NC Processing Research Articles

NC process information mining based optimization method of roughing tool sequence selection for pocket features

The appropriate and intelligent selection of roughing tool sequence for pocket features is essential to improve the efficiency of NC machining. However, there exist few researches exploring how to discover and utilize the valuable NC process information imbedded in 3D CAD models. In this paper, a NC process information mining based optimization method of roughing tool sequence selection for pocket features is presented. Firstly, the medial axis transform (MAT) is introduced to represent the tool paths of a pocket feature, and corresponding parameters of MAT are calculated. Secondly, considering the restrictions of tool movements during machining, the mapping mechanism between geometry and NC process is elaborated based on MAT to reveal the association of 3D CAD models and NC machining. The deeper information for NC process planning is mined to reflect the machining procedure feasibly. Then, the multi-objective optimization model is constructed by considering material removal amount and cutting consistency synthetically. Moreover, the precedence and distances between roughing tools are formulated in a Candidate Tools Graph (CTG). Finally, a hybrid ant colony algorithm (ACA) and simulated annealing (SA) approach based on CTG is proposed to generate the global optimal roughing tool sequence. In the experiment, various pocket features are conducted to illustrate the application effectiveness of the proposed method. The experimental results show that our method can achieve highly satisfactory results and outperforms other approaches.

Blockchain-based application for NC machining process decision and transaction

In the field of NC process design, a large number of designers or manufacturing enterprises have provided a wealth of crowd intelligence resources. However, the lack of organizational methods for the knowledge contained in a large number of machining process data makes it impossible to effectively utilize the machining process knowledge. At the same time, due to the intellectual property protection of machining process, process knowledge cannot be freely shared among designers and manufacturing enterprises, which makes the process design system limited in knowledge that can be applied and difficult to break through and improve. To counter this problem, a blockchain-based NC machining process decision and transaction approach is proposed. First, the process knowledge repositories in the process design consortium are structurally characterized by the probability graph structure to support the automatic decision-making of process schemes; Then, process design requirements are transmitted to each process design node in the consortium through the blockchain; Then, according to the process design requirements, the process scheme is determined in each node with the process design capability of such parts through depth first search and probability calculation; Finally, the process schemes are fed back to the demander through the blockchain to achieve the purpose of transaction and knowledge protection. The effectiveness of the proposed method is verified by the test of actual parts.

An inexact subgraph matching algorithm for subpart retrieval in NC process reuse

With the wide application of CAD/CAM technology, huge amounts of process data are generated each year, which are valuable to be referred to and reused. For the reuse of these historical process data, the retrieval of the subpart model is the key, as similar structures usually correspond to similar NC processes. However, the existing subpart retrieval methods are only practical to the parts with simple structures or fixed geometry. This research proposes a subpart model retrieval method based on inexact subgraph matching, which can be used for parts of arbitrary complexity. By representing the part model as an attribute graph, the task is first transformed into an inexact subgraph matching task where some degree of matching difference is accepted to retrieve similar subparts. Next, this research proposes VF3-light-N, an inexact subgraph matching algorithm that operates on attribute graphs. The idea of VF3-light-N is to quantify the mismatch of both nodes and edges based on matching error first. Then use the empty map to remove the nodes that cannot be matched, so that the remaining nodes and edges can be matched exactly. Thus, VF3-light-N can search out all the matched subgraphs within a certain noise threshold. A case study based on aircraft structural parts is carried out, and the result shows that the proposed method can efficiently retrieve subparts from complex part models. Furthermore, it is believed that VF3-light-N can be also used in other inexact subgraph matching applications, such as feature recognition.

Processing Method of Rectangular Unequal Distance Thread

With the improvement of the social demand for our daily life, the products needed in our life are getting higher and higher, and the requirements for the mechanical structure and functions need to be constantly improved, which leads to an increase in the demand for unequal distance threads. This will further improve the processing technology and processing efficiency of unequal distance threads. In the following, we will talk about the processing method of rectangular unequal distance threads, focusing on the basic idea of NC processing of unequal distance threads Programming skills, rough and finish machining methods in CNC machining, tool application.

NC process analysis–based intersecting machining feature recognition and reuse approach

NC process analysis–based intersecting machining feature recognition and reuse approach

Efficient NC process scheme generation method based on reusable macro and micro process fusion

Process reuse technology has been widely studied and applied in the manufacturing industry. However, the current NC machining process reuse generally assumes that the micro process is compatible with the macro process but, in fact, reusable processes from similar local structures from multiple parts are usually incompatible with each other when under the overall manufacturing requirements of the target parts. As a result, a large number of user interactions are still required for modification and adjustment in practical engineering applications and process reuse do not provide a significant improvement to the design efficiency. Therefore, an efficient NC process scheme generation method based on reusable macro and micro process fusion is proposed in this paper. Firstly, according to the calculation of semantic distance of process design intention, the micro process is mapped to the macro process to realize fusion of the two processes, and a compatibility credibility evaluation model is established to evaluate the fusion results. Then, when the fusion result is credible, the machining areas corresponding to the process scheme are adjusted and optimized at the geometric level. The adjustment and optimization of machining areas provides the integration of machining areas and the optimization of the machining sequence. Finally, the effectiveness and feasibility of the proposed method are verified through a test of example parts.

Study on Mechanical Properties of Lost Foam Pattern in Machining

Lost foam casting has special requirements on the process performance of molding machinery, and the processing technology of Lost foam casting pattern is one of the core and key technologies of Lost foam casting. The research status of lost foam pattern and the safety problems existing in the process of lost foam casting were analyzed. The mechanical properties of lost foam pattern and its mechanical property model were studied, which provided theoretical support for the research of numerical control processing and safe casting of lost foam pattern. The development of Lost foam casting pattern NC processing technology is conducive to the use of information technology, digital technology to enhance the technological progress of traditional industries, promote the clean production of Lost foam casting, realize energy saving and emission reduction, and promote the rapid development of mechanical equipment manufacturing industry.

Research on nxug10.0 impeller automatic programming and DMU50 five axis machining center

Taking nxug10.0 software as the platform and impeller as an example, this paper analyzes the structural characteristics and processing difficulties of impeller, reasonably formulates the NC processing scheme, and uses nxug10.0 impeller processing module to plan the tool path, generate the tool path file, and simulate the processing to verify the correctness of the tool path. The NC program of impeller is generated by special post processor and uploaded to DMU50 five axis NC machining center to complete the actual processing of impeller. Through the detection of impeller, the results show that the impeller fully meets the design and use requirements.

Associations between patient knowledge of others' experiences and treatment choice in men with localized prostate cancer.

6578 Background: Men with localized prostate cancer must select from multiple treatment options, without one clear best choice. Consequently, personal factors, such as knowing other prostate cancer patients who have undergone treatment, may influence patient decision-making. However, associations between knowledge about others’ experiences and treatment decision-making among localized prostate cancer patients has not been well characterized. We used data from a population-based cohort of localized prostate cancer patients to examine whether patient-reported knowledge of others’ experiences is associated with treatment choice. Methods: The North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS) is a population-based cohort of localized prostate cancer patients enrolled from 2011-2013 throughout the state of North Carolina in collaboration with the North Carolina Central Cancer Registry. All patients were enrolled prior to treatment and followed prospectively. Patient decision-making factors including knowledge of others’ experiences with prostate cancer treatment options were collected through patient report. Patient treatment choice was determined through medical record abstraction and cancer registry data. Results: Among 1,202 patients, 17% reported knowing someone who pursued active surveillance (AS) while 28%, 46%, and 59% reported knowing someone who received brachytherapy, external beam radiation (EBRT), or radical prostatectomy (RP), respectively; 26% underwent AS, 9% brachytherapy, 21% EBRT, and 39% RP as their initial treatment. In unadjusted analyses, patients with knowledge of others’ experiences with brachytherapy, EBRT or RP had more than twice the odds of receiving that treatment compared to patients who did not. Knowledge of others’ experience with AS was not associated with choice to undergo AS. Multivariable analysis adjusting for age, race, risk group, and patient-reported goals of care showed knowledge of others’ experiences with brachytherapy (OR 4.60, 95% confidence interval [CI] 2.76 to 7.68), EBRT (OR 2.38, 95% CI 1.69 to 3.34), or RP (OR 4.02, 95% CI 2.84 to 5.70) was significantly associated with odds of receiving that treatment. The odds of receiving a particular treatment option were further increased among patients who reported knowing someone who had a “good” experience with the treatment in question. Conclusions: This is the first population-based study to directly demonstrate the impact of a patient’s knowledge of others’ experiences on treatment choice in prostate cancer. These data provide a new consideration to clinicians in their counseling of patients with newly diagnosed prostate cancer, and also impacts research into the informed decision-making process for this disease.

Effect of income on patient decision-making in localized prostate cancer.

6552 Background: Socioeconomic status affects goals of care and treatment choices. We investigated the impact of low household income on diagnosis, goals of care, and treatment choice in patients with localized prostate cancer. Methods: The North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS) is a population-based cohort of prostate cancer patients identified at the time of diagnosis, enrolled from 2011-2013, and followed prospectively. Sociodemographic information and decision making factors including goals of care were collected by patient report. Patients were asked to rate the importance of quality of life, cure, burden to friends and family, cost, and effect on daily activity as well as which of these goals was the most important in their treatment decision making. Annual household income was stratified in to 3 levels: < 40K (low), 40-90K (middle),>90K (high). Results: Of 1382 patients, 539 (39%), 553 (40%), and 290 (21%) reported low, medium, and high household income. Lower income patients were less college educated, more frequently unemployed, and had higher rates of either no insurance or government sponsored insurances. Low income patients had higher PSA and worse clinical stage at diagnosis. In goals of care, low income patients more frequently rated high importance on burden (78.8% vs 76.0% vs 65.2% p<0.01) and cost of cancer (61.2% vs 38.5% vs 14.5% p<0.01), and factors other than cure as the most important treatment decision factor. While overall treatment rate at 1 year was similar by income group, the type of treatment differed. On multivariate analyses, adjusting for age, race, clinical risk group, employment, insurance, and treatment goal, high income was associated with increased odds of having surgery (OR 1.81, CI 1.16 – 2.81), and reduced odds of having radiation (0.60, CI 0.36-0.99). Conclusions: Poor patients with low household income have worse prostate cancer at diagnosis. These patients have different goals of care which impact their choice of treatment. These findings provide novel insight into disparities in diagnosis and outcome in prostate cancer.[Table: see text]

Mapping the Memorial Anxiety Scale for Prostate Cancer to the SF-6D.

To create a crosswalk that predicts Short Form 6D (SF-6D) utilities from Memorial Anxiety Scale for Prostate Cancer (MAX-PC) scores. The data come from prostate cancer patients enrolled in the North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS, N = 1016). Cross-sectional data from 12- to 24-month follow-up were used as estimation and validation datasets, respectively. Participants' SF-12 scores were used to generate SF-6D utilities in both datasets. Beta regression mixture models were used to evaluate SF-6D utilities as a function of MAX-PC scores, race, education, marital status, income, employment status, having health insurance, year of cancer diagnosis and clinically significant prostate cancer-related anxiety (PCRA) status in the estimation dataset. Models' predictive accuracies (using mean absolute error [MAE], root mean squared error [RMSE], Akaike information criterion [AIC] and Bayesian information criterion [BIC]) were examined in both datasets. The model with the highest prediction accuracy and the lowest prediction errors was selected as the crosswalk. The crosswalk had modest prediction accuracy (MAE = 0.092, RMSE = 0.114, AIC = -2708 and BIC = -2595.6), which are comparable to prediction accuracies of other SF-6D crosswalks in the literature. About 24% and 52% of predictions fell within ± 5% and ± 10% of observed SF-6D, respectively. The observed mean disutility associated with acquiring clinically significant PCRA is 0.168 (standard deviation = 0.179). This study provides a crosswalk that converts MAX-PC scores to SF-6D utilities for economic evaluation of clinically significant PCRA treatment options for prostate cancer survivors.

Care received by rural and urban patients with newly diagnosed prostate cancer: Results from a population-based prospective cohort.

203 Background: Rural residence is a source of disparity in cancer access and outcomes. It is not known to what extent rurality affects access to care in patients with prostate cancer. Methods: The North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS) is a population-based cohort of newly-diagnosed prostate cancer patients. Patients were enrolled from 2011-2013 through collaboration with the state cancer registry at diagnosis and followed prospectively. Urban/rural residence was defined by the rural urban continuum code (RUCC): 1-3 (urban) and 4-9 (rural). Medical records were collected and abstracted for prostate cancer care received. Individual-level sociodemographic information was collected by patient report. Results: Among 1,456 NC ProCESS participants with a median age of 65 years, 1089 were categorized as urban and 367 (25%) rural. This is a sociodemographically diverse cohort with 30.2% non-White (including 26.9% Black), 34.1% with high school education or less, and 37.3% with household income < = $40,000. The distance to travel for diagnostic scans was greater for rural patients (miles): CT (7.5 urban vs 17.1 rural, p = 0.07), MRI (8.1 vs 12.0, p = 0.04) and bone scan (6.8 vs 14.1, p = 0.009). However, there was no difference in the percent of patients who underwent CT (15.9% urban vs 12.8% rural, p = 0.15), MRI (7.8% vs 8.2%, p = 0.81) and bone scan (15.9% vs 19.4%, p = 0.13); or the percentage of patients with high risk or metastatic disease who had any staging scan (64.2% vs 66.6% p = 0.8). While all patients consulted with a urologist, rural patients were less likely to have had consultation with a radiation oncologist (42.4% vs 35.8%, p = 0.04). Rural patients were also more likely to report that treatment was more difficult due to travel, including robotic prostatectomy (6.8% vs 13.9% p = 0.001) and radiation therapy (8.01% vs 16.07%, p = 0.001). In patients with low risk cancer, rural patients were more likely to have reported treatment at 12 months (68.2% vs 58.7% p = 0.04) instead of surveillance or observation. For high risk patients, both rural and urban patients reported high rates of treatment by 3 months (96.3% vs 91.3%, p = 0.40). After adjustment for age, income, race, education and insurance, rural residence was associated with increased likelihood of receiving treatment at 1 year (OR 1.54, CI 0.99 – 2.39) in low risk patients, but not associated with receiving treatment at 3 months (OR 3.63, CI 0.24 -54.5) among high risk patients. Conclusions: In a population-based cohort, rural patients with prostate cancer have greater barriers such as travel distance, but similar proportions of rural and urban patients received staging scans and timely treatment for high-risk prostate cancer. Rural patients were less likely to receive multidisciplinary consultation prior to treatment, and were less likely to have surveillance for low risk disease.

A Modeling Method of Cylindrical Turning Processing Behavior

This paper put forward the theory of processing behavior through research on conceptual system of advanced manufacturing technologies and production modes such as cloud manufacturing and systematic classification of processing technology, and gave the concept of processing behavior primitive element. The processing behavior was classified and the relationship between different levels of processing behavior was clarified. To realize the standardization of NC processing technology for parts of automatic turning programming. Embed turning behavior into the design elements, realize the combination of design and manufacturing, shorten the time and space of coordination and product cycle, reduce product design and manufacturing costs, and achieve green, low consumption, high quality, high efficiency and effective manufacturing of turning parts.

Learning-Based Prediction of Pose-Dependent Dynamics

The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to vibrations, which can deteriorate the quality of the machined workpiece surface. The prediction of tool vibrations based on the used NC path and process configuration can be achieved by, e.g., applying geometric physically-based process simulation systems prior to the machining process. However, recent research showed that the dynamic behavior of the system, consisting of the machine tool, the spindle, and the milling tool, can change significantly when using different inclination angles to realize certain machined workpiece shapes. Intermediate dynamic properties have to be interpolated based on measurements due to the impracticality of measuring the frequency response functions for each position and inclination angle that are used along the NC path. This paper presents a learning-based approach to predict the frequency response function for a given pose of the tool center point.

Associations between prostate cancer-related anxiety and health-related quality of life.

BackgroundThere are uncertainties about prostate cancer‐related anxiety's (PCRA) associations with health‐related quality of life (HRQOL) and major depression, and these could affect the quality of mental healthcare provided to prostate cancer patients. Addressing these uncertainties will provide more insight into PCRA and inform further research on the value of PCRA prevention. The goals of this study were to measure associations between PCRA and HRQOL at domain and subdomain levels, and to evaluate the association between PCRA and probable (ie, predicted major) depression.MethodWe analyzed secondary cross‐sectional data from the North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS—a population‐based cohort of prostate cancer patients enrolled shortly after diagnosis [between January 2011 and June 2013] and followed prospectively). Patient‐reported measures of PCRA and HRQOL from 1,016 enrollees who participated in NC ProCESS’s 1‐year follow‐up survey were assessed. Outcomes of interests were a) linear correlations between contemporaneous memorial anxiety scale for prostate cancer (MAX‐PC) and Short Form 12 (SF‐12) scores, and b) measures of association between indicators of clinically significant PCRA (ie, MAX‐PC > 27) and probable depression during survey contact (ie, SF‐12 mental component score ≤43).ResultsPCRA measures had notable associations with SF‐12’s mental health subscale (assesses low mood/nervousness [rho = −0.42]) and emotional role functioning subscale (assesses subjective productivity loss [rho = −0.46]). Additionally, the risk of probable depression was significantly higher in participants with clinically significant PCRA compared with those without it (weighed risk ratio = 5.3, 95% confidence interval 3.6‐7.8; P < .001).ConclusionProstate cancer patients with clinically significant PCRA should be assessed for major depression and productivity loss.

Design and optimization of energy-efficient milling processes using a geometric physically-based process simulation system

The increasing complexity of production processes, shortening product lifecycles and rising energy costs lead to an emerging need for an efficiency optimization approach including process simulations in factory adaption planning as well as in process planning. This paper presents a method for the design of milling processes by analyzing process times, energy consumption and process stability based on process simulations. By evaluating simplified virtually conducted processes, reasonable parameter value combinations can be selected efficiently and provide flexibility by generating multiple solutions. Using detailed process simulations and conducting iterative adjustments to ensure a sufficient workpiece quality, the selected parameter sets are transferred to actual NC processes.

Study on multi-axis simulated NC machining for thin-walled impeller

Thin-walled impellers are widely used in aerospace and other high-end manufacturing industries However, the machining of thin-walled impeller is a difficult problem. In this paper, the simulated NC machining for thin-wall impeller with a wall thickness of 1.8 mm is presented. Firstly, the Three-dimensional model of thin-wall impeller with 18 blades is created in SolidWorks. The multi-axis NC machining processing for impeller includes is divided into four stages: roughing and grooving, finishing blade, finishing hub and finishing fillet. All the tool paths for the above-mentioned processing stages are planned by blade expert module in MasterCAM. The five-axis simulated machining for thin-walled impeller is carried out to detect abnormal phenomena such as tool collision by machine simulation module in MasterCAM. The study can simulate the real processing scene for multi-axis NC machining thin-walled impeller and improve the design of NC processing efficiency.

A complex network based NC process skeleton extraction approach

Process skeleton can effectively reflect the macro process constraints and key features of parts, which has rich reuse value. However, neither the automatic extraction of common reusable structures at geometric level nor the discovery of typical process routes at semantic level can effectively support the reuse of macro processes. To counter this problem, a novel complex network based NC process skeleton extraction approach is proposed. First, the characteristics for a good process skeleton are analyzed and the structured model for representing typical macro process based on CAM model data is elaborated. Then, given a set of structured NC machining process instances, the corresponding extraction approach is proposed, which includes three important phases: (1) constructing a NC machining process data network by using the machining process instances; (2) analyzing the topological metrics of the process data network to judge the key process element nodes and generating candidate process skeletons; (3) determining the final process skeletons by choosing those candidate process skeletons with moderate granularity and conforming to the specific process. Finally, the experimental results are presented to demonstrate the effectiveness of the approach. The presented approach can help smart machines reuse the machining know-how about cutting similar parts so that parameter settings can be updated automatically.

A multi-source similar subparts based NC process fusion and regrouping approach

As a vast number of 3D CAD models associated with NC process are generated each year, taking full advantage of them is an effective way to generate the NC process for query subparts with less time and lower cost. However, there has been little research on how to discover and utilize the valuable information imbedded in the NC process of multiple existing similar subparts. In this paper, a novel multi-source similar subparts-based NC process fusion and regrouping approach is proposed. Firstly, the multi-source similar subparts are described as multi-dimension vectors consisting of feature attributes and NC process. Secondly, the attribute similarities of query feature and similar features are calculated to establish the similarity matrix. Then, based on the multi-source similar features, the gray relational analysis is utilized to mine the association between feature attributes and NC process, and the relation matrix is constructed. Based on the multiplication of similarity matrix and relation matrix, the adaption matrix is calculated to represent the important degree of the NC process of similar features for query feature. Through the weighted sum of adaption values and adjustments, the NC process is obtained for the query subpart. Finally, based on the feature interactions in the query subpart, the NC process of the query subpart is regrouped to meet the requirements of NC machining.

An Effective Numerical Control Machining Process Optimization Approach of Part With Complex Pockets for Numerical Control Process Reuse

Recently, various process reuse technologies have come to be widely used in manufacturing. The existing methods mainly focus on searching and reusing similar NC processes. For the optimization of process schemes generated by reusable NC machining processes, however, no effective strategy has yet been proposed, especially when it comes to complex parts with intersecting features. To address this issue, we present, here, an effective NC machining process optimization approach of the part with complex pockets for NC process reuse. This approach involves two levels, that of the machining feature and that of the part. In the former case, the cutting tool and a cutting depth of the machining region is first optimized by making full use of the tool's machining capacity and avoiding air-cutting. In the latter case, the cutting sequence of the machining regions is further optimized in the macro process so as to maintain the efficiency of the process scheme. The effectiveness of the proposed approach is verified by a jag of the electronic product and an aircraft structural in our developed prototype system based on CATIA. The presented method can be integrated into commercial CAD/CAM software for rapid NC programming.