than the traditional method, however they have significant industrial benefits because they have can be used to identify CFCs with either a single cut, or from any tool-path with chip-load variation, respectively. The RTA force model predicted the average cutting forces similarly to the UV force model, however, the UV force model had lower errors using the rapid RT testing method at the extreme corners of the experimental design space.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Worker-centered evaluation and redesign of manufacturing tasks for ergonomics improvement using axiomatic design principles","authors":"","doi":"10.1016/j.cirpj.2024.10.001","DOIUrl":"10.1016/j.cirpj.2024.10.001","url":null,"abstract":"<div><div>Humans are considered the most valuable resource in manufacturing systems thanks to their craftsmanship, dexterity, and autonomy significantly affecting productivity, quality, and the overall company competitiveness. This paper introduces the SAGE (Systematic Approach to Generating Ergonomic Manufacturing tasks) methodology, a structured approach based on Axiomatic Design principles to integrate Human Factors evaluation early in the operations design phase and redesign manufacturing tasks to improve operators well-being. The primary objective is to mitigate discomfort and safety risks that often lead to musculoskeletal disorders, absenteeism, and production delays. SAGE provides a comprehensive framework for assessing ergonomic aspects of manufacturing tasks and identifying the need for redesign. It offers a detailed set of Functional Requirements (FRs) for reference, assesses FR satisfaction, evaluates task complexity using the Independence Axiom, and examines the intensity of FR satisfaction through the Information Axiom. The methodology includes specific implementation guidelines, ensuring its applicability across diverse manufacturing contexts. Its effectiveness is demonstrated through a large-scale parts assembly case study inspired by the bus and coach industrial sector, where a production engineer evaluated a windows assembly task and identified ergonomic design interventions. A comparative analysis with other relevant methods is finally presented, highlighting the approach's effectiveness.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Experimental evaluation of 5G performance based on a digital twin of a machine tool","authors":"","doi":"10.1016/j.cirpj.2024.09.012","DOIUrl":"10.1016/j.cirpj.2024.09.012","url":null,"abstract":"<div><div>The 5G mobile communication standard can potentially meet the networking requirements for different industrial use cases simultaneously due to the promised low latency, high bandwidth, and high device density while providing a high quality of service. These capabilities enable the realization of digital twins (DTs) that are based on edge computing for time- and safety-critical wireless applications. However, the investigation of the applicability of 5G for DTs in real-world manufacturing scenarios is still lacking. In this work, we have evaluated a DT based on edge-computing and 5G mobile communication using extensive experiments. We have focused on the communication technology and requirements needed to enable functionalities on edge devices. The key contribution of this paper is a comprehensive experimental study on 5G performance characteristics in an existing manufacturing system. Moreover, the influence of 5G on the functionality of the edge-based DT is evaluated and discussed. Full factorial experiments with different network configurations are designed and conducted. The performance of communication characteristics (latency, jitter) is evaluated as well as the impact on the continuity between real and digital processes. The results are also compared with the WiFi standard by experimental evaluation. At last, the limits of current 5G networks for manufacturing are discussed.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Physics-supported Bayesian machine learning for chatter prediction with process damping in milling","authors":"","doi":"10.1016/j.cirpj.2024.09.014","DOIUrl":"10.1016/j.cirpj.2024.09.014","url":null,"abstract":"<div><div>Chatter stability of milling operations is a complicated phenomenon causing serious productivity issues in the manufacturing industry, yet a shop-floor implementable solution is lacking. This paper follows a physics-supported Bayesian machine learning approach and incorporates the potential effect of process damping on the stability of the process. Using a likelihood function based on the Nyquist stability criterion, the learning system monitors the actual stability state of the process during arbitrary cuts and refines the underlying model parameter uncertainties in the structural dynamics, cutting force coefficients, as well as the process damping. The framework can operate with limited training data and display the remaining uncertainties in stability predictions to the machine operator. Experimental case studies show the effectiveness of the proposed method and highlight the importance of considering process damping for certain endmills.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Numerical modelling and experimental investigations to predict the tool wear of copper electrodes during µ-EDM process","authors":"","doi":"10.1016/j.cirpj.2024.09.011","DOIUrl":"10.1016/j.cirpj.2024.09.011","url":null,"abstract":"<div><div>The micro electrical discharge machining (µ-EDM) process is one of the most widely used techniques to produce miniaturized components in micro-electro mechanical system (MEMS) applications due to its inherent advantages. This work investigates the wear phenomena and the morphology of the copper electrodes during the micro-die sinking process. A numerical model of a single spark is developed assuming the Gaussian distribution of heat flux to estimate the crater dimensions formed in the copper tool electrode (tool wear) used as a result of electric discharge. The crater dimension attained from the ABAQUS finite element model is validated with experimental results using a single spark test setup. Moreover, the effect of input parameters namely capacitance and voltage on the electrode wear rate and surface roughness is also studied. The crater dimensions from the single discharge study are used to formulate the wear model for different possibilities of crater distribution, such as non-overlapping craters, craters with less than 30 % overlap, and 50 % overlap. The electrode wear rate (EWR) also displayed a decline from 20.4 % to 11.6 % and further to 8 % when the overlap was permitted up to 30 % and up to 50 % for the wear model respectively. The developed model results are further compared with experimental results in terms of the electrode wear rate and depth of erosion and the deviations are found to be 20.33 % and 20.55 % respectively</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A real-time dual NURBS interpolator with optimised control of flexible acceleration and deceleration for five-axis CNC machining","authors":"","doi":"10.1016/j.cirpj.2024.09.015","DOIUrl":"10.1016/j.cirpj.2024.09.015","url":null,"abstract":"<div><div>The limited computing capacity makes it difficult to plan a suitable feedrate profile in real-time for high speed and high accuracy machining of five-axis parametric toolpaths. In this paper, a real-time interpolation algorithm with optimised control of flexible acceleration and deceleration (acc-dec) for the dual NURBS toolpath is proposed. The toolpath is marked as subsegments with similar geometric properties by introducing the five-axis curvature. Machine kinematic and toolpath geometry constraints are considered in the kinematic parameter constraint model. Initial feedrate profiles are solved in a dynamic 3D window which preserves the motion performance of machine tools to a great extent. Convolution is used to smooth the initial feedrate profile to achieve a higher order continuity over the global range. Feedrate fluctuations caused by imprecise parameter interpolation are eliminated through modifying each interpolation periods. Resampling adjusts the position of interpolation points and unify the interpolation periods. All operations mentioned are in series and real-time is strictly guaranteed. Effectiveness of the developed algorithm is validated in simulations and also experimentally on a Self-developed-NC controlled 5-axis machine tool.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Tool wear prediction based on SVR optimized by hybrid differential evolution and grey wolf optimization algorithms","authors":"","doi":"10.1016/j.cirpj.2024.09.013","DOIUrl":"10.1016/j.cirpj.2024.09.013","url":null,"abstract":"<div><div>Tool wear prediction is key to ensuring product quality and machining efficiency. However, the prediction results of most models are unstable or inaccurate. To address the issues, a tool wear prediction model, based on support vector regression which was optimized by differential evolution and gray wolf optimization algorithms, was proposed in this paper. The method optimized the parameters of support vector regression model through differential evolution and grey wolf optimization algorithms to make the model more balanced in terms of its global and local search capabilities. First, the vibration and power signals were collected by sensors during the milling processes. Then, the features extraction and features selection were performed on the vibration and power signals. Next, the proposed model was developed and trained. Finally, the tool wear was predicted using the proposed model. The results showed that the proposed model had better performance than other models in terms of prediction accuracy and prediction efficiency, and it was applicable to the condition of multiple cutting parameters with generalizability, which will provide some valuable technical support for machining.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigation of the effects of CO2 pre-cooling on the cooling capacity for cryogenic cooling in machining operations","authors":"","doi":"10.1016/j.cirpj.2024.09.007","DOIUrl":"10.1016/j.cirpj.2024.09.007","url":null,"abstract":"<div><div>Liquid carbon dioxide (LCO<sub>2</sub>) based cryogenic cooling has shown promising results in terms of wear reduction, productivity increase and energy efficiency when machining high-temperature materials. For process-safe use with low pulsation, CO<sub>2</sub> must be fed in the liquid state to cool the process zone. LCO<sub>2</sub> is typically stored in riser bottles in which gaseous and liquid aggregate state coexist. A preliminary study has already shown that the liquefied state of the CO<sub>2</sub> can be stabilized by pre-cooling. In this paper, the influence of a heat exchanger as a pre-cooling system on the cooling capacity of the CO<sub>2</sub> is investigated and the required energy consumption is compared to unstabilized CO<sub>2</sub>, pressure increased CO<sub>2</sub> and compressed air. It has been shown that pre-cooling leads to a more energy-efficient increase in the cooling capacity of the CO<sub>2</sub> compared to pressure increased CO<sub>2</sub>.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755581724001445/pdfft?md5=c0639d136231d10500c10ba7297156ac&pid=1-s2.0-S1755581724001445-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}