Smart Machine Health and Maintenance: Tool Assembly Prognostics

2008 ◽  
Author(s):  
Edzel R. Lapira ◽  
Amit Deshpande ◽  
Jay Lee ◽  
John Snyder
Keyword(s):  
High Speed ◽  
Manufacturing Industry ◽  
Learning Algorithm ◽  
High Volume ◽  
Third Party ◽  
Manufacturing Operations ◽  
Prognostic Application ◽  
Machine Health ◽  
Smart Machine ◽  
Tool Assembly

It is well-established that unbalance in tool assembly causes excessive loads on spindle bearings and tool wear and increased vibration levels. However, in the days where high-speed machining (HSM) has become a common practice in the manufacturing industry, methodologies to measure tool assembly unbalance are not developed. In HSM the effects are worse, as the unbalance force is directly proportional to square of the spindle speed. Common practice in industry is to balance the tool assembly either with in-house balancing machines or use third-party balancing services after every batch cycle. This paper describes a data-driven methodology that detects the presence of unbalance in a tool assembly relative to the tools with known balance levels. The unbalance detection prognostic application developed as part of the Smart Machine Platform Initiative (SMPI) checks for the threshold unbalance level in the tool assembly for the given machining requirements before the start of any run. This approach uses statistical tools and a supervised learning algorithm based on the Watchdog Agent® toolbox developed by the Center for Intelligent Maintenance Systems. The proposed research finds high applicability in high-precision manufacturing operations involving high-volume production.

The Green, Digital Clamping Device Composed of Self-Locking Power Screw Driven by the Servo Motor

2009 ◽  
Author(s):  
Yang Liu ◽  
Kangmin Zhong ◽  
Xiaoming Sheng ◽  
Mingdi Wang
Keyword(s):  
High Speed ◽  
Manufacturing Industry ◽  
High Volume ◽  
Energy Utilization ◽  
Servo Motor ◽  
High Volume Production ◽  
Volume Production ◽  
Basic Link ◽  
Clamping Device ◽  
The Cost

Fluid transmission, such as hydraulic and pneumatic, is widely used in the fixtures in modern industry. But there are some disadvantages in these fixtures. First, too much loops and turns in the hydraulic or pneumatic systems have lead to lower energy utilization ratio and complicated structure. Second, oil emission in hydraulic system may cause environment pollution, and the noise in pneumatic system may cause pollution too. Third, fluid system always needs electro-hydraulic or electro-pneumatic transform elements for digital intelligent control, which will add the cost and the complexity of system. In order to overcome this disadvantage, a new kind of mechatronics clamping device is designed innovatively, which is driven by servo motor and translated along the self-locking power screw. So it was very simple with little transmission elements and has no high-speed mechanic components. By changing the geometry shape of basic link, different requirements for clamping forces and clamping situations can be satisfied. This new kind of clamping device has prominent advantages in green and digital aspects. Moreover, it can meet perfectly the requirements of short-cycle, high-volume production in modern manufacturing industry.

scholarly journals The Spread of Droplets and Aerosols of Surgical Motor Handpiece Irrigation Using Different Suction Systems

2021 ◽  
Vol 2 ◽  
Author(s):  
James K. H. Tsoi ◽  
Hao Ding ◽  
Ki Hon ◽  
Yiu Yan Leung
Keyword(s):  
High Speed ◽  
Learning Algorithm ◽  
Irrigation System ◽  
Mouth Opening ◽  
High Volume ◽  
Dental Clinic ◽  
Single Operator ◽  
Droplet Sizes ◽  
Low Volume ◽  
Phantom Head

Objective: This study aimed to compare the effectiveness of various combinations of dental suction devices in reducing the amount and distance of spread of aerosols and droplets using an electrical surgical motor model with a self-irrigation system.Materials and Methods: In a standard single-chaired air-conditioned ventilated dental clinic, an electrical dental surgical motor with a high-speed handpiece (Implantmed) cooled with 0.2% fluorescein containing normal saline was used to drill a gypsum block mounted on a phantom head in a supine position. A single operator performed thrice each of the following suction settings: (a) no suction, (b) low-volume suction, (c) low-volume + high-volume suctions, and (d) low-volume + external oral suctions. Aerosols (0.1–5 μm) were measured with a particle counter at the mouth opening of the phantom head, and droplet sizes and distances were analyzed via a machine learning algorithm by identifying fluorescence droplets on pre-loaded pieces of paper on the floor for each group.Results: The different suction systems have different performances in terms of droplet distance (p = 0.007), whereas using (c) high volume suctions (41.1 ± 22.9 cm) and (d) external oral suction unit (39 ± 18.2 cm) had significantly reduced the spread of droplets when compared with (a) without suction (58.9 ± 17.1 cm). Using (d) external oral suction or (c) high volume suction could reduce the number for all droplet sizes. The use of (c) high volume suction was most effective in reducing aerosol count of 0.3–1 μm, while (d) external oral suction was most effective in reducing aerosol count of 3–5 μm.Conclusions: Both external oral suction and high-volume suction were effective in reducing aerosols and droplets generated by the irrigation of a surgical high-speed motor handpiece. External oral suction could be an effective alternative to high volume suction in dental surgical procedures to reduce the spread of aerosols and droplets.Clinical Relevance: External oral suction or high-volume suction should be used in conjunction with low-volume suction in surgical procedure to reduce the spread of aerosols and droplets in a dental clinic environment.

scholarly journals Study on the High-Speed Milling Performance of High-Volume Fraction SiCp/Al Composites

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4143
Author(s):  
Youzheng Cui ◽  
Shenrou Gao ◽  
Fengjuan Wang ◽  
Qingming Hu ◽  
Cheng Xu ◽  
...  
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Volume Fraction ◽  
Simulation Analysis ◽  
Cutting Temperature ◽  
High Volume ◽  
Cutting Parameters ◽  
High Volume Fraction ◽  
High Wear Resistance ◽  
Element Analysis

Compared with other materials, high-volume fraction aluminum-based silicon carbide composites (hereinafter referred to as SiCp/Al) have many advantages, including high strength, small change in the expansion coefficient due to temperature, high wear resistance, high corrosion resistance, high fatigue resistance, low density, good dimensional stability, and thermal conductivity. SiCp/Al composites have been widely used in aerospace, ordnance, transportation service, precision instruments, and in many other fields. In this study, the ABAQUS/explicit large-scale finite element analysis platform was used to simulate the milling process of SiCp/Al composites. By changing the parameters of the tool angle, milling depth, and milling speed, the influence of these parameters on the cutting force, cutting temperature, cutting stress, and cutting chips was studied. Optimization of the parameters was based on the above change rules to obtain the best processing combination of parameters. Then, the causes of surface machining defects, such as deep pits, shallow pits, and bulges, were simulated and discussed. Finally, the best cutting parameters obtained through simulation analysis was the tool rake angle γ0 = 5°, tool clearance angle α0 = 5°, corner radius r = 0.4 mm, milling depth ap = 50 mm, and milling speed vc= 300 m/min. The optimal combination of milling parameters provides a theoretical basis for subsequent cutting.

Geometrical design of a crystal growth system guided by a machine learning algorithm

CrystEngComm ◽  
2021 ◽  
Author(s):  
Wancheng Yu ◽  
Can Zhu ◽  
Yosuke Tsunooka ◽  
Wei Huang ◽  
Yifan Dang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Crystal Growth ◽  
High Speed ◽  
Learning Algorithm ◽  
Computational Techniques ◽  
Machine Learning Algorithm ◽  
Geometrical Design ◽  
Large Numbers ◽  
Growth System ◽  
Speed Method

This study proposes a new high-speed method for designing crystal growth systems. It is capable of optimizing large numbers of parameters simultaneously which is difficult for traditional experimental and computational techniques.

Regression Analysis of Predictions and Forecasts of Cloud Data Centre KPIs Using the Boosted Decision Tree Algorithm

2021 ◽  
Author(s):  
Thomas Weripuo Gyeera
Keyword(s):  
Decision Tree ◽  
Heterogeneous Computing ◽  
Learning Algorithm ◽  
High Volume ◽  
Dynamic Allocation ◽  
Test Bed ◽  
Cloud Data ◽  
On Demand ◽  
Boosted Decision Tree ◽  
Data Centres

<div>The National Institute of Standards and Technology defines the fundamental characteristics of cloud computing as: on-demand computing, offered via the network, using pooled resources, with rapid elastic scaling and metered charging. The rapid dynamic allocation and release of resources on demand to meet heterogeneous computing needs is particularly challenging for data centres, which process a huge amount of data characterised by its high volume, velocity, variety and veracity (4Vs model). Data centres seek to regulate this by monitoring and adaptation, typically reacting to service failures after the fact. We present a real cloud test bed with the capabilities of proactively monitoring and gathering cloud resource information for making predictions and forecasts. This contrasts with the state-of-the-art reactive monitoring of cloud data centres. We argue that the behavioural patterns and Key Performance Indicators (KPIs) characterizing virtualized servers, networks, and database applications can best be studied and analysed with predictive models. Specifically, we applied the Boosted Decision Tree machine learning algorithm in making future predictions on the KPIs of a cloud server and virtual infrastructure network, yielding an R-Square of 0.9991 at a 0.2 learning rate. This predictive framework is beneficial for making short- and long-term predictions for cloud resources.</div>

Pulp mill process closure: a review of global technology developments and mill experiences in the 1990s

2004 ◽  
Vol 50 (3) ◽  
pp. 183-194 ◽  
Author(s):  
S.C. Stratton ◽  
P.L. Gleadow ◽  
A.P. Johnson
Keyword(s):  
Manufacturing Industry ◽  
Pollution Prevention ◽  
Optimal Solution ◽  
Pulp Mill ◽  
Thermomechanical Pulp ◽  
Pulp Mills ◽  
Oxygen Delignification ◽  
Manufacturing Operations ◽  
The Impact ◽  
Mill Process

The impact of effluent discharges continues to be an important issue for the pulp manufacturing industry. Considerable progress has been made in pollution prevention to minimize waste generation, so-called manufacturing “process closure.” Since the mid-1980s many important technologies have been developed and implemented, many of these in response to organochlorine concerns. Zero effluent operation is now a reality for a few bleached chemi-thermomechanical pulp (BCTMP) pulp mills. In kraft pulp manufacturing, important developments include widespread adoption of new cooking techniques, oxygen delignification, closed screening, improved process control, new bleaching methods, and systems that minimize pulping liquor losses. Coupled to this is a commitment to reduce water use and maximize reuse of in-mill process streams. Some companies pursued bleach plant closure, and many have been successful in eliminating a portion of their bleaching wastewaters. However, the difficulties inherent in closing bleach plants are considerable. For many mills the optimal solution has been found to be a high degree of closure coupled with external biological treatment of the remaining process effluent. No bleach plants at papergrade bleached kraft mills are known to be operating effluent-free on a continuous basis. This paper reviews the important worldwide technological developments and mill experiences in the 1990s that were focused on minimizing environmental impacts of pulp manufacturing operations.

scholarly journals Research on machine learning Algorithm optimization based on 0-1 coding

2021 ◽  
Vol 2083 (4) ◽  
pp. 042086
Author(s):  
Yuqi Qin
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Manufacturing Industry ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Algorithm Optimization ◽  
The Core ◽  
Coding Method ◽  
Discrete Manufacturing

Abstract Machine learning algorithm is the core of artificial intelligence, is the fundamental way to make computer intelligent, its application in all fields of artificial intelligence. Aiming at the problems of the existing algorithms in the discrete manufacturing industry, this paper proposes a new 0-1 coding method to optimize the learning algorithm, and finally proposes a learning algorithm of “IG type learning only from the best”.

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